Peter Fisk

Over the past two decades, Asia has transformed from being the world’s factory to becoming its innovation engine. From super apps and AI platforms to smart logistics and consumer electronics, Asian companies are now at the forefront of technological disruption and business reinvention. They are reshaping industries, influencing global standards, and outpacing many Western counterparts—not just in scale but in the speed and imagination of innovation.

How did this transformation happen? And why are companies like Bytedance, DJI, Grab, Jio, Haier, Ping An, Sea and Tencent now regarded as among the world’s most innovative?

1. Massive, Demanding, Digital-First Markets

Asia’s biggest asset is its population: more than 4.7 billion people, including the fastest-growing middle class in the world. These markets are mobile-first, young, and digitally native—forcing companies to innovate quickly and at scale.

Take Bytedance, the parent company of TikTok. Founded in China in 2012, it leveraged AI-driven personalization to reimagine content consumption. Unlike platforms that rely on social graphs, TikTok’s content is algorithmically curated, creating an addictive user experience that has since been copied globally. The Chinese market’s diversity and size gave Bytedance an ideal sandbox to refine this model before going global.

Similarly, Grab, founded in Malaysia and now headquartered in Singapore, has evolved from a ride-hailing app into Southeast Asia’s leading super app. It integrates transportation, payments, food delivery, insurance, and more—meeting the needs of consumers in fragmented, infrastructure-light environments. This model was born out of necessity in a region where digital infrastructure had to leapfrog traditional systems.

2. Innovating for Inclusion and Scale

Asian innovators often solve problems unique to their regions—lack of physical infrastructure, informal economies, or underserved populations. These constraints inspire inclusive innovation that often proves globally relevant.

Jio, the Indian telecom and digital services company launched by Reliance Industries in 2016, disrupted India’s telecom market with free calls and ultra-low data costs. By building its network from scratch using 4G and investing heavily in digital content, cloud, and services, Jio connected over 450 million Indians online in just a few years. This was not just innovation in pricing—it was a digital nation-building strategy. Now, Jio is extending into healthcare, education, fintech, and AI with homegrown ambition.

Ping An, one of the world’s largest insurance and financial services companies, turned itself into a technology-first enterprise. It uses AI, big data, and blockchain to serve over 220 million customers and 500 million internet users. Its Good Doctor app became China’s leading health tech platform, with AI-driven diagnostics and 24/7 telemedicine. Ping An’s transformation reflects how Asian firms are embedding tech at the core of traditional sectors like insurance, banking, and healthcare.

3. Reimagining Business Models

Many Asian companies are not just adopting Western models—they are inventing new ones. The concept of the super app, for instance, did not originate in Silicon Valley but in China and Southeast Asia.

Tencent’s WeChat is a prime example. Starting as a messaging app, it became a platform for payments, news, games, shopping, and government services. By enabling third-party mini-programs within the app, Tencent created a mobile-first operating system for everyday life. This level of integration, with seamless UX across services, is rare outside Asia and has influenced global tech giants like Meta and PayPal.

Similarly, Sea Group, based in Singapore and best known for its gaming arm Garena and e-commerce platform Shopee, has created regionally tailored services that blend social engagement with transaction. Shopee’s gamified shopping experience and localized promotions turned it into a leading e-commerce player across Southeast Asia and Latin America.

4. Flexible Ownership and Ambitious Leadership

Ownership structures in Asia are often more flexible and founder-led than in the West. This allows for bold decisions, long-term thinking, and alignment between innovation and execution.

Consider Haier, the Chinese home appliance giant. It reinvented itself into a modular, platform-driven organization using a management philosophy called “Rendanheyi”—empowering small, autonomous teams to act like startups. Haier’s shift from manufacturing to an ecosystem-based innovation model allowed it to acquire GE Appliances in the US and become a leader in smart home solutions globally.

Asian founders and leaders often exhibit a unique blend of nationalism and entrepreneurial drive. Masayoshi Son of SoftBank exemplifies this with his long-term, global investment thesis built around AI and connectivity. Similarly, Mukesh Ambani’s Jio strategy was as much about transforming India as it was about dominating markets.

5. Supportive Governments and Innovation Ecosystems

Governments across Asia have played a crucial role in enabling innovation through infrastructure, policy, and funding.

In China, the government’s “Made in China 2025” strategy incentivized R&D in AI, robotics, and semiconductors. The creation of special economic zones and digital infrastructure hubs enabled companies like DJI (the global leader in drones) and SenseTime (a major AI player) to scale rapidly.

Singapore and South Korea have long invested in education, IP protection, and startup incubation. Singapore’s EDB (Economic Development Board) and Temasek have backed ventures in fintech, biotech, and green energy. South Korea’s Samsung and Hyundai ecosystems are supported by government-led research and supplier networks, allowing them to stay globally competitive in semiconductors, mobility, and clean tech.

Even in India, digital public goods like Aadhaar (digital identity) and UPI (real-time payments infrastructure) have given startups a massive platform to innovate and scale. IndiaStack is now being exported to other developing economies.

6. Bold Visions, Global Playbooks

Asian innovators are increasingly building for the world. Ant Group, for example, pioneered mobile payments with Alipay and now drives global fintech innovation. Tokopedia and Gojek merged to create GoTo Group, aiming to be Southeast Asia’s leading digital ecosystem.

Japanese firms like Rakuten are combining e-commerce, fintech, and mobile telecoms under one brand, while NTT is pushing the boundaries of smart cities and digital twins. In South Korea, Kakao has replicated the super app model with a creative edge in content, entertainment, and NFTs.

Even in frontier tech, Asia is advancing rapidly. SK Hynix and TSMC are global semiconductor leaders. Baidu and Naver are pioneering autonomous vehicles and language AI. In Japan, Preferred Networks is pushing the edge in deep learning for industrial automation and robotics.

7. A Future Shaped in Asia

The next decade of innovation will be increasingly shaped in Asia—not just because of its population or capital, but because of its mindset.

Asian companies are not afraid to leapfrog. They build for complexity, scale, and inclusion. They merge physical and digital worlds. They rewire traditional industries with AI, data, and platform logic. And they move fast.

As the world grapples with climate change, aging populations, urban congestion, and economic inequality, Asia’s innovation playbook—problem-solving at scale, embedding tech everywhere, and integrating services around user needs—may become the global blueprint.

Companies like Bytedance, Grab, Jio, Haier, Ping An, and Tencent are just the beginning. The next wave—from Indonesia to India, Japan to Korea, China to Vietnam—is coming. And they’re not just competing with Silicon Valley. They’re defining what innovation looks like in the 21st century.

Predicting which companies will see the most significant stock market growth by 2030 involves identifying those best positioned at the intersection of exponential technologies, structural global shifts, and strong execution. These are companies driving or benefiting from megatrends such as AI, climate tech, biotech, digital transformation, and changing demographics.

Here is a curated selection of companies across sectors and geographies that are well-positioned for outsized growth — along with the reasons why. (Remember these are not investment recommendations, simply an analysis of markets and companies, and illustration of their value-based growth potential!).

For each company we consider the strategic significance of the company—”why” it is well-positioned to grow significantly. We also identify the “2030 growth catalyst”, meaning the specific events likely to supercharge the company’s growth by 2030, and the broader “growth drivers”, ie the structural, longer-term factors that will sustain and support the company’s growth over time – technologies, capabilities, business models, partnerships, or geographic expansion.

1. Nvidia … powering the AI revolution

Founded in 1993 by Jensen Huang, Chris Malachowsky, and Curtis Priem, NVIDIA began as a graphics chip company for gaming. Under CEO Jensen Huang, it has evolved into a dominant force in AI computing, data centers, autonomous vehicles, and more. It grew exponentially with the rise of GPU computing and now leads the AI revolution with its full-stack AI platform, including CUDA software, GPUs, and supercomputers like DGX.

• 2025 Market Cap: $3 trillion
• 2030 Potential Market Cap: $6 trillion
• Why: The foundational infrastructure provider for AI, from GPUs to full-stack AI computing platforms.
• 2030 Growth Catalyst: Enterprise adoption of generative AI, AI-as-a-platform services, expansion into robotics and autonomous systems.
• Growth Drivers:
  • World’s leading supplier of GPUs, central to AI, machine learning, and edge computing.
  • Expanding into AI software, networking, and data centre platforms.
  • Strong ecosystem dominance, high margins, and strategic leadership in generative AI.

2. ASML … the machines that make semiconductors

Founded in 1984 as a joint venture between Philips and ASM International, ASML is headquartered in Veldhoven, Netherlands. Under CEO Peter Wennink, it has become the global monopoly in extreme ultraviolet (EUV) lithography. ASML plays a pivotal role in the semiconductor value chain, enabling the production of the smallest and most advanced chips. Its technology is critical to Moore’s Law and the future of AI and high-performance computing.

• 2025 Market Cap: $500 billion
• 2030 Potential Market Cap: $1.2 trillion
• Why: Sole supplier of EUV lithography, essential for advanced semiconductor manufacturing.
• 2030 Growth Catalyst: Surge in demand for next-gen chips across AI, 5G, and quantum.
• Growth Drivers:
  • High-margin, high-barrier tech monopoly
  • Long-term supplier contracts with TSMC, Intel, Samsung
  • Expanding capacity to meet global reshoring demand

3. Tesla … accelerating the transition to clean energy

• 2025 Market Cap: $750 billion
• 2030 Potential Market Cap: $2.5 trillion
• Why: Beyond EVs: energy, AI robotics, and autonomy leader.
• 2030 Growth Catalyst: Commercialisation of autonomous vehicles and Tesla Energy at scale.
• Growth Drivers:
  • Energy storage and solar business
  • Robotaxi network
  • Dojo AI training platform and humanoid robots

4. BYD … dreams driving the future of mobility

BYD (Build Your Dreams) was founded in 1995 by Wang Chuanfu as a rechargeable battery company. It entered the auto industry in 2003 and became one of the world’s largest EV makers. Known for vertical integration, BYD manufactures its own batteries, chips, and EV components. Backed by investors like Warren Buffett, it leads China’s EV market and is rapidly expanding into global markets.

• 2025 Market Cap: $100 billion
• 2030 Potential Market Cap: $450 billion
• Why: Vertically integrated EV manufacturer dominating China and expanding globally.
• 2030 Growth Catalyst: Global mass-market EV adoption, battery exports.
• Growth Drivers:
  • In-house batteries and chips
  • Affordable EV models for emerging markets
  • Global expansion (ASEAN, LATAM, EU)

5. Reliance Jio … becoming India’s leading lifestyle brand

• 2025 Market Cap: $250 billion
• 2030 Potential Market Cap: $800 billion
• Why: India’s most diversified conglomerate, pivoting from oil to digital, retail, and clean energy.
• 2030 Growth Catalyst: Jio as India’s dominant digital ecosystem across telecom, finance, and commerce.
• Growth Drivers:
  • Jio Financial, JioMart, JioCinema, and 5G services
  • Green hydrogen and solar investments
  • 1.4B person digital consumer base

6. MercadoLibre … the digital backbone of Latin America

Founded in 1999 by Marcos Galperin in Argentina, MercadoLibre is Latin America’s leading e-commerce and fintech platform. It operates in 18 countries, offering online marketplaces, digital payments, logistics, and credit services. With its MercadoPago and MercadoEnvios platforms, it serves both consumers and merchants. Under Galperin’s leadership, it continues to scale digital services in a region with growing internet penetration and fintech demand.

• 2025 Market Cap: $80 billion
• 2030 Potential Market Cap: $350 billion
• Why: Amazon + PayPal of Latin America with strong moat in logistics and fintech.
• 2030 Growth Catalyst: Latin America’s digital finance revolution and rising e-commerce penetration.
• Growth Drivers:
  • MercadoPago’s banking and credit services
  • Logistics and fulfillment infrastructure
  • Cross-border commerce expansion

7. Eli Lilly … biotech powerhouse, AI-powered drugs

• 2025 Market Cap: $850 billion
• 2030 Potential Market Cap: $2.2 trillion
• Why: Dominates obesity and diabetes treatment with Mounjaro; strong biotech pipeline.
• 2030 Growth Catalyst: Mainstream use of GLP-1 drugs for metabolic disease and longevity.
• Growth Drivers:
  • FDA approvals for Alzheimer’s and cancer drugs
  • Global rollout of Mounjaro/Zepbound
  • Expansion in emerging health markets

8. TSMC … the world’s largest chip maker

Founded in 1987 by Morris Chang, TSMC (Taiwan Semiconductor Manufacturing Company) pioneered the pure-play foundry model. Headquartered in Hsinchu, Taiwan, and led by C.C. Wei, it is the world’s largest contract chip manufacturer. TSMC produces the most advanced chips for top tech companies globally and is central to innovation in AI, smartphones, and high-performance computing.

• 2025 Market Cap: $600 billion
• 2030 Potential Market Cap: $1.2 trillion
• Why: World’s most advanced semiconductor foundry powering Apple, Nvidia, AMD, etc.
• 2030 Growth Catalyst: AI, automotive, and IoT chips becoming core infrastructure.
• Growth Drivers:
  • Geographical diversification (US, Japan, EU fabs)
  • Leadership in 3nm and advanced packaging
  • Supply chain resilience and premium pricing

9. NextEra Energy … America’s leading clean energy business

Founded in 1984 and headquartered in Florida, NextEra Energy is the parent of Florida Power & Light and NextEra Energy Resources. Under CEO John Ketchum, it leads in wind and solar energy generation in North America. The company is at the forefront of the clean energy transition, investing in grid modernization and storage, and leveraging policy support like the Inflation Reduction Act.

• 2025 Market Cap: $150 billion
• 2030 Potential Market Cap: $300 billion
• Why: Largest renewable energy generator in the US.
• 2030 Growth Catalyst: Scaling solar, wind, and grid-scale battery storage.
• Growth Drivers:
  • IRA subsidies and regulatory tailwinds
  • Digital grid infrastructure
  • Distributed energy services for businesses and consumers

10. ARM … designing next generation chips

ARM was founded in 1990 as a joint venture between Acorn Computers, Apple, and VLSI Technology. Based in Cambridge, UK, it designs energy-efficient chip architectures widely used in mobile and embedded systems. Now led by CEO Rene Haas, ARM has expanded into data centers and AI edge computing. Its flexible licensing model powers over 250 billion chips globally, making it foundational to modern electronics.

• 2025 Market Cap: $120 billion
• 2030 Potential Market Cap: $400 billion
• Why: Dominant CPU architecture for mobile, AI edge, IoT, and increasingly cloud.
• 2030 Growth Catalyst: AI at the edge, IoT proliferation, and high-margin licensing.
• Growth Drivers:
  • Embedded AI chips for smart devices
  • Expanding royalty streams from data centers
  • Strategic shift toward value-based licensing

In summary

In addition here are some “bonus picks” … smaller, high-potential, higher-risk companies that could see significant stock market growth by 2030:

1. UiPath … smart robotics from Romania

Founded in 2005 in Romania by Daniel Dines and Marius Tîrcă, UiPath is a global leader in robotic process automation (RPA). Headquartered in New York, the company helps enterprises automate repetitive tasks across systems using AI-powered bots. Led by co-founder and CEO Daniel Dines, UiPath has grown rapidly with a strong customer base in finance, healthcare, and logistics. Its automation-first platform is expanding into intelligent automation and process mining.

• 2025 Market Cap: $10 billion
• 2030 Potential Market Cap: $100 billion
• Why: UiPath is a leader in robotic process automation (RPA), offering AI-powered tools that automate repetitive tasks in enterprise workflows. With the convergence of AI and automation, demand for intelligent systems to boost productivity is surging.
• 2030 Growth Catalyst: Enterprise AI adoption, mass automation of back-office functions, AI copilots for every worker.
• Growth Drivers:
  • Expansion into end-to-end AI-powered automation platforms
  • Deeper integrations with cloud platforms (Microsoft, AWS, Google)
  • Growing demand in finance, healthcare, government sectors
  • Upselling AI-based orchestration and analytics services

2. Palantir … making sense of complex data

Founded in 2003 by Peter Thiel, Alex Karp, and others, Palantir started as a data analytics company for defense and intelligence. Under CEO Alex Karp, it expanded into commercial sectors with platforms like Foundry and Gotham that help organizations integrate and make sense of complex data. With increasing adoption in healthcare, finance, and manufacturing, Palantir is gaining traction as AI-driven decision-making becomes mission-critical.

• 2025 Market Cap: $55 billion
• 2030 Potential Market Cap: $300 billion
• Why: Palantir specializes in AI-driven big data analytics, serving defense, intelligence, and commercial clients. It’s gaining traction for its Foundry and AIP platforms that offer mission-critical decision-making tools powered by LLMs.
• 2030 Growth Catalyst: AI-infused enterprise decision platforms; scaled use across commercial sectors and public infrastructure.
• Growth Drivers:
  • Accelerating shift from bespoke to scalable AI platforms
  • Strong US and NATO government contracts (defense, healthcare, intelligence)
  • Commercial expansion in pharma, manufacturing, energy
  • Thought leadership in AI ethics, security, and national resilience

3. Sea Group … Singapore retail meets entertainment

• 2025 Market Cap: $30 billion
• 2030 Potential Market Cap: $120 billion
• Why: Sea operates Southeast Asia’s dominant e-commerce (Shopee), digital financial services (SeaMoney), and gaming (Garena). With Southeast Asia’s growing middle class and digital infrastructure, Sea is well positioned as a regional tech super-app.
• 2030 Growth Catalyst: Regional super app combining shopping, fintech, and entertainment in one platform.
• Growth Drivers:
  • Shopee scaling e-commerce in Indonesia, Vietnam, Philippines, Brazil
  • SeaMoney expansion into payments, insurance, lending
  • Return of gaming growth via Garena’s new titles or cross-border IP
  • Digital infrastructure and logistics play in fast-growing economies

4. Illumina … leading the genomics revolution

Founded in 1998 and based in San Diego, Illumina is a pioneer in DNA sequencing technologies and genomics solutions. The company, now led by CEO Jacob Thaysen, enables researchers, hospitals, and pharmaceutical companies to sequence genomes quickly and affordably. Despite recent strategic challenges, it remains critical to the advancement of precision medicine, population genomics, and biotech R&D.

• 2025 Market Cap: $30 billion
• 2030 Potential Market Cap: $120 billion
• Why: Illumina is the global leader in DNA sequencing technology. Its platforms power genomics research, precision medicine, and diagnostics, all central to the healthcare revolution.
• 2030 Growth Catalyst: The “genomics-as-infrastructure” moment: sequencing becomes routine for population health, cancer, rare diseases, and AI-informed medicine.
• Growth Drivers:
  • Rapid adoption of genomic testing by health systems
  • Falling cost of sequencing (towards $100/genome)
  • New clinical diagnostics partnerships and AI applications
  • Strategic spinouts or divestments (e.g. Grail) to focus on core

5. CleanSpark … sustainable bitcoin mining

Founded in 1987 and headquartered in Nevada, CleanSpark is a Bitcoin mining and energy technology company that focuses on sustainable mining powered by renewables. Led by CEO Zachary Bradford, CleanSpark distinguishes itself by leveraging energy-efficient operations and vertically integrated power sourcing. The company is also investing in microgrids and grid-interactive energy systems, making it a unique clean-tech and crypto hybrid growth story.

• 2025 Market Cap: $2 billion
• 2030 Potential Market Cap: $12 billion
• Why: CleanSpark provides sustainable Bitcoin mining and microgrid energy solutions. It bridges crypto infrastructure with renewable energy tech — offering a scalable model for energy-intensive industries.
• 2030 Growth Catalyst: Convergence of clean energy + crypto infrastructure + grid balancing services.
• Growth Drivers:
  • Renewable-powered mining leadership (low carbon footprint)
  • Expansion into smart microgrid tech and virtual power plants
  • Leverage of carbon credits and green finance
  • Positioned well in US-based digital asset ecosystem with policy tailwinds

6. KlimaDAO … blockchain for climate change

Launched in 2021, KlimaDAO is a decentralized autonomous organization (DAO) aiming to accelerate climate action through blockchain and carbon markets. Built on the Polygon network, it tokenizes carbon credits into the KLIMA token, incentivizing demand for verified carbon offsets. KlimaDAO operates without a central corporate leadership but is stewarded by a community of developers, climate activists, and governance token holders. It seeks to create a transparent, liquid, and scalable market for environmental assets, and is part of a broader trend toward regenerative finance (ReFi).

• 2025 Market Cap: $100 million (token-based market cap)
• 2030 Potential Market Cap: $10 billion
• Why: KlimaDAO is a decentralized autonomous organization creating a programmable carbon market via blockchain. It tokenizes carbon credits to create transparency and liquidity in the voluntary carbon market.
• 2030 Growth Catalyst: Institutional and government adoption of on-chain carbon markets and climate finance infrastructure.
• Growth Drivers:
  • Rise of nature-based carbon markets and climate tokens
  • Integration with ESG reporting platforms and supply chains
  • Partnerships with climate registries and offset projects
  • Regulation and demand for transparent carbon accounting

In today’s world of accelerating change, disruption is no longer the exception, it is the norm.

Technology, climate imperatives, shifting customer expectations, and geopolitical volatility are reshaping the business landscape. In this environment, incremental improvement is no longer sufficient. True business transformation—a fundamental reinvention of how a company creates and captures value – is necessary for survival and long-term success.

But what does transformation really mean? At its core, transformation is about reimagining the future of the business: what it stands for, how it competes, how it works, and how it wins. It’s a step beyond operational change or digital upgrades. It is a whole-system shift—combining purpose, strategy, operating model, culture, capabilities, and performance.

What is business transformation?

Business transformation involves a step change in performance driven by a shift in core business logic—how value is created and delivered. This could mean moving from products to platforms, from fossil fuels to renewables, from a local to a global model, or from analogue to digital. In some cases all of these.

True transformation usually touches four interconnected domains:

• Reimagining purpose and vision – defining the ‘why’ of the organisation; its role in a rapidly changing world, its aspirations, and what it uniquely offer, supported by a vision of what better can look like.

• Redefining strategy and priorities – refocusing ‘where and how’ to play – reshaping the strategy, business model, customer propositions, innovating products and services, and future business portfolio.

• Reinventing culture and organisation – creating the internal conditions—leadership, mindset, capabilities, behaviours, structures, and systems—that enable change and innovation.

• Rewiring operations and performance – shifting the core activities, capabilities, and technology infrastructure to support new ways of working, and delivering performance short and long-term, for sustained value creation.

At its best, business transformation results in significant growth, market leadership, and renewed relevance. It can mean, over time, a fundamental shift in the core business. It can transform performance, creating significant new profit streams, and doubling or tripling the market value over 4-5 years. At its worst, it is superficial, disconnected, and fails to deliver impact. All the more reason to get it right.

Transformational companies around the world

Some companies have stood out in recent years for their ability to successfully reinvent themselves, responding to massive shifts with agility and vision.

DSM … science-led reinvention

Originally a Dutch coal mining company, DSM has continuously reinvented itself for over a century. Most recently, it divested from chemicals and refocused on biosciences, nutrition, and health. The merger with Firmenich accelerated this pivot, creating a purpose-driven leader in sustainable ingredients. DSM’s transformation illustrates how companies can shed legacy businesses to focus on high-growth, impact-led markets.

Schneider Electric … the world’s most sustainable company

Once a provider of electrical components, Schneider Electric transformed into a global leader in energy management and automation. Its purpose—“to be the digital partner for sustainability and efficiency”—has guided a decade-long pivot towards software, smart systems, and decarbonisation. The company reorganised around digital platforms and embedded sustainability into every part of its strategy and culture. It now helps thousands of companies monitor and reduce their carbon footprint while achieving sustained double-digit growth.

Fujifilm … from camera film to healthcare 

When digital photography disrupted its core market, Fujifilm—unlike Kodak—chose to radically reinvent itself. It leveraged its deep expertise in chemistry and materials to pivot into healthcare, cosmetics, and advanced materials. Its diversification into medical imaging, regenerative medicine, and pharmaceuticals allowed it not only to survive the death of film but to thrive in new sectors. Fujifilm’s transformation is a masterclass in strategic foresight, reinvention of capabilities, and disciplined execution.

Ping An … from insurer to multi-sector ecosystem

Ping An, one of world’s largest insurers, has undergone a radical transformation into a technology-driven ecosystem for financial and healthcare services. Recognising the disruptive potential of digital platforms, Ping An invested in AI, blockchain, and cloud, creating industry-leading apps like Good Doctor (healthcare) and Lufax (finance). Its strategy involved turning traditional financial services into tech-powered, data-rich customer experiences—while also developing internal AI tools to increase operational efficiency. Ping An’s transformation exemplifies how traditional players can redefine their core by embedding technology at scale.

Microsoft … ready to win in an age of AI

Under CEO Satya Nadella, Microsoft reimagined itself from a PC-centric, legacy software firm into a global cloud powerhouse. Nadella reinvigorated Microsoft’s purpose “to empower every person and every organization on the planet to achieve more,” steering it towards cloud infrastructure (Azure), remote collaboration (Teams), and generative AI (Copilot). The transformation was cultural as well as strategic—moving from internal rivalry to openness and innovation. The result: a trillion-dollar leap in market value and renewed relevance.

IKEA … from flatpacks to circularity 

IKEA has evolved from a low-cost furniture retailer to a purpose-led sustainability leader. It has committed to becoming climate positive by 2030, embraced circular product design, and explored new service models including buy-back, rentals, and urban formats. The transformation includes not only rethinking its supply chain and materials, but also transforming its culture—empowering employees to innovate and enabling faster experimentation.

On … scaling a start-up into lifestyle leader

Swiss sportswear brand On Running combines elite performance with sustainability. Its transformation is unique—scaling rapidly while maintaining its core design ethos and environmental focus. The CFO played a pivotal role, helping develop a circular subscription model for recyclable shoes and using data to optimise global expansion. It exemplifies how newer companies can build transformation into their growth journey from the start.

Relentless reinvention … once you’ve transformed, transform again

Business transformation, of course, is no longer a one-off project, it’s a relentless, continuous process. As markets evolve due to technological disruption, shifting customer expectations, environmental challenges, and geopolitical uncertainty, companies must constantly reinvent themselves to stay competitive. Transformation is not just about reacting to change; it’s about building the capabilities to anticipate, shape, and lead it.

This requires becoming an ambidextrous organisation—able to simultaneously optimize today’s core business while exploring and scaling tomorrow’s opportunities. It means balancing operational efficiency with strategic innovation, and fostering cultures where adaptability and experimentation thrive alongside discipline and performance.

Amazon exemplifies this duality, continually reinventing its model—from retail to cloud services, logistics, and AI—while maintaining tight operational excellence. Schneider Electric has pivoted from hardware manufacturing to smart energy solutions, combining legacy strengths with digital innovation. DBS Bank, once a slow-moving institution, has transformed into a technology-driven, customer-centric bank by embedding agile practices and a startup mindset across the organization.

Agility is central to this model—organizational structures must be flexible, decision-making decentralized, and leadership aligned on a shared purpose. Spotify’s “squad” model, for instance, empowers cross-functional teams to experiment quickly and bring new value to market fast.

Many organisations seek to build a dual approach to transformation, most simply illustrated by the double portfolio of “exploit and explore” – developing a portfolio of initiatives to enhance today’s business, while also initiatives to create the future. You need to work on both, and gradually explore becomes exploit. Some companies do this structurally like Ping An, with co-CEOs, one exploiting its core insurance business, the other developing new businesses in healthcare, mobility and real estate. Or think about Alphabet’s X company, working on exploring the future beyond search. Investors, of course, seek both.

Ultimately, transformation is no longer about fixing broken parts; it’s about continuously reimagining the whole—products, models, ecosystems, and ways of working. Businesses that embed this capacity to evolve—who see reinvention as a muscle, not a moment—will be best placed to thrive in an age where change is the only constant.

3 of the biggest challenges for transformation

Even the most visionary leaders face deep challenges in delivering transformation at scale. Three of the most critical and complex leadership challenges are balancing a portfolio of innovations, navigating dual transformation (external and internal), and aligning the board and executive team.

1. Balancing today and tomorrow

Leaders must manage a dynamic portfolio of innovations that span immediate improvements and longer-term reinvention. This means simultaneously optimising the core business (Horizon 1), incubating adjacent innovations (Horizon 2), and exploring radical new ventures (Horizon 3). The challenge is resource allocation: how to invest in transformative opportunities without compromising current performance. Leaders must create space for experimentation while maintaining operational excellence. This tension between “running the business” and “changing the business” often stretches leadership focus and organisational attention. This demands leaders who are performer-transformers, and a dual transformation approach.

2. Combining strategic and organisational change

Transformation must occur both externally—through a new strategic vision, value proposition, and business model—and internally, through organisational structure, culture, processes, and capabilities. It’s not enough to define a new direction; leaders must also mobilise the company to deliver it. This requires orchestration across functions, integration of digital and sustainability agendas, and active engagement with customers, partners, and ecosystems. Internally, leaders must rewire the organisation for agility, collaboration, and learning. That means letting go of legacy hierarchies, empowering cross-functional teams, and developing new talent and mindsets. Strategic ambition must be matched by organisational readiness.

3. Aligning the board and executive team

Perhaps the most overlooked but critical challenge is aligning the leadership at the top. True transformation starts with a shared dream—a compelling vision that stretches beyond today’s constraints. Yet many boards are anchored in risk management and short-term financials, while transformation requires bold bets and long-term thinking. Leaders must bridge this gap, building trust, framing transformation in terms of future value creation, and managing performance across multiple time horizons. Within the executive team, cohesion is vital: alignment of goals, clarity of roles, and a shared commitment to lead the change. Without unified leadership, even the best strategies falter.

In short, transformation is as much about leadership as it is about strategy. It demands courage, coherence, and collaboration across the leadership system to shape the future and deliver it with discipline.

Accelerating the transformation journey

While every company’s journey is unique, successful transformations tend to follow several common principles and practices:

1. Start with purpose

Transformation is more likely to succeed when anchored in a compelling, future-facing purpose. Purpose inspires stakeholders, provides clarity during uncertainty, and guides strategic choices. Companies like Unilever and Danone have demonstrated how a strong sense of purpose can align business transformation with broader societal needs.

2. Envision a bold future

Companies need to articulate a bold vision—not just improve the present. A compelling narrative about the future energises teams and creates direction. Disney, for instance, didn’t just go digital—it reimagined itself as a streaming-first, direct-to-consumer company.

3. Redesign the business model

Transformation involves rethinking how the business creates and captures value. This may involve shifting from selling products to services, building platforms, or monetising data. Adobe transitioned from packaged software to cloud subscriptions. Ørsted moved from fossil fuels to renewable energy production. These moves require strategic courage and long-term investment.

4. Make culture a strategic asset

Culture often makes or breaks transformation. Companies need to foster learning, psychological safety, accountability, and openness to change. Microsoft’s cultural reset—from “know-it-alls” to “learn-it-alls”—was a critical enabler of its business transformation.

5. Invest in capability building

Transformation demands new skills—in AI, customer experience, sustainability, or agile working. Leading companies build these capabilities through training, hiring, and partnerships. DBS Bank, for example, turned itself into a “technology company in banking,” with internal accelerators and digital talent programs.

6. Structure for process and cultural agility

Legacy hierarchies often slow down transformation. High-performing companies redesign around networks, cross-functional teams, and empowered local units. Amazon’s “two-pizza teams” and Spotify’s squad model are iconic examples of agile structures supporting innovation.

7. Operationalise with systems and metrics

Transformation should be operationalised—translated into targets, incentives, and accountability systems. Schneider Electric embedded sustainability KPIs across the organisation, ensuring that purpose translated into performance.

8. Deliver quick wins while shaping the long term

Transformation is a marathon, but quick wins build momentum. Successful leaders sequence transformation to deliver near-term impact—such as new product lines, cost savings, or customer wins—while building the foundation for longer-term shifts.

Transformation as a leadership imperative

Great business transformations start with great leadership. In times of radical change, leaders play an essential role—not just as decision-makers, but as visionaries, mobilisers, architects, and role models. They must be bold enough to imagine a future beyond today’s business model, and disciplined enough to bring it to life across the entire organisation.

Here’s a detailed breakdown of what leaders must do to drive successful transformation—starting with vision, and following through with strategy, organisation, and execution—along with powerful real-world examples.

1. Have the courage to imagine a different future

The first and most critical responsibility of a transformative leader is to define a new vision that breaks from legacy logic. This demands courage—because it often involves letting go of what made the company successful in the past.

• Challenge the status quo. Leaders must ask: What business are we really in? What future could we shape—not just survive? They must be willing to explore and articulate a future that may not yet exist in their industry.
• Inspire ambition. A bold vision isn’t just a stretch target—it’s a compelling narrative about how the organisation can solve bigger problems, serve new needs, or change how value is created.

Satya Nadella became CEO in 2014 when Microsoft was in decline. He reframed its purpose as “empowering every person and every organization on the planet to achieve more,” moving beyond Windows to cloud, AI, and collaboration tools. His vision reinvigorated the company—and set the direction for all future strategy and culture.

Masahiko Uotani redefined Shiseido’s identity in the face of stagnation —from a Japanese cosmetics brand to a global beauty innovator focused on skin science and wellness. This allowed the company to pivot strategically into health, tech, and sustainability.

2. Translate vision into strategy and bold priorities

Vision without strategy is just a dream. Leaders must translate vision into clear, actionable priorities that redefine how the company competes.

• Redefine the business model. This might involve shifting from products to services, analog to digital, or linear to circular models. Leaders must make deliberate choices about where and how to play.
• Create new value propositions. What does the customer of the future need? Leaders must reimagine how they deliver value—and sometimes who they serve.
• Make hard trade-offs. Strategy is about focus. Leaders must say no to legacy businesses or behaviours that don’t support the transformation.

Henrik Poulsen led Ørsted’s exit from fossil fuels, reorienting the business around offshore wind. The strategy was clear: become a global leader in renewable energy. This meant divesting legacy assets and doubling down on future growth, even when it meant short-term pain.

Peter Ma led Ping An’s transformation from a traditional insurer into a tech-powered ecosystem. He strategically invested in AI, blockchain, and platforms like Good Doctor and Lufax—turning disruption into opportunity.

3. Mobilise the organisation and lead cultural change

No transformation succeeds without people. Leaders must create the conditions—mindsets, structures, and behaviours—for the organisation to embrace the future.

• Model the new mindset. Leaders must embody the values and behaviours they expect. If they want curiosity, agility, and collaboration, they must live them daily.
• Flatten hierarchy and empower teams. Organisational agility is critical. Leaders should enable cross-functional teams, decentralised decision-making, and rapid learning.
• Create psychological safety. Transformation involves risk and failure. Leaders must build trust, reward experimentation, and make it safe to speak up.

Shigetaka Komori led a deep cultural shift at Fujifilm, from a traditional, hierarchical firm to an entrepreneurial, innovation-led company. He protected R&D budgets during crisis and empowered teams to explore healthcare and materials science as new business areas.

Piyush Gupta transformed DBS Bank into “a tech company in banking.” He broke silos, invested in digital skills, and created an innovation culture that permeated all levels. DBS now regularly ranks among the world’s most innovative banks.

4. Align Systems, capabilities, and resources

Once strategy is defined and culture is shifting, leaders must align the business system to support the new model. This means rewiring the organisation for execution.

• Build future-ready capabilities. Leaders need to invest in the skills, technologies, and partnerships/ecosystems that the new strategy requires—whether it’s AI, sustainability, digital, or data.
• Redesign metrics and incentives. People do what they’re measured and rewarded for. Leaders must update KPIs, dashboards, and incentives to reflect transformation goals.
• Fund the future. Capital allocation is critical. Leaders must direct investment toward the bold bets—while responsibly managing legacy operations.

Jean-Pascal Tricoire embedded sustainability into the Schneider Electric’s performance metrics, linking executive pay to ESG outcomes. He built capabilities in digital energy and IoT, aligning strategy, talent, and structure to make sustainability a core growth engine.

Shantanu Narayen led Adobe’s shift from boxed software to cloud subscriptions. This meant new pricing, capabilities, and go-to-market models. The company retrained teams, revamped platforms, and restructured to deliver recurring customer value.

5. Sustain momentum and communicate relentlessly

Transformation isn’t a single initiative—it’s a multi-year journey. Leaders must maintain belief, energy, and accountability through ambiguity and change.

• Celebrate progress. Leaders must share quick wins, milestones, and success stories to maintain momentum, the belief and desire for change, and deliver progress.
• Communicate consistently. A compelling transformation story should be repeated often—internally and externally—so everyone understands the vision, their role, and the journey ahead.
• Evolve as the future unfolds. Leaders must stay adaptive, revisiting assumptions and updating direction as conditions change. Transformation never really ends.

Paul Polman made sustainability the centre of Unilever’s strategy and communicated it constantly—with investors, employees, and customers. He built long-term credibility and trust by showing how purpose and profit could reinforce each other.

John Iossifidis sustained momentum at Al Ghurair by driving transformation progressively at all levels, built around a strong sense of shared, meaningful purpose and vision, then empowering business units and managers to innovate and transform.

Relentless reinvention, the engine of value creation

Here are some compelling examples of the performance impact of business transformation, showing how companies that reimagined their purpose, strategy, and organisation achieved substantial profit growth, market value gains, and long-term resilience—often from entirely new business areas.

• Fujifilm‘s operating profit from new business segments grew by over 400% from 2010 to 2023. Market cap rose from around ¥1.5 trillion in 2010 to almost ¥6.5 trillion in 2024, a 4x growth in value creation.
• Microsoft‘s cloud revenues grew from $6.3B in 2015 to over $117B in 2024 (Azure, Office 365, Dynamics). Market cap rose from $340B in 2014 to over $3 trillion by 2024, which is a 780% increase.
• Schneider Electric‘s doftware and services now contribute around 50% of revenues and growing. Share price increased from €60 in 2015 to over €220 in 2024, reflecting nearly 4x market cap growth.
• PingAn’s tech platform revenue grew to 15% of total group revenue, from almost zero in 2013. Group market cap rose from $60B in 2010 to over $200B by 2021. Return on equity consistently above 18–20%.
• DSM‘s EBITDA margins improved by ~400 basis points over 10 years. Share price rose from €40 in 2010 to €160+ by 2022 representing 4x growth in market value.
• Unilever‘s “Sustainable Living Brands” grew 69% faster than the rest of the portfolio and delivered 75% of growth (2019). Market cap increased from £70B in 2010 to over £110B+ by 2024, despite market volatility.

Transformation is not a one-off change, but a journey over many years of many change projects, and ultimately becomes an ongoing capability. In an era of rapid disruption and rising stakeholder expectations, companies must continuously reinvent themselves to stay relevant and create value.

The leaders who succeed have their heads up not heads down – not just managing their companies, but shaping their futures.

The most innovative businesses today are reimagining what it means to create, deliver, and capture value.

Moving far beyond traditional “new” models – like auctions and exchanges, licensing and subscriptions – a next generation of business models is emerging — powered by AI, new technologies like blockchain and robotics, ecosystems, unlocking intangible assets, and catalysed by urgent environmental and social challenges.

Across every sector, these radical business models are reshaping how companies grow and compete. What defines them is not just their use of technology — but their redefinition of value itself. They:

• Shift from ownership to access, or from access to participation

• Replace centralised control with decentralised collaboration

• Convert data, trust, and relationships into monetisable assets

• Build value systems where profit and purpose reinforce each other

The future of business isn’t just digital. It’s distributed, decentralised, and deeply human in its impact.

These models are the blueprint for the next generation of business — intelligent, inclusive, and built around the intangible assets that now drive competitive advantage. In a world where code, creativity, and climate matter more than capital, these pioneers are not just changing business. They’re reinventing it.

Here’s a global look at some of the most radical business models reshaping industries today.

1. Brand-led ecosystems and cultural capital models

Examples: Patagonia (US), On Running (Switzerland), Glossier (US)

Certain brands today are building entire ecosystems around cultural identity, shared purpose, and community contribution. Patagonia’s transformation into a non-profit trust reshaped its business into an engine for climate action. Glossier used its loyal fanbase to co-create products and fuel word-of-mouth growth. On Running leverages its elite athlete endorsements and sustainability credentials to grow a purpose-led premium community.

Here, the brand itself becomes the platform — an intangible asset that compounds over time through trust, activism, and user collaboration.

• These businesses monetise cultural alignment, not just products. Brands capture ideas and propositions that are much more than technology. Their model grows stronger the more people believe in it.

2. Data-native platforms and relationship-driven ecosystems

Examples: Tesla (US), Bytedance (China), Ping An (China)

Some companies have made data their central business model. Tesla doesn’t just sell cars; it continuously collects driving data to improve its autonomous systems and energy products. Ping An, a Chinese financial services group, builds interconnected services — from health to banking to insurance — around deep customer data and long-term trust.

In these models, relationships — often invisible — become the key strategic asset. The more a business knows about its users, the more predictive and sticky its offerings become.

• Data becomes the flywheel. The more it’s used, the more value it creates — forming a self-reinforcing advantage that’s hard to replicate.

3. Regenerative and circular value models

Examples: Notpla (UK), Bext360 (Africa/US), TerraCycle/Loop (US)

These models embed sustainability and circularity into the business logic itself. Notpla, a London startup, makes biodegradable packaging from seaweed. Bext360 uses blockchain and AI to trace every coffee bean back to its origin, rewarding sustainable farming practices. Loop, developed by TerraCycle, builds reusable packaging systems for brands like Nestlé and Unilever.

Here, transparency, traceability, and customer trust become key intangible assets. The brand value is inseparable from environmental impact and social equity.

• Consumers increasingly demand climate-positive action — not just neutrality. These businesses are turning sustainability into a competitive advantage, not a compliance burden.

4. AI-native autonomous enterprises

Examples: Lindy.ai (US), Cognosys (Global), Hypertype (EU)

These businesses don’t just use AI — they are built around it. Entire workflows, decision-making structures, and customer interactions are being run by AI agents and autonomous systems. Lindy.ai, for instance, creates a personalised “chief of staff” AI that handles scheduling, communication, and task prioritisation. As these systems mature, companies may no longer need large administrative layers.

These models rely heavily on intangible assets — particularly proprietary data, user behaviour insights, and relationship history — to continuously learn and personalise services at scale.

• These businesses radically lower operational costs and redefine scale. A team of five people with the right AI stack can now rival the output of a 100-person company

5. DAOs: decentralized autonomous organisations

Examples: KlimaDAO (Global), CabinDAO (US), BitDAO (Singapore)

DAOs replace traditional corporate hierarchies with decentralized governance, where decisions are made by token-holders and enforced by smart contracts. KlimaDAO, for example, is building a blockchain-based economy around carbon credits. CabinDAO is creating a global co-living network governed by its digital community.

The value lies in community trust, governance transparency, and open-source code — intangible assets that replace boardrooms with consensus mechanisms.

• DAOs challenge the fundamental idea of top-down control, instead enabling collective ownership and direction — a model better suited to borderless, digital-native organizations

6. Tokenized ownership and micro-incentives

Examples: Rally.io (US), RealT (US), Sweat Economy (UK)

Tokenization enables companies to convert physical or digital value into fractional, tradeable ownership. RealT tokenizes real estate properties, allowing individuals to buy shares and receive rental income in crypto. Sweat Economy rewards people for physical activity with tokens that can be traded or spent. Rally.io enables creators to launch their own branded tokens, giving fans both access and investment-like upside.

Here, brands and communities are transformed into economic ecosystems where participation equals ownership — and engagement drives value.

• These models offer new ways to align incentives and unlock value that used to be passive or inaccessible.

7. Emotionally Intelligent AI Companions

Examples: Character.ai (US), Replika (US), Soul Machines (NZ)

A new category of business is emerging at the intersection of AI, emotion, and digital identity. Character.ai lets users build AI personalities that can engage in realistic conversations. Soul Machines develops digital humans for customer service, healthcare, and education — capable of reading and responding to emotions.

The core value is in relationships and trust — ephemeral yet deeply powerful assets. Users don’t just use these services; they form bonds with them.

• These models shift business from transactional to relational. You’re not just selling a service — you’re co-creating an emotional experience.

8. Embedded climate accounting and ethical nudging

Examples: Doconomy (Sweden), Earthchain (UK), Klarna’s carbon insights (Sweden)

These businesses integrate carbon tracking and impact measurement into daily spending. Doconomy’s credit card tracks users’ carbon footprints and can even block purchases beyond a set CO2 limit. Earthchain works with retailers to embed product-level climate impact at the point of sale.

Such models rely on consumer consciousness and ethical engagement — new forms of value that turn impact awareness into competitive edge.

• These models turn climate literacy into action, and offer companies a new lever for differentiation beyond price and product.

Reinventing the concept of business

These radical new business models are reshaping how companies grow and compete. However organisations have been reinventing their organisations for quite some time – a concept that became very popular with the advent of online platforms like Airbnb or Uber. Everyone wanted to reinvent their business as a platform, an exchange, or subscription.

So while many of these forms of business models are not new, its worth taking a few steps back to remind ourselves about what is a business model, what are the diverse options available, and how to we build them and transition from old to new.

The evolution of business models

Historically, businesses were built on simple models:

• Product sales (e.g., Ford selling cars),

• Service models (e.g., legal firms billing by the hour), or

• Retail and distribution (e.g., department stores buying wholesale and selling at a markup).

These models were linear and predictable — until they weren’t.

The digital revolution triggered a seismic shift. The rise of the internet in the 1990s enabled new intermediaries, such as eBay’s auction marketplace, and Amazon’s online retail model. In the 2000s, platforms and apps introduced further models based on ecosystems and data. Then came mobile, social media, and cloud computing — which reduced the costs of reaching customers and operating at scale.

Today, companies no longer compete only on products or services, but on the architecture of their business model. A superior product with an inferior model may lose. A simple idea with a breakthrough model can win big.

The expanding universe of business models

Over time, a wide range of business models has emerged. Some are classic, others born of digital transformation. Many combine multiple components. Here’s a snapshot of key types:

1. Product Sales

• The most traditional model: make something, sell it for more than it cost.

• Example: Toyota, Zara — selling cars or fashion with volume and margin.

2. Licensing

• Charging others to use intellectual property.

• Example: ARM Holdings licenses its chip designs to tech manufacturers around the world.

3. Razor and Blades

• Sell one item cheap (the razor), make money on the consumables (the blades).

• Example: HP printers and ink, or Nespresso and coffee pods.

4. Subscription

• Recurring revenue in exchange for ongoing access.

• Example: Netflix, Spotify, Adobe Creative Cloud.

5. Freemium

• Offer a free basic version; charge for premium features.

• Example: Dropbox, Zoom, and Notion — converting a small % of free users to paid ones.

6. Marketplace or Platform

• Connect buyers and sellers, take a cut.

• Example: Uber, Airbnb, Alibaba. These rely on building trust, liquidity, and network effects.

7. Franchise

• License the brand and model to independent operators.

• Example: McDonald’s, Anytime Fitness, or Marriott Hotels.

8. Auction and Exchange

• Dynamic pricing based on demand.

• Example: eBay, or StockX in the sneaker and fashion resale market.

9. Data Monetization

• Offer free services, and monetize user data or insights.

• Example: Google and Facebook generate vast revenues through targeted advertising.

10. Usage-Based or Pay-As-You-Go

• Charge only for what’s used — ideal for cloud computing or utilities.

• Example: AWS (Amazon Web Services), Twilio, Zipcar.

11. Crowdsourcing and Crowdfunding

• Leverage communities to build or fund products.

• Example: Kickstarter, GoFundMe, or Threadless for design.

12. Direct-to-Consumer (D2C)

• Bypass traditional retail to own customer relationships and data.

• Example: Warby Parker, Allbirds, or India’s boAt electronics.

13. Circular and Sharing Economy

• Based on reuse or shared access instead of ownership.

• Example: ThredUp, Fat Llama, or Lime scooters.

14. Ecosystem-Based

• Creating a constellation of products, services, and partners that reinforce each other.

• Example: Apple’s walled garden, or Tencent’s super app WeChat in China.

Examples of global business model innovation

• Haier evolved from a traditional appliance manufacturer into a platform of micro-enterprises. Each business unit within Haier operates like a startup — incentivized to serve customers directly, with shared services in the background. The result: agility, innovation, and resilience.
• Unilever in emerging markets uses a reverse logistics model for its “Shakti” initiative in India — empowering rural women as micro-entrepreneurs who sell hygiene products locally and collect packaging for reuse.
• Tesla’s model integrates software, hardware, and energy services — combining direct-to-consumer sales, over-the-air updates, energy storage, and AI-based autonomous driving. Its value is no longer just in vehicles but in data, brand, and energy platforms.
• Shopify enabled a new kind of distributed entrepreneurship — with tools, templates, and infrastructure that allowed anyone to become an online retailer. Its model grows by helping others grow.

How to build a new business model

Creating a new business model starts with rethinking the assumptions of your current one. Key questions include:

• Who is our customer — and what job are they hiring us to do?

• What unique value can we offer — and how can we deliver it differently?

• What relationships, data, or brand assets can we leverage?

• How can technology reshape the cost or experience of delivery?

• Where is the money coming from — and is that the only way?

One powerful tool is the Business Model Canvas — a simple framework that breaks a business into nine components: customer segments, value propositions, channels, customer relationships, revenue streams, key activities, key resources, key partners, and cost structure.

To innovate, test different combinations:

• Could we shift from selling to subscription?

• Could we serve new customer segments through platforms?

• Could we turn data into a new product or insight engine?

• Could we create new value by collaborating with unlikely partners?

Transitioning from old to new models

Transitioning to a new business model is one of the hardest — and most critical — leadership challenges. It means letting go of legacy assumptions, revenue streams, and ways of working. The shift must often be staged and carefully managed.

Here are key steps:

1. Start small: Pilot the new model in one segment, geography, or customer base.

2. Learn fast: Measure what works, adapt quickly, and scale only what proves value.

3. Align incentives: Ensure internal teams are rewarded for embracing new models, not protecting old ones.

4. Communicate clearly: Customers, investors, and employees need to understand why the change matters.

5. Keep both engines running: During transition, companies may need to balance the legacy model (“Engine 1”) and the new model (“Engine 2”) — as explained in O’Reilly and Tushman’s ambidextrous organization framework.

Jump to the future

We now see even more radical models emerge — powered by AI, blockchain, sustainability pressures, and new social expectations. Business models will become more fluid, adaptive, and ecosystem-based. Value will increasingly flow from intangible assets like trust, brand, relationships, and data.

The ability to design, test, and evolve business models will be the most important skill of future-ready leaders. Because in a world of change, your business model — not just your product — will decide whether you win or vanish.

Business model innovation is no longer a luxury. It’s a necessity. Whether you’re a startup or a century-old corporation, your future depends on your ability to imagine new ways to create and capture value — and to let go of the past to embrace what comes next.

When technologist Luis von Ahn was building the popular language-learning platform Duolingo, he confronted a problem that reached far beyond software engineering. The challenge was not only how to teach millions of people to speak another language, but how to make them want to. How could an app designed for education compete with the attention-grabbing allure of Instagram or TikTok? How could learning itself become something people craved, rather than a duty they postponed?

Von Ahn, a Guatemalan computer scientist who had previously sold two companies to Google, understood the psychology of digital behaviour as much as he understood algorithms. He knew that to teach at scale, Duolingo had to feel less like school and more like a game — less like homework and more like a hit of dopamine. He wanted to make the learning experience so addictive that users would return to it as instinctively as they reached for social media.

The result was a revolution in the way people learn languages — and a profound case study in how education itself could be reinvented.

The psychology of learning meets the mechanics of play

Duolingo’s interface is deceptively simple: short lessons, friendly cartoons, bright colours, and the little green owl who celebrates your progress or scolds your neglect. Beneath this simplicity lies a sophisticated use of behavioural science. The app employs gamification — the use of game-like rewards and structures to motivate behaviour — with precision. Users earn points, climb leaderboards, and maintain “streaks” for consecutive days of study. They receive instant feedback for right and wrong answers. Progress is visible, tangible, measurable.

Von Ahn’s insight was that humans, regardless of age or culture, are wired to seek progress, status, and affirmation. He borrowed the mechanics of mobile gaming and social media — streaks, badges, notifications, rankings — and repurposed them for a nobler cause: learning. The psychological hooks that make Instagram endlessly scrollable or Candy Crush habit-forming became the same hooks that kept people returning to conjugate Spanish verbs or master Japanese kanji.

But Duolingo’s deeper innovation lies not just in gamification. It lies in democratisation. Von Ahn grew up in Guatemala, where access to high-quality education was limited to a privileged few. He wanted to build a platform that made learning free, fun, and universal. By using artificial intelligence to personalise lessons, by harnessing cloud computing to deliver it at scale, and by designing for mobile-first access, Duolingo broke open the gates of education for hundreds of millions of learners.

Today, over 600 million people use Duolingo. It teaches 40 languages, from English and Spanish to Swahili and Navajo. It is as likely to be used by a refugee learning a new country’s language as by an executive preparing for a global posting. And its impact goes beyond language: Duolingo has proven that learning can be delightful — that when designed right, it can be something we choose to do, not something we have to do.

What Duolingo tells us about the future of learning

The success of Duolingo poses a radical question: if education can be made this engaging, why isn’t all learning like this? Why do so many classrooms, lecture halls, and corporate training programmes still feel joyless, disconnected, and outdated?

Learning, as a human act, has barely changed in centuries. The dominant model — a teacher at the front, students in rows, content delivered in linear chunks — dates back to the industrial age. It was designed to produce compliant workers for predictable jobs. But the world has changed. Information is no longer scarce. Skills expire fast. Technology evolves faster. And the capacity to learn — to adapt, unlearn, and reinvent oneself — has become the most valuable skill of all.

If we are to keep up with this world, learning itself must be reinvented: made more immersive, more personal, more continuous, more creative, and more human.

Learning as experience, not instruction

The most powerful shift underway is from instruction to experience. Traditional education delivers content — lectures, textbooks, PowerPoints — as if learning were the passive absorption of facts. But research in cognitive science, from thinkers such as John Dewey and Jean Piaget to modern neuroscientists, shows that people learn best by doing, experimenting, and reflecting. Learning is not a transfer of information; it is the construction of meaning.

This idea is now being realised through technology in extraordinary ways. Virtual and augmented reality are allowing learners to step inside complex systems and stories. For example, Labster, a Danish company, creates virtual science laboratories where students can perform chemistry experiments without chemicals or risk. Immerse and ENGAGE XR offer virtual classrooms where learners interact as avatars, conducting debates or exploring 3D models. Medical students train on digital cadavers. Engineers learn by manipulating simulated machinery. History students walk through ancient cities reconstructed in VR.

These experiences are not just novel — they are more effective. The combination of visual, spatial, and emotional engagement creates stronger memory and deeper understanding. It turns learning from a cognitive act into a sensory one.

Learning becomes personal

Technology also enables a second revolution: personalisation. Every learner is different — in pace, style, motivation, and prior knowledge — yet most education still treats learners as identical. Adaptive learning platforms, powered by artificial intelligence, are changing this.

AI can now analyse how each individual learns, what mistakes they make, where they hesitate, and what excites them. It can adjust difficulty, sequence, and content in real time. Platforms like Knewton, Squirrel AI, and Century Tech are pioneering such adaptive models in schools, while corporate learning systems like Degreed, Coursera for Business, and LinkedIn Learning personalise pathways for professionals.

Duolingo itself uses machine learning to tailor lessons, ensuring that each learner stays in the sweet spot between challenge and mastery — hard enough to be interesting, easy enough to be achievable.

The result is a shift from standardisation to individualisation, from education as a conveyor belt to education as a compass. Learning becomes a lifelong conversation between the learner and the system, continuously refined by data and feedback.

Learning through play, purpose and community

But technology alone cannot make learning meaningful. Engagement requires emotion — curiosity, play, purpose, and belonging. The most successful learning experiences tap into these deeper drivers.

Gamified platforms like Duolingo and Kahoot! use play to trigger intrinsic motivation. Minecraft: Education Edition allows children to learn coding, architecture, and ecology by building virtual worlds. The LEGO Foundation promotes “learning through play” as a philosophy for all ages, including adults rediscovering creativity and collaboration.

Purpose adds another layer. When people learn in pursuit of a cause, not just a grade or promotion, they absorb knowledge more deeply. Programmes like Teach For All, One Young World, and Ashoka Fellows blend education with social impact, turning learning into action. The rise of sustainability-oriented business schools and ESG-focused executive programmes shows how purpose can re-energise professional learning.

Community is the glue that sustains it all. Humans are social learners. We learn best in groups, through dialogue, storytelling, and feedback. Online communities — from Reddit’s r/learnprogramming to MasterClass forums and peer networks on FutureLearn — have recreated the seminar in digital form. Meanwhile, in physical spaces, new schools and universities are designing campuses for collaboration rather than lectures.

Reinventing learning for children

The reinvention of learning starts with how we educate the young. Across the world, innovative schools are breaking free from the factory model of education, creating environments that nurture creativity, resilience, and agency.

Finland remains a global reference point. Its schools emphasise trust, autonomy, and curiosity over tests and homework. Teachers are highly trained and given freedom to design lessons. Students learn through projects that connect disciplines to real life — combining maths, art, and social studies around themes like climate change or sustainable cities.

In the Netherlands, Agora School allows students to design their own curriculum entirely, guided by coaches rather than teachers. There are no subjects, grades, or classrooms — only projects that align with each child’s interests. The result is extraordinary engagement: children take ownership of learning rather than compliance.

Elsewhere, schools like Green School in Bali and United World Colleges around the globe blend academic rigour with environmental and cultural immersion. Learning happens in bamboo classrooms, in forests, in communities. The emphasis is on empathy, sustainability, and global citizenship — the competencies the 21st century needs most.

These examples suggest that the future of education lies not in memorising what machines can already do, but in cultivating what makes humans unique: creativity, compassion, curiosity, critical thinking, and collaboration.

Universities in transition

Higher education, once the pinnacle of intellectual formation, is also under pressure to reinvent. Rising costs, shifting student expectations, and the digitisation of content are eroding the old model of the ivory tower. The pandemic accelerated the move to hybrid and online learning, revealing both the possibilities and the shortcomings of virtual education.

Leading universities are responding by blending digital access with experiential immersion. Minerva University, based in San Francisco but operating globally, has replaced the physical campus with a global network. Students live in different cities each semester — Berlin, Seoul, Buenos Aires — and attend live seminars online through an interactive platform designed for deep discussion. The focus is on critical thinking, interdisciplinary problem-solving, and cultural adaptability.

Other institutions are embracing micro-credentials and modular degrees. MIT’s MicroMasters, Harvard’s online certificates, and FutureLearn’s short courses allow learners to build flexible, stackable qualifications that evolve with their careers. Learning no longer needs to happen once, between 18 and 22; it can unfold continuously, anywhere, anytime.

Universities are also partnering with industry to close the gap between theory and practice. The rise of applied research labs, innovation studios, and entrepreneurship centres transforms campuses into ecosystems where students learn by creating, testing, and launching ideas.

Reinventing corporate and executive learning

If schools and universities are changing slowly, corporate learning is moving at breakneck speed. Businesses have realised that in an era of disruption, their greatest asset is not what they know, but how fast they can learn.

The traditional model of executive education — a week at a business school with case studies and networking dinners — now feels inadequate. In its place, a wave of new learning experiences is emerging that emphasise agility, experimentation, and future-readiness.

Programmes such as Singularity University in Silicon Valley immerse leaders in exponential technologies — AI, robotics, blockchain, synthetic biology — while challenging them to tackle global challenges. The d.school at Stanford and Hyper Island in Stockholm teach creative problem-solving through design thinking, rapid prototyping, and reflection.

Meanwhile, platforms like Coursera, edX, and Udemy are democratising access to world-class business education. Anyone, anywhere, can now learn from professors at Yale or practitioners at Google. The boundaries between formal and informal, physical and digital, education and entertainment, are dissolving.

Corporate learning is also becoming social and experiential. Companies like Unilever, Microsoft, and DBS Bank have replaced top-down training with internal “learning ecosystems” — networks of mentors, digital resources, and collaborative projects. Learning happens in the flow of work, through peer coaching and real-world challenges.

The most forward-looking organisations treat learning as culture, not curriculum. They reward curiosity, encourage experimentation, and view failure as feedback. They understand that in a volatile world, the organisation that learns fastest wins.

The neuroscience of engagement

Why do some learning experiences stick while others fade? Neuroscience is beginning to provide answers. Learning that triggers emotional engagement, novelty, and reward activates dopamine pathways in the brain, strengthening memory and motivation. In contrast, rote learning and passive listening fail to engage these circuits.

Duolingo’s success with streaks and rewards reflects this principle — it stimulates the same pleasure pathways as social media, but towards a positive end. Similarly, immersive simulations and storytelling activate multiple areas of the brain, making information more likely to be retained.

Understanding these mechanisms allows educators to design learning that works with the brain rather than against it. The future of pedagogy lies at the intersection of psychology, design, and data — in creating experiences that align cognitive science with human curiosity.

Learning as a lifelong pursuit

The old idea of education as a stage that ends with a diploma is collapsing. In a world where industries transform within a decade, lifelong learning is no longer optional. Workers must continuously reskill and reinvent themselves.

Governments and companies are responding. Singapore’s SkillsFuture initiative provides every citizen with lifelong learning credits to spend on courses. The European Union’s Upskilling Pathways programme encourages member states to provide personalised learning opportunities for adults.

Digital platforms are filling the space between education and employment. Google Career Certificates, IBM SkillsBuild, and LinkedIn Learning offer short, targeted programmes aligned with labour market needs. The barrier between learning and earning is dissolving.

But beyond employability, lifelong learning is becoming part of identity. It reflects a mindset of curiosity and adaptability. As the philosopher Alvin Toffler wrote, “The illiterate of the 21st century will not be those who cannot read and write, but those who cannot learn, unlearn, and relearn.”

It begins with curiosity and meaning

For all the power of technology, the essence of learning remains profoundly human. It begins with curiosity — the desire to know — and culminates in meaning — the ability to connect knowledge to life.

No algorithm can replace the spark of a great teacher, the insight of a mentor, or the inspiration of shared discovery. The danger of digital learning is that it can become efficient but soulless, reducing education to content delivery. The opportunity is to use technology to amplify humanity, not replace it — to free teachers from routine tasks so they can focus on dialogue, creativity, and empathy.

Reinventing learning, therefore, is not about gadgets or apps; it is about reimagining the relationship between humans and knowledge. Technology provides the tools, psychology provides the understanding, but imagination provides the purpose.

Building a positive culture of learning

What Duolingo has demonstrated at massive scale is that learning can be joyful, social, and self-propelling. The next step is to infuse that spirit across society — into schools, workplaces, and communities.

Imagine a world where learning is as ubiquitous and as habit-forming as social media. Where every person has a personalised learning companion powered by AI, curating pathways based on passions and goals. Where education systems reward curiosity over conformity. Where businesses measure success not by output but by growth in collective capability.

This culture of learning would transform economies and societies alike. It would narrow inequality by making opportunity accessible. It would accelerate innovation by multiplying minds able to think differently. It would humanise technology by aligning it with aspiration.

Reinventing learning … from Duolingo to the world

Luis von Ahn once said that Duolingo’s mission was not to teach languages but to make learning accessible to all. The deeper lesson of his story is that learning itself can be reinvented — by combining the psychology of motivation with the ethics of inclusion and the possibilities of technology.

From a small app on a smartphone to the reinvention of global education, the principles remain the same: make it personal, make it playful, make it purposeful, and make it possible for everyone.

If the 20th century was the age of schooling, the 21st will be the age of learning — continuous, connected, and creative. The tools are in our hands. The curiosity is in our nature. All that remains is to design systems that unleash it.

As Duolingo’s little owl might remind us, the future belongs to those who keep learning — one small lesson, one daily streak, one joyful discovery at a time.

• Inspiring workshops and development programs

The climate crisis has long been framed as a story of restraint — of cutting back, consuming less, flying less, wanting less. For decades the narrative has been one of limits, sacrifice, and slow adaptation. Yet a new generation of thinkers and innovators is turning that story on its head. What if the solution is not to shrink our world, but to redesign it? What if the answer to a warming planet is not paralysis, but possibility?

Around the world, engineers, entrepreneurs, and ecologists are no longer asking how to avoid disaster but how to cool the planet. Their thinking is bolder, their timelines shorter, and their tools more ambitious. They are drawing from nature’s own playbook — regeneration, restoration, and feedback — and combining it with the power of exponential technologies, circular economies, and creative human cooperation.

The Shift from Reduction to Regeneration

Paul Hawken’s Regeneration: Ending the Climate Crisis in One Generation has become a touchstone for this new mindset. Rather than framing climate action as damage limitation, Hawken invites us to see it as a design challenge — to restore the living systems that sustain life. His central insight is both scientific and spiritual: carbon is not the enemy, but the element of connection, cycling endlessly through plants, oceans, and soil. When we burn it, we break that cycle. When we restore it, we rebuild balance.

Hawken’s work has inspired a wave of regenerative thinking that transcends traditional environmentalism. Instead of merely “sustainability” — maintaining what we have — regeneration seeks to make the world better, richer, and more resilient. It’s a shift from doing less harm to doing more good; from neutrality to positive impact.

Across sectors, this regenerative logic is now shaping strategy and innovation. From companies reimagining materials and food systems, to cities investing in biodiversity and resilience, the emphasis is on circular, restorative growth — a new economy that works with nature rather than against it.

Cooling at Speed and Scale

If regeneration is the philosophy, then cooling the planet is its practical expression. Scientists and entrepreneurs are exploring interventions that actively lower global temperatures — not in centuries, but in decades.

Some of these efforts are strikingly direct. Carbon capture and storage, once a fringe idea, is now moving into the mainstream. In Iceland, Climeworks operates the world’s largest direct air capture plant, using geothermal energy to pull CO₂ from the air and mineralise it underground. In Canada, Carbon Engineering is building facilities capable of extracting a million tonnes of CO₂ per year.

Others are taking inspiration from the Earth’s own systems. Enhanced weathering projects, for example, accelerate natural rock processes that absorb carbon. In Kenya and Scotland, researchers are spreading basalt dust on farmland, turning agricultural soils into massive carbon sinks. Forest restoration, mangrove replanting, and seagrass regeneration — all old ideas — are being turbocharged with AI mapping, drone reforestation, and data-driven ecosystem management.

Then there are the moonshots: approaches once considered unthinkable. Stratospheric aerosol injection — mimicking volcanic eruptions to reflect sunlight — is back under serious study, as are marine cloud brightening projects off the coasts of Australia and California. These “solar reflection” techniques remain controversial, but the urgency of climate feedback loops has rekindled debate about whether we can afford not to explore them.

Nature as Technology

Perhaps the most profound innovation is rediscovering that nature itself is the most sophisticated technology we know. Photosynthesis, microbial metabolism, ocean currents — these are the planet’s original carbon management systems. Modern science is learning to harness and amplify them.

In Finland, a startup called Solar Foods produces protein from hydrogen and CO₂ using microbes — a process that turns air into food with minimal land or water use. In the Netherlands, researchers are engineering biochar systems that convert agricultural waste into stable carbon, improving soil health while locking carbon underground for centuries. In the United States, companies like Living Carbon are developing genetically enhanced trees that capture carbon faster than their wild counterparts.

These solutions share a radical optimism: that human ingenuity, guided by ecological intelligence, can not only stop the damage but reverse it.

Cities That Heal

Urban areas — responsible for 70% of global emissions — are becoming laboratories for planetary healing. Singapore is weaving greenery into its skyline with vertical forests and cooling corridors that lower city temperatures. Copenhagen aims to be the world’s first carbon-neutral capital, powered by renewable energy and circular waste systems. Paris has pledged to become a “15-minute city,” reducing car dependence while increasing local vibrancy.

London, too, is experimenting with a regenerative urban future. New heat networks, powered by underground and waste energy, now provide low-carbon warmth to thousands of homes. The city’s “superloop” of electric buses and expanding cycling infrastructure signal a broader cultural shift — from linear consumption to living systems design.

But cities are not only sites of emission; they are also centres of coordination. Urban innovation scales quickly, combining public policy, citizen behaviour, and technology deployment. If the industrial revolution began in cities, the regeneration revolution may well do the same.

A Revolution in Food and Farming

Few sectors illustrate the potential of regenerative design more vividly than agriculture. Conventional farming, dependent on synthetic fertilisers and monocultures, degrades soil and releases vast amounts of carbon. Regenerative agriculture, by contrast, treats the farm as a living ecosystem — integrating cover crops, composting, rotational grazing, and biodiversity to restore soil carbon and fertility.

Across Africa, Asia, and Latin America, smallholders are reviving indigenous techniques that store carbon while improving yields. In the American Midwest, large-scale farmers are adopting no-till methods and planting “carbon-smart” crops supported by data-driven platforms such as Indigo Ag.

Meanwhile, the future of protein is being reimagined. Precision fermentation, cellular agriculture, and mycelium-based foods are scaling fast. These technologies promise to cut land and water use while offering new markets for sustainable growth. Companies like Meati in the US and Solar Foods in Europe are showing that innovation and nature need not be opposites — they can be allies in regeneration.

Rethinking Capitalism Itself

But regeneration is not only technological. It is economic, moral, and cultural. The deeper question is: what kind of economy can sustain life, rather than deplete it?

The regenerative model challenges the very foundations of extractive capitalism. It asks companies not how to offset their impact, but how to embed their value creation in systems that restore. That means redesigning business models around circular flows, long-term stewardship, and ecological accounting.

Pioneers like Patagonia, Interface, and Unilever have already shown what this looks like in practice. Interface’s “Factory as a Forest” initiative aims to make each production site a net-positive ecosystem — generating more clean air, water, and biodiversity than it consumes. Unilever’s “Regenerative Agriculture Principles” now extend across its supply chains, connecting livelihoods and land restoration.

Financial systems, too, are beginning to adjust. Regenerative finance (ReFi) is emerging as a movement to align capital with planetary health. Tokenised carbon credits, nature-backed currencies, and biodiversity-linked bonds are early experiments in this new field. The aim: to make the health of ecosystems not an externality, but the core metric of economic value.

The Acceleration Imperative

Speed matters. Every year of delay compounds the challenge. The good news is that exponential technologies can compress timelines dramatically. AI-driven climate modelling now allows researchers to test thousands of interventions virtually before field trials begin. Advanced materials — from carbon-storing concrete to biodegradable plastics — are moving from lab to market at record pace.

Even public policy is learning to accelerate. The European Green Deal, the Inflation Reduction Act in the US, and China’s vast investment in clean technologies all signal a new industrial race — one defined not by fossil fuels, but by the energy transition. Nations are competing not only to decarbonise, but to lead in the industries of the future: batteries, hydrogen, fusion, and synthetic biology.

A Cultural Shift

Ultimately, the climate challenge is as much about imagination as engineering. For decades, we have been told that human activity inevitably harms the planet. Regeneration reframes that relationship: human systems can heal the planet when aligned with natural ones.

This demands a cultural transformation — from extractive to generative, from scarcity to possibility. Artists, educators, and storytellers play a crucial role in this shift. When people can see a hopeful future, they are more likely to build it.

Movements like “Planetary Health” and “Earth System Governance” are beginning to reshape disciplines, connecting climate to health, equity, and security. The younger generation — from climate scientists to startup founders — sees regeneration not as an ideology, but as an organising principle for civilisation itself.

From Despair to Design

The task ahead is immense, but not impossible. Every degree of warming avoided matters; every system redesigned adds resilience. The same ingenuity that built industrial civilisation can now be turned toward ecological repair.

The challenge is to move faster and think bolder — to treat climate not as a burden, but as a frontier for innovation. Whether through nature-based restoration, advanced carbon removal, or regenerative business, the path forward lies in imagination backed by action.

As Paul Hawken writes, regeneration is “the story of life continuing to create conditions for life.” It is not a distant dream but a practical blueprint. What began as a crisis of limits is becoming a movement of creation.

If we act decisively, the 21st century could be remembered not as the age of decline, but as the moment humanity learned to make the Earth thrive again. Cooling the planet, it turns out, may begin with warming the human spirit — to believe, once more, in our collective power to regenerate the world we share.

Technology is no longer a background enabler of business strategy; it is core to the strategy. Each year, the World Economic Forum identifies the most promising breakthroughs set to reshape markets, industries, and society. The Top 10 Emerging Technologies of 2025 is more than a list of inventions—it’s a roadmap to where value will be created, disrupted, and redefined.

For business leaders, the implications are immediate. These technologies—from AI that reasons like a human to sustainable materials that unlock circular economies—are not distant possibilities. They are investment priorities, talent magnets, and innovation accelerators already moving from lab to market. They will change customer expectations, supply chains, and competitive dynamics.

Understanding these shifts is essential for building resilience and seizing opportunity. The leaders who engage early—experimenting, partnering, and scaling—will not only navigate disruption but set the pace of progress in their industries.

Here are 10 emerging technologies that have the potential to reshape industries, redefine healthcare, and accelerate the transition to a more sustainable and intelligent world.

• Structural Battery Composites – Batteries integrated into the structure of vehicles or aircraft.
• Osmotic Power (Blue Energy) – Harvesting clean energy from the salt gradient between seawater and freshwater.
• Advanced Nuclear Technologies – Safer, simpler, and more cost-effective reactors.
• Engineered Living Therapeutics – Microbes programmed to produce drugs inside the body.
• GLP-1s for Neurodegenerative Disease – Repurposing weight loss drugs to tackle Alzheimer’s and Parkinson’s.
• Autonomous Biochemical Sensors – Real-time monitoring of health markers.
• Green Nitrogen Fixation – Sustainable ammonia production for fertilizers.
• Nanozymes – Synthetic nanomaterials mimicking enzymes for healthcare and industry.
• Collaborative Sensing – Networks of distributed sensors powered by AI.
• Generative Watermarking – Tracing the origins of AI content for trust and transparency.

Deep dives into each tech

Structural Battery Composites (SBCs)

What they are. Structural battery composites integrate the functions of a rigid, load-bearing material and a rechargeable battery in the same component. Instead of packing heavy cells inside a passive casing, the “case” itself becomes the battery—e.g., portions of an EV’s body, a drone’s wing spar, or even building panels doubling as energy storage.

Why it matters. Weight and volume are the enemies of electrification. SBCs promise large system-level gains: lighter vehicles (longer range with the same pack or same range with smaller packs), simplified architectures, fewer parts, and potentially lower costs and lifecycle emissions. In aerospace, where every kilogram counts, embedding storage into primary structures could unlock longer endurance for e-aviation and UAVs. In the built environment, SBCs hint at walls and facades that store and smooth on-site renewable electricity.

How it works. SBCs typically combine carbon-fiber reinforcement (mechanical strength) with solid-state or polymer electrolytes and engineered interfaces that can carry both ionic and structural loads. The technical challenge is balancing electrochemical performance (capacity, cycle life, safety) with mechanical properties (stiffness, toughness, crash behavior) in a single laminate or sandwich structure.

Trajectory and hurdles. Early prototypes exist, but scaling means qualifying entirely new multifunctional materials for safety-critical use. Key issues include damage tolerance and repairability, thermal management, fire safety, end-of-life recycling, and the need for new standards and test protocols (you’re crash-testing the “battery” as part of the chassis). Supply chains must adapt for co-manufacturing energy and structural layers at high yield. Still, the Forum frames SBCs as an inflection point for materials-energy convergence with cross-sector impact over the coming decade.

Bottom line. If validated at scale, SBCs could rewrite design rules for EVs, aircraft, marine craft, and buildings—collapsing separate subsystems into lightweight, power-storing structures and pushing electrification into domains where today’s batteries struggle.

Collaborative Sensing

What it is. Collaborative sensing links many disparate sensors—cameras, LiDAR, smartphones, vehicles, traffic lights, weather stations—into a network that fuses data in real time. AI sits atop this mesh to extract context and coordinate actions across domains such as mobility, emergency response, and environmental monitoring.

Why it matters. A single sensor has limited field-of-view and reliability; thousands working together create resilience, coverage, and richer situational awareness. Think traffic lights that dynamically retime based on live road, air-quality, and transit feeds; cars that “see” around corners using other vehicles’ sensors; mine sites and ports that coordinate machinery more safely; cities that detect floods or wildfire smoke early and route resources accordingly.

Enablers and challenges. Advances in edge computing, low-latency networks, and multimodal AI enable on-the-fly sensor fusion. The hard parts are governance and trust: privacy, security, data ownership, consent, and bias in models that make operational decisions. Powering massive sensor fleets, creating interoperable standards, and ensuring cyber-resilience are also essential. The WEF emphasizes that trust and safety frameworks must grow alongside deployments.

Outlook. As infrastructure digitizes, collaborative sensing becomes a backbone for smart cities and autonomy. Expect early value in controlled environments (industrial sites, campuses) and progressive rollouts in transport and public safety—where benefits can be measured in minutes saved and lives protected.

Green Nitrogen Fixation

What it is. Ammonia is indispensable for fertilizer, underpinning roughly half of global food production. Today it’s made mainly via Haber-Bosch, a high-temperature, high-pressure process fueled by fossil hydrogen—responsible for about 2% of global energy use and significant CO₂ emissions. “Green” nitrogen fixation swaps in low-carbon pathways: electrolytic or photochemical routes, bio-engineered microbes and enzymes, or hybrid systems that leverage renewable electricity.

Why it matters. Decarbonizing ammonia tackles a major industrial emitter while making food systems less exposed to gas price shocks. It also enables on-site or distributed production near farms, potentially reducing transport emissions and improving access in emerging markets.

State of play. The report notes momentum from lab to pilot scale across electrochemical nitrogen reduction, plasma catalysis, photocatalysis, and biocatalytic approaches, though achieving energy efficiency, selectivity (suppressing hydrogen evolution), and durability at scale remains tough. Systems engineering—coupling intermittent renewables to continuous production, storage, and safety—will determine competitiveness against incumbent Haber-Bosch.

Risks and policy. Certification of “green ammonia,” clear carbon accounting, and incentives (e.g., for green H₂) can accelerate adoption. Bio-based routes raise biosafety and containment questions; any distributed production must meet stringent safety standards given ammonia’s hazards.

Outlook. With fertilizer demand steady and shipping eyeing ammonia as a zero-carbon fuel, green fixation could influence both agriculture and maritime decarbonization if cost and performance targets are met.

Nanozymes

What they are. Nanozymes are engineered nanomaterials that mimic natural enzymes’ catalytic activity while often being more stable, cheaper, and easier to manufacture at scale. They can catalyze redox reactions, peroxidase-like activity, and more—opening use in biosensing, diagnostics, environmental remediation, and targeted therapies.

Why it matters. Natural enzymes are powerful but fragile (temperature, pH, proteolysis) and costly to produce. Nanozymes tolerate harsher conditions, can be tailored for activity and targeting, and integrate with electronics for readouts. Potential wins: faster, rugged point-of-care tests; catalytic filters that break down pollutants; oncology or neurodegeneration interventions where nanozymes activate drugs or scavenge reactive species.

Evidence and momentum. The WEF synthesis highlights accelerating research and early commercialization, including companies pursuing nanozyme-enabled diagnostics and therapeutics. Market forecasts anticipate rapid growth as materials and selectivity improve, though clinical use will demand rigorous safety and biodistribution data, plus regulatory clarity for nanomedicine.

Caveats. Key challenges are specificity (avoiding off-target reactions), biocompatibility and clearance, and standardized assays to compare catalytic performance with native enzymes. For environmental uses, lifecycle and ecotoxicity assessments are essential.

Outlook. By combining catalysis, materials science, and device integration, nanozymes could become a general-purpose tool for robust sensing and intervention in messy, real-world settings where proteins struggle.

Engineered Living Therapeutics

What they are. “Living medicines” use engineered microbes or cells that reside in the body and manufacture therapeutic molecules on demand—think programmable probiotics that sense inflammation and release anti-inflammatory factors, or bacteria that convert toxic metabolites into harmless products.

Why it matters. Conventional drugs are static; living systems can adapt, persist, and target niches (gut, skin, tumor microenvironments). That raises the prospect of long-acting, responsive therapies for chronic disease, metabolic disorders, infections, and even cancer, potentially with lower costs and improved adherence.

State of play. Synthetic biology, chassis optimization, and AI-assisted design are converging to improve safety circuits (kill switches, auxotrophy), delivery, and manufacturability. Early trials and regulated probiotics offer learnings, but regulatory pathways must evolve to assess genetically modified organisms living inside patients. Post-market monitoring, horizontal gene transfer risks, and environmental containment for excreted organisms are active considerations.

Outlook. The Forum frames engineered living therapeutics as a meaningful step toward adaptive medicine—if safety engineering and governance keep pace with ingenuity. Expect initial approvals in tightly controlled indications and delivery sites, then expansion as toolkits mature.

GLP-1s for Neurodegenerative Disease

What this means. GLP-1 receptor agonists (GLP-1 RAs)—best known for type 2 diabetes and obesity—are being investigated for Alzheimer’s and Parkinson’s. Mechanistically, they cross the blood-brain barrier and may reduce neuroinflammation, improve insulin signaling, enhance cellular energy management, and support clearance of toxic proteins.

Why it matters. Neurodegenerative diseases impose huge human and economic burdens, with limited disease-modifying options. If GLP-1s slow progression, even modest effects could extend independent living and reduce care costs. The report notes mixed early clinical results but enough signals to justify larger, rigorous trials now under way. Affordability and supply constraints remain salient.

Risks and realities. Translating metabolic benefits to neuroprotection is non-trivial; dosing, duration, and patient selection matter. Frailty and unintended weight loss in older patients require careful oversight. Policymakers may need new reimbursement models if upfront drug costs offset long-term care savings.

Outlook. Repurposing a mature drug class accelerates timelines. If efficacy is proven, GLP-1s could shift neurology from symptom management to disease modification and spur combination regimens with other agents (e.g., GIP co-agonists). W

Autonomous Biochemical Sensing

What it is. Analytical devices that continuously detect and quantify biochemical markers with minimal human intervention—wired for real-time data capture and often self-powered. Beyond glucose monitors, think wearables for inflammatory cytokines, continuous hormone tracking, microbial “whole-cell” biosensors that report pollutants or pathogens, and environmental nodes that surveil soil and water chemistry.

Why it matters. Continuous data can move systems from reactive to preventive: early infection warnings, real-time food safety validation, leak/spill detection before public exposure, and adaptive agriculture. During crises, a distributed biochemical “nervous system” can inform faster, targeted responses.

Hurdles. Sensors must balance sensitivity with longevity in messy environments; fouling and biofilms degrade performance. Engineered microbial sensors raise biosafety and permitting issues. Then there’s data governance: privacy for health signals, secure telemetry, and analytics that avoid false alarms.

Outlook. Expect early traction in industrial and regulated settings where ROI is clear (pharma, food processing, water utilities), followed by consumer health niches. As materials and wireless power advance, biochemical sensing will become a standard layer of digital infrastructure.

Osmotic Power Systems

What they are. Osmotic (salinity-gradient) power harvests energy when fresh and salty water mix, typically across a selective membrane that drives ion flow and electricity generation. Advances in membranes and system design have revived a previously niche concept, with pilot plants exploring coastal and estuarine deployments.

Why it matters. It’s clean, steady (not intermittent like wind/solar), and colocates with abundant coastal water flows. Integrating osmotic systems with desalination or wastewater treatment may share infrastructure and enable resource recovery (e.g., lithium from brines), improving project economics. The report cites research momentum and early investment signals.

Challenges. Membrane cost, durability (fouling, scaling), and energy density are central. Environmental permitting must address impacts on estuarine ecosystems and salinity plumes. Grid integration and hybridization with other renewables can improve capacity factors but add complexity.

Outlook. If new membranes and modular designs hit cost targets, osmotic power could complement baseload-seeking grids and provide resilient coastal microgrids—especially valuable as electrification and water stress rise.

Advanced Nuclear Technologies

What they are. A new wave of nuclear systems—such as small modular reactors (SMRs), alternative coolants, advanced fuels, and passive safety designs—aims to deliver firm, low-carbon power with improved safety, cost, and siting flexibility. These can serve grids, industrial heat, or hydrogen production.

Why it matters. Electrification (EVs, heat pumps, AI data centers) is driving demand for reliable clean power. Advanced nuclear offers high capacity factors with small land footprints and potential load-following. Modularization and factory fabrication promise better cost control than bespoke gigawatt plants.

Issues to solve. Licensing pathways, financing models, spent-fuel strategies, and public acceptance remain pivotal. Supply chains for advanced fuels (e.g., HALEU) and skilled labor must scale. Integration with district heat, desalination, or industrial processes can boost value but requires tailored regulation.

Outlook. The Forum highlights advanced nuclear as a repurposing of established tech for new demands—poised to help decarbonize grids if projects demonstrate schedule and budget discipline. Early deployments at industrial sites and remote locations are likely beachheads.

Generative Watermarking

What it is. Invisible (or machine-readable) markers embedded in AI-generated content—images, audio, video, and potentially text—to signal provenance and enable authentication at scale. Watermarks may be cryptographic, signal-processing-based, or standardized metadata, designed to persist through common transformations.

Why it matters. As synthetic media proliferates, societies need infrastructure to discern origin and maintain trust—especially during elections, disasters, or markets-moving events. Watermarking complements other provenance approaches (e.g., content credentials) and can help platforms, newsrooms, and courts assess authenticity. The Forum elevates this as a key trust-and-safety technology for the networked world.

Limits and governance. Determined adversaries may attempt removal or spoofing; standards and broad adoption are critical. Watermarks raise questions around privacy, interoperability, open vs. proprietary schemes, and how to treat non-watermarked content. The WEF flags the need for shared norms and technical collaboration to prevent fragmentation and evasion.

Outlook. Expect rapid maturation as major model providers and platforms adopt watermarking and provenance stacks, paired with detection and disclosure policies. It’s not a silver bullet against misinformation, but as part of a layered authenticity ecosystem, it’s a pragmatic step toward healthier information markets.

Themes that stand out

• Convergence of biology and technology: From programmable microbes to wearable health sensors, biotech is becoming deeply integrated into our daily lives.
• Energy reinvention: Clean, efficient power—from blue energy to structural batteries and next-gen nuclear—is reshaping the global energy mix.
• Healthcare reimagined: Therapies are becoming more personalized, real-time, and even self-generating inside the body.
• AI and accountability: As generative AI scales, watermarking and collaborative sensing show that transparency and ethics are rising priorities.
• Sustainability through innovation: Green nitrogen and osmotic energy represent a broader shift toward technologies that work with nature, not against it.

These breakthroughs remind us that technology is not just about speed or scale, it’s about direction. And the direction we choose matters.

We live in a culture obsessed with youth. Silicon Valley entrepreneurs in their twenties are hailed as the ultimate visionaries, Olympic athletes in their thirties are considered veterans, and companies often prize “fresh thinking” as if it is exclusively the province of the young. The unspoken assumption is that mental sharpness, creativity, and problem-solving peak early in life and then decline in an inevitable slide.

But what if that assumption is wrong? What if, in fact, the human mind is designed to reach its peak not in the frantic energy of youth but in the reflective depth of maturity? New research from Dr. Gilles Gignac at the University of Western Australia has quantified what many have sensed: that overall brain performance — when you blend knowledge, judgment, perspective, and emotional balance — does not peak until around 60 years old.

This finding challenges more than just stereotypes. It suggests that the very arc of human development is different than we thought. And it invites a powerful question: if our brain is capable of reaching new heights later in life, how do we train ourselves — mind and body — to ensure we actually get there? And what does it mean for how we live, work, and organise society?

The cult of youth, the virtue of age

Walk into any gym and you’ll find posters of athletes in their twenties, physiques at their physical prime. Open the business pages and you’ll see stories of young disruptors breaking rules and changing industries. The message is everywhere: the best years are early years.

It is true that certain mental functions — particularly those linked to raw processing speed, memory recall, or reaction times — are sharper in youth. Psychologists call this fluid intelligence, and like sprinting ability, it tends to peak earlier.

But the human brain is not built only for speed. Over decades, it accumulates knowledge, builds patterns of recognition, refines judgment, and develops what researchers call crystallized intelligence. This is the wisdom that lets an experienced investor spot market shifts, a seasoned doctor diagnose complex conditions, or a grandparent know just when to step in with the right advice. It’s why Warren Buffett made the bulk of his fortune after fifty. It’s why Nelson Mandela, released from prison at 71, became one of history’s most revered leaders.

I’m not saying all this because I’m 60 (well, I am in my 50s!), but society assumes that it’s all downhill from your 40s. Wrong, there is so much more to give.

Why the brain peaks at 60

So why does peak performance arrive so late? Neuroscience and psychology give us several clues:

• Accumulated Knowledge
  Decades of learning, working, reading, and engaging with the world build a vast library of information. At 60, the brain is a well-stocked archive.
• Pattern Recognition
  Experience wires the brain to recognize patterns more quickly. A chess master in their sixties may not move as fast as a teenager, but their intuition about which move to make is far more accurate.
• Emotional Regulation
  Studies show older adults are generally better at managing stress, emotions, and interpersonal dynamics. They bring calm and perspective where younger people may react impulsively.
• Judgment and Wisdom
  Decisions aren’t made only on facts — they’re shaped by values, trade-offs, and long-term consequences. Older adults draw on decades of judgment.
• Neuroplasticity Continues
  Once thought to stop in youth, we now know the brain continues to rewire itself throughout life. Learning new skills, practicing mindfulness, or exercising can stimulate fresh neural connections even at 70 or beyond.

In short, youth gives us raw horsepower, but age gives us the steering wheel. At 60, the two meet in a unique balance.

Training your brain for its peak

If our best mental years can arrive later, the question becomes: how do we make sure we actually reach them? Just as an athlete trains their body, we can train our brain — and the two, in fact, are inseparable. Here’s how:

1.  Keep Learning, Always

The brain is like a muscle: it grows with use. People who continue to learn languages, study history, explore new technologies, or take up musical instruments maintain cognitive agility far longer. It is no coincidence that some of the most innovative entrepreneurs, like Reid Hoffman (LinkedIn) or Arianna Huffington, are perpetual learners who reinvent themselves midlife.

2.  Exercise the Body to Exercise the Brain

Physical activity is one of the most powerful brain enhancers. Aerobic exercise boosts blood flow, delivers oxygen, and stimulates growth factors that promote neuroplasticity. Walking, running, swimming, or yoga can all keep neural pathways sharp.

3.  Sleep, Rest, Recover

Sleep isn’t downtime — it’s brain training time. Memory consolidates, synapses reset, and creative insights emerge in dreams. Consistent, quality rest is an underrated tool for long-term mental performance.

4.  Mindfulness and Meditation

Mindfulness practice thickens areas of the brain linked to attention and reduces stress hormones that impair memory. Leaders from Steve Jobs to Ray Dalio have credited meditation with sharper judgment.

5.  Social Connection

Loneliness accelerates cognitive decline, while strong relationships stimulate emotional and intellectual engagement. Conversations challenge the brain in ways puzzles cannot. In fact, research shows that regular social interaction is as critical to longevity as not smoking.

6.  Purpose and Curiosity

The most important driver may be purpose. People who believe they still have meaningful work, relationships, or contributions to make continue to stretch their abilities. Think of Jane Goodall, still traveling and advocating for the planet at nearly 90. Purpose keeps the brain alive.

Examples of Genius at 60

History is full of people who demonstrate the late flowering of human potential.

• Leonardo da Vinci – Painted Mona Lisa in his early 60s.

• Claude Monet – Painted the Water Lilies series in his 60s.

• Mark Twain – Wrote The Adventures of Huckleberry Finn in his 60s.

• Laura Ingalls Wilder – Published Little House on the Prairie series in her 60s.

• Frank McCourt – Published Angela’s Ashes at 66.

• Charles Darwin – Published On the Origin of Species at 50, continued groundbreaking work into his 60s.

• Dmitri Mendeleev – Refined the periodic table in his later 50s–60s.

• Benjamin Franklin – Invented bifocals and engaged in diplomacy in his 60s.

• Peter Higgs – Developed the Higgs boson theory in his 60s, recognized with Nobel Prize later.

• Ray Kroc – Built McDonald’s into a global empire in his 50s–60s.

• Colonel Sanders – Franchised KFC at 65.

• Vera Wang – Entered fashion design at 40, but global influence peaked in her 60s.

• Warren Buffett – While active for decades, his most transformational acquisitions (Berkshire Hathaway conglomerate expansion, Coca-Cola investment) occurred in his 60s–70s.

• Charlie Munger – Partnered with Buffett, peak influence in investment strategy well into 60s and 70s.

• George Soros – Quantum Fund major bets and philanthropic strategy peaked in his 60s.

• Walt Disney – Launched Disneyland at 60 (opened 1955 when he was 53, continued innovating into 60s with new projects).

• Amancio Ortega (Zara/Inditex) – Major global expansion of Inditex occurred in his late 50s and 60s.

• Henry Ford – Continued to innovate (Model T, production methods, Ford Foundation) into his 60s.

• John Pemberton (Coca-Cola) – Commercialized Coke, with major business growth post-50s.

• David Rockefeller – Built Rockefeller family banking and philanthropic influence well into his 60s and 70s.

• Bernard Marcus & Arthur Blank (Home Depot) – Launched Home Depot in their 50s; expansion continued aggressively into their 60s.

• Peter Thiel – While an outlier in youth entrepreneurship, his major strategic influence at PayPal, Palantir, and Founders Fund peaked in his 50s–60s.

Closer to home, think of the colleague who becomes the “go-to” problem solver not because they are the fastest, but because they’ve “seen it before” and know what matters. Or the mentor whose one sentence reframes a dilemma you’ve wrestled with for weeks. That is the power of brains that have ripened, not just raced.

What it means for business

If people truly peak later than we thought, businesses need to rethink how they value, deploy, and develop talent.

1.  Rethinking Retirement

Mandatory retirement at 60 or 65 may cut people off just as they reach their prime. Imagine if Warren Buffett had been forced out at 60. Companies may need new models that blend senior talent with emerging leaders.

2.  Multi-Generational Teams

The best organizations will harness both youthful speed and mature wisdom. Young staff may drive experimentation; older colleagues provide context and judgment. Together they are stronger.

3.  Training and Reskilling Across Life

Education shouldn’t stop in our twenties. Businesses that invest in mid-career and late-career learning will unleash new levels of innovation.

4.  Leadership Development

Boards should reconsider the bias toward younger CEOs. Some of the most effective leaders — Satya Nadella at Microsoft, Christine Lagarde at the IMF, Tim Cook at Apple — took the helm later in life.

5.  Designing Work for Cognitive Longevity

Flexible schedules, remote work, and roles that emphasize judgment over speed can help older employees thrive. These aren’t perks; they are performance multipliers.

What it means for Society

Beyond business, the findings have profound social implications.

• Ageism Needs to End
  The idea that older people are less valuable is not only unfair — it’s scientifically wrong. Societies that sideline elders waste their richest human capital.
• Healthcare Priorities
  Investing in cognitive health — from fitness programs to lifelong education — should be a public health priority, not a luxury.
• Politics and Policy
  If peak judgment arrives at 60, perhaps we should not worry that leaders are “too old.” The problem is not age itself but whether they maintain curiosity, energy, and purpose.
• Redefining Success in Life
  The obsession with “achieving everything early” creates unnecessary pressure. If the best is yet to come, then life is a marathon, not a sprint.

Unlocking your brain power

The science is clear: the brain does not burn out early; it matures into brilliance. But like an athlete training for the Olympics, reaching your peak at 60 requires preparation. The choices you make at 30, 40, and 50 determine how strong, resilient, and creative your mind will be when it blossoms later.

The formula is simple but profound: move your body, feed your mind, rest deeply, connect widely, and live with purpose.

Imagine a society where 60 is not seen as the beginning of decline but as the arrival of mastery. Where businesses design careers that crescendo, not taper. Where individuals know that each decade is not a fading echo of youth but a step toward the fullest expression of who they can be.

Brilliant at 60

If you are 25 and anxious about “running out of time,” relax — your best years are still ahead. If you are 45 and wondering if you’ve peaked, remember: you are only halfway to your summit. And if you are 60, welcome — you are entering the golden age of your mind.

The late bloom of brilliance is not an accident of nature; it is the very design of human life. Train your brain, move your body, stay curious, live with purpose — and the best of you will still be to come.

Dove’s Campaign for Real Beauty launched in 2004, challenging beauty stereotypes by featuring “real women” of different shapes, sizes, ages, and ethnicities instead of traditional models. Sparked by research showing only 2% of women considered themselves beautiful, the campaign sought to redefine beauty standards and boost self-esteem. Memorable initiatives included the “Evolution” video (2006), exposing the manipulation of beauty through digital editing, and the “Real Beauty Sketches” (2013), highlighting women’s self-perception versus how others saw them. Over two decades, it has evolved into a movement, sparking global dialogue on inclusivity, authenticity, and body confidence.

20 years of real beauty

To mark 20 years of advocating for Real Beauty, Dove launched a campaign addressing a new threat to authentic representation: the influence of AI-generated imagery. Recognizing that standard AI prompts often produce idealised, unrealistic beauty norms, Dove saw an opportunity to shift how beauty is reflected in digital environments.

Their proprietary prompts, grounded in their longstanding Real Beauty philosophy, led to more inclusive visual outputs—proving the brand’s enduring cultural relevance. Supported by a global study that revealed one in three women feel pressured to change their appearance due to online beauty standards, Dove committed to redefining beauty once again—this time within the algorithms that shape our digital world.

To counter the narrow definitions embedded in AI’s outputs, Dove partnered with Pinterest on an initiative that empowered women to define beauty on their own terms. Users were invited to select characteristics that reflected their vision of beauty. In turn, these preferences populated their Pinterest feeds with diverse, authentic imagery.

This custom experience launched with a high-impact homepage takeover and was reinforced by a strategic paid campaign and robust full-channel rollout. The campaign didn’t just challenge AI’s defaults—it transformed them, ensuring Dove’s Real Beauty message re-emerged at the top of the algorithm. The initiative primarily targeted millennial women aged 25 to 54, strengthening their connection with Dove’s Real Beauty values.

The campaign delivered an impressive 787 million impressions and exceeded all key benchmarks. It achieved a 2.9 percentage point increase in brand association and drove engagement levels that were 21.4% higher than Pinterest’s norm for women. Ultimately, the personalized Pinterest feeds became visual proof of Dove’s continued leadership in shaping how beauty is represented—and celebrated—online.

There’s Nothing Like This: The Strategic Genius of Taylor Swift

Kevin Evers book is a compelling exploration of how one of the world’s biggest pop stars became one of its savviest business leaders. More than a biography, the book offers a strategic playbook—showing how Taylor Swift built, evolved, and protected a global brand with what Evers argues is the foresight and discipline of a top CEO.

He tells the story chronologically, tracing Swift’s evolution from teenage songwriter to cultural icon. He begins with her decision to sign with a small record label over a major one, allowing her greater creative control—a rare move at just 14 years old. This set the tone for a career defined by calculated risks, long-term thinking, and a deep understanding of underserved markets. Her early music catered directly to teenage girls—an overlooked demographic in country music at the time—positioning her as an immediate disruptor.

At the heart of Swift’s strategy is her ability to build and maintain deep, emotional connections with her audience. The book highlights how she transformed the fan-artist relationship through handwritten notes, personal invitations to listening parties, and pioneering use of social media. She wasn’t just promoting songs—she was building community. Evers calls this a model of “fan obsession,” where loyalty and engagement are not byproducts of fame, but drivers of it.

What’s most striking in the book is how Swift consistently turned obstacles into opportunities. Whether it was the fallout from the Kanye West VMAs incident, the backlash around her political silence, or the loss of ownership over her master recordings, she responded not with retreat but with reinvention. Her decision to re-record her entire back catalog to regain ownership wasn’t just a business move—it was a cultural moment, reshaping how artists think about intellectual property and control.

Swift’s artistic reinventions—from country to pop, indie-folk to electro—are framed as strategic expansions into new markets, not just aesthetic choices. And her command of digital platforms, from Tumblr to TikTok, shows her fluency in how attention works in the modern age.

• Teenage country star: At 14, Swift turned down a deal from RCA to sign with Scott Borchetta’s nascent Big Machine Records, advocating to write her own song, targeting an untapped teen-girl demographic. Her debut album spent 24 weeks at number 1, affirming the “Blue Ocean” strategy of serving underserved audiences.

• Fan obsession and connection: Swift would personally hand-write notes, invite fans to intimate listening sessions, and cultivate deep relationships via early social media. This “fan-obsession” helped turn followers into lifelong advocates.

• Resilience and anti-fragility: Post-2009 MTV VMA incident, she doubled down on songwriting authenticity in Speak Now, showcasing her ability to turn setbacks into strengths. The book argues she doesn’t just recover; she grows stronger from adversity.

• Genre and platform reinvention: Strategic shifts: from country to pop (1989), then onto indie-folk (Folklore/Evermore), leveraging disruption as opportunity. Harnessed TikTok and streaming to drive speculation and algorithm-friendly campaigns.

• Ownership and monetisation: Re-recorded her masters—an unscripted, high-stakes strategy that gained her rights control and royalties. Expanded product ecosystem: vinyls, direct deals with AMC, and merch—leveraging her “conglomerate” status.

• Economic powerhouse: the 151-date Eras global tour grossed nearly $2 billion. Each album-era integrated into live experiences, delivering hours of content and underlining brand maturity.

The book devotes significant attention to her financial ecosystem, culminating in the global success of that Eras Tour. Evers portrays the tour not just as a performance spectacle but as a masterclass in product bundling, scarcity, and immersive branding—with impacts stretching into the billions of dollars in economic activity.

Ultimately, There’s Nothing Like This argues that Swift is a blueprint for the modern brand: adaptable, emotionally resonant, fan-powered, and strategically self-aware. Her career is not just an artistic journey but a case study in how to lead, evolve, and endure in a volatile world.

Why do I like this book? This is not just a book for Swifties, it’s essential reading for anyone interested in strategy, branding, or leadership in the 21st century.

Another Way: Building Companies That Last… and Last… and Last

Dave Whorton and Bo Burlingham present a bold alternative to the high-growth, venture-backed startup model that dominates Silicon Valley. Instead of building companies designed to “get big fast” and exit quickly, the authors advocate for the Evergreen approach: building purpose-driven, profitable, and enduring companies that prioritize people over hype, and values over valuations.

At the heart of the book is the belief that business can be both principled and prosperous—and that long-term thinking leads to deeper impact and more resilient success. Drawing on the experiences of dozens of founders who rejected the startup treadmill, Whorton (a former VC himself) and Burlingham (author of Small Giants) identify seven core principles that define Evergreen companies, known as the Seven Ps:

• Purpose – A compelling reason for being that goes beyond making money.

• Perseverance – The grit to stay focused on the long game, not just quarterly results.

• People First – Prioritizing employees, customers, and communities over short-term gains.

• Private – Remaining privately held to avoid the pressures of public markets or outside investors.

• Profit – Using profitability as a discipline and fuel for growth, not an end in itself.

• Paced Growth – Choosing steady, manageable growth over rapid scaling.

• Pragmatic Innovation – Embracing change and technology when it serves the company’s mission and culture—not for its own sake.

Through compelling case studies—ranging from small family-run businesses to mid-sized industry leaders—the book demonstrates how Evergreen companies often outperform flashier competitors in the long run. These businesses tend to have higher employee retention, stronger cultures, deeper customer loyalty, and greater resilience in economic downturns.

The book also tracks Whorton’s own journey from working at Kleiner Perkins to founding the Tugboat Institute, which champions Evergreen businesses. His story reflects the broader theme: that meaningful, values-driven work is not only possible in business—it may be the best way to build something truly lasting.

In an era obsessed with unicorns and IPOs, Another Way is a powerful reminder that enduring value comes from integrity, intention, and investment in people—not from chasing the next big thing. It offers both inspiration and a practical framework for entrepreneurs, leaders, and investors who want to build businesses that endure for generations.

Why do I like this book? Because reinvention, or rather relentless reinvention, is now the big challenge and opportunity for every business in a world of continuous change.

AI First: The Playbook for a Future‑Proof Business and Brand

Adam Brotman and Andy Sack have created a clear, action-oriented guide for business leaders navigating the transformative power of artificial intelligence. Rather than treating AI as just another tool, the authors argue that businesses must reimagine themselves from the ground up—placing AI at the very heart of how they operate, innovate, and grow. Becoming “AI-first” is not about chasing hype; it’s about building a new kind of organization that can thrive in a radically different era.

Drawing on their experience at companies like Starbucks and Forum3, Brotman and Sack lay out a practical framework to help leaders understand what it truly means to be AI-first. The shift begins with mindset: AI isn’t a department or a plug-in—it’s a strategic capability that must be championed from the top. The book emphasizes that CEOs and executive teams must lead this transformation by fostering a culture that’s data-fluent, experimentation-friendly, and deeply aligned around AI’s role in shaping the customer experience and brand identity.

The book advocates for starting small—using pilot projects to demonstrate value quickly and generate internal momentum. But they also stress that this is not just a technology shift; it’s a business and cultural one. Companies must redesign jobs, retrain teams, and rethink how humans and machines work together. AI should not replace people, but elevate their contributions—freeing them to focus on creativity, strategy, and empathy.

One of the strongest messages is about brand: in a world where AI makes everything more personalized and efficient, your brand becomes your greatest differentiator. How you use AI—transparently, ethically, and intelligently—will shape customer trust and loyalty more than ever.

• 95% of marketing to be AI-driven within five years, says Sam Altman

• AI-first leadership mindset is pivotal—begin with executive awareness and advocacy

• Talent and job design must evolve, redefine roles and nurture AI fluency across teams

• Early pilot wins demonstrate practical ROI, critical to gaining buy-in

• Brand differentiation as AI becomes ubiquitous, strategic integration is ke

Ultimately, AI First offers both inspiration and a practical roadmap. It’s for leaders who understand that the future won’t wait—and that preparing for it means rethinking the fundamentals of how their business works, delivers value, and earns attention in an increasingly intelligent world.

Why do I like this book? Because too many books have become tech obsessed about AI. The real insights come from how to apply it to business, in radical, creative and profitable ways.

Building a StoryBrand: Clarify Your Message So Customers Will Listen

Donald Miller offers a powerful marketing guide built around a deceptively simple truth: if customers don’t understand what you offer within the first few seconds, they’ll tune out. To solve this, Miller introduces the StoryBrand Framework, a seven-part storytelling formula that helps businesses clarify their message and make it irresistibly compelling.

At the heart of the book is the idea that the customer is the hero of the story—not the brand. Too many companies position themselves as the star, talking about their history, features, and accomplishments. But great marketing, Miller argues, casts the brand as the guide—the wise mentor who helps the customer overcome challenges and achieve success.

Using the structure of classic storytelling, Miller breaks the framework into seven key elements:

• A character (your customer)

• Has a problem (external, internal, and philosophical)

• And meets a guide (your brand)

• Who gives them a plan (clear steps or solutions)

• And calls them to action (buy now, sign up, etc.)

• That helps them avoid failure (what’s at stake)

• And ends in success (what transformation they’ll achieve)

The book is full of practical examples, website critiques, and brand scripts that make it easy to apply the framework across all types of messaging—websites, sales pitches, ads, social media, and presentations. Whether you’re a startup founder or a marketing director, Miller shows you how to cut through the noise and tell a story your customers will actually care about.

The result is clearer communication, stronger customer engagement, and a more consistent, confident brand voice. Building a StoryBrand isn’t just a marketing book—it’s a strategic toolkit for anyone trying to grow their business by making their message matter.

Why do I like this book? Brands are my first love – I started out 35 years ago as a brand manager – but have become trivialised and marginalised by many business leaders. Yet in a world of intangible assets, they matter more than ever.

Superagency: What Could Possibly Go Right With Our AI Future

Silicon Valley legend and Linkedin founder Reid Hoffman has written a hopeful, deeply reasoned exploration of how artificial intelligence can enhance—not replace—human potential. Rather than focusing on fear or speculation, Hoffman (co-founder of LinkedIn and a long-time AI investor) builds a pragmatic, optimistic case for how AI, if developed and deployed thoughtfully, can amplify human agency and make us more capable of solving the world’s biggest challenges.

The central idea of the book is that AI should not be seen as a threat to humanity, but as a partner—a “thinking companion” that augments our abilities, expands our choices, and helps us navigate complexity. Hoffman calls this enhanced capacity “superagency,” and argues that it represents a new era of empowerment, much like past revolutions in language, printing, and computing.

Hoffman organizes the book around a series of key ideas:

• AI as Amplifier: Like fire, electricity, or the internet, AI doesn’t have values—it takes on the intent of the people using it. That’s why shaping its future starts with us.

• Informational GPS: AI can serve as a guide, helping individuals and institutions make better decisions faster, by mapping possibilities and clarifying consequences.

• Deploy, Then Reflect: Hoffman champions an iterative approach—build AI applications, deploy them responsibly, observe impacts, and refine. Waiting for perfection is too slow; improvement comes through use.

• Human-Centered Design: AI should be built to support human goals—enhancing learning, creativity, entrepreneurship, and empathy. He gives examples like AI tutors, AI coaches, and tools for scientific discovery.

• Guardrails and Governance: While optimistic, Hoffman is clear-eyed about the risks—from misinformation to bias to power concentration. He argues for collaborative governance involving companies, governments, and civil society.

• Private Commons: A call for shared access to powerful models and tools to ensure AI benefits are widespread—not monopolized by the few.

Throughout, Hoffman shares insights from his experience at the frontlines of tech innovation and policy, and makes the case that ethical ambition, not fear, should guide our approach to AI. He warns against paralysis through pessimism, urging readers to engage actively, thoughtfully, and with purpose in shaping the AI era.

In short, Superagency is a manifesto for building a future where human and artificial intelligence work together, not in competition. It’s a refreshing, empowering vision for leaders, technologists, and citizens who want to shape AI not just to do more—but to be more.

The Thinking Machine

This is a compelling biography of Jensen Huang by Stephen Witt, the visionary co-founder and CEO of Nvidia, and a deep dive into how he transformed a struggling graphics chip company into a dominant force powering the modern AI revolution.

Witt chronicles Huang’s journey from his early days as a Taiwanese immigrant with a passion for technology to his breakthrough leadership at Nvidia. The book highlights Huang’s remarkable ability to anticipate and shape future technology trends, especially his foresight in recognizing the potential of graphics processing units (GPUs) beyond gaming—pioneering their use for artificial intelligence and deep learning.

Central to the story is Huang’s relentless focus on innovation, risk-taking, and building a strong company culture that thrives on boldness and agility. Under his leadership, Nvidia not only revolutionized computer graphics but became the backbone of AI infrastructure, powering everything from data centers to self-driving cars.

Witt also explores the technical breakthroughs Nvidia made, such as the development of CUDA, a parallel computing platform that allowed GPUs to be used for general-purpose processing, unlocking new possibilities in AI research and applications.

Beyond the technology, The Thinking Machine portrays Huang as a strategic thinker and charismatic leader who blends engineering expertise with business acumen, inspiring his teams to push boundaries and redefine industries.

In essence, the book is both a portrait of a singular leader and a case study in how vision, innovation, and perseverance can create a company that not only adapts to change but shapes the future itself.

The Optimist

This is a detailed and intimate biography of Sam Altman, one of the most influential figures in the tech world today. Keach Hagey’s book traces Altman’s journey from a precocious young entrepreneur in St. Louis to becoming the CEO of OpenAI, a leading organization at the forefront of artificial intelligence development.

Hagey paints a portrait of Altman as a visionary leader driven by a combination of relentless ambition, intellectual curiosity, and a deep sense of responsibility toward the future of technology and humanity. The book explores Altman’s unique leadership style, characterized by bold decision-making, a willingness to embrace risk, and a rare ability to navigate complex ethical and business challenges.

A central theme is Altman’s optimistic belief in technology’s potential to solve some of the world’s most pressing problems, balanced by his awareness of AI’s risks and the need for careful governance. The biography covers major milestones, including Altman’s time at Y Combinator, his efforts to steer OpenAI toward commercial success while maintaining its mission, and his role in popularizing transformative AI technologies like ChatGPT.

Hagey also delves into the personal side of Altman’s life—his relationships, doubts, and the pressures of leading in an era of rapid technological change. The book provides insights into the challenges of managing a cutting-edge tech company amid public scrutiny, ethical dilemmas, and intense competition.

Ultimately, The Optimist presents Sam Altman as a complex figure whose optimism about technology’s future is tempered by realism, making him a compelling example of modern leadership in a disruptive age.