Reinventing Business with AI … How I’m learning to embrace the best of AI (and other new technologies) to radically reinvent organisations, and accelerate more profitable growth

May 15, 2025

A recent Goldman Sachs survey highlighted the greatest fear of Fortune 500 CEOs … making the wrong decisions about AI.

Where are the biggest opportunities, and threats for my business? How should I embrace it? Who should I turn to for help, and which technologies to go for? What are the essentials, compared to the nice to haves? How can I test it, and mitigate risks? And how do I future proof my investment to ensure that it will stay relevant going forwards?

AI is reasonably seen as a trillion-dollar opportunity, not just for the tech companies creating AI models, but largely for how every kind of business will embrace it, to innovate and reinvent themselves.

Of course we already see AI in our daily lives … from Google Maps to Siri chat, passport face recognition and Netflix recommendations. But it is still a speck compared to its likely size and impact over the next 5-10 years.

Accenture suggests AI could boost global GDP by up to $15.7 trillion by 2035. PwC agrees with that figure, with $6.6 trillion coming from increased productivity, and $9.1 trillion from increased consumption. It suggests China will benefit most, with a 26% GDP boost, compared to North America with a 14.5% GDP boost.

Beyond the tech, beyond the hype

AI is not just another tool in the digital toolbox — it’s a transformative force reshaping how business is imagined, built, and scaled. For forward-thinking leaders, AI offers a once-in-a-generation opportunity to rethink the fundamentals: strategy, business models, products, services, and even leadership itself.

AI is not something to simply delegating to your CTO.

Capturing AI’s full potential requires more than deploying new technologies. It demands a shift in mindset — from efficiency-focused automation to reinvention-focused innovation. Leaders must not only understand AI but see it as a catalyst for bold experimentation. Spend 3-4 hours with ChatGPT asking it – about your future, your industry, your strategy – and you’ll start to appreciate its potential

The AI imperative for strategic reinvention

Traditionally, strategy has been based on periodic analysis, fixed frameworks, and linear planning. AI challenges all of that. With real-time data processing, predictive analytics, and generative capabilities, leaders can now:

  • Forecast demand, risk, and opportunity with greater accuracy

  • Simulate multiple scenarios to guide adaptive strategy

  • Personalize offerings and pricing at scale

  • Accelerate go-to-market testing through rapid prototyping and feedback loops

For example, Shell uses AI and machine learning in its strategic planning to optimize energy trading, predictive maintenance, and even forecast energy transitions. By integrating AI into its core strategy function, Shell is not just becoming more efficient — it’s evolving into a data-intelligent energy ecosystem.

Reinventing business models with AI

AI enables entirely new business models that were previously impossible. Leaders can now reimagine value creation and capture by:

  • Shifting from product-centric to service-centric models

  • Monetizing data and algorithms as assets

  • Using AI-driven platforms to orchestrate multi-sided marketplaces

Spotify has built its model on AI recommendation engines. Founder Daniel Ek understands that AI isn’t just a feature — it’s the foundation. From dynamic playlists to hyper-personalized advertising, AI enables Spotify to create “a unique music service for every user,” moving from content distribution to emotional resonance.

Ant Group, the Chinese fintech giant behind Alipay, exemplifies this transformation. Under the leadership of Eric Jing, the company built an AI-driven financial platform that not only serves hundreds of millions of consumers but also provides microloans, insurance, and investment tools — all powered by real-time machine learning. Their AI models assess risk more accurately than traditional financial institutions, opening access to underserved populations and reshaping the economics of financial services.

Accelerating product and service innovation

Airbus applies AI to develop autonomous flight systems and optimize aircraft design. Their “Skywise” platform aggregates operational data from fleets around the world and uses AI to predict maintenance needs, reduce downtime, and identify design improvements — turning aircraft into learning machines.

AI dramatically shortens the innovation cycle. Leaders can now:

  • Generate and test product ideas using generative design

  • Use customer behavior data to shape new features

  • Deploy AI agents to co-create with users in real-time

Consider Procter & Gamble, where AI is embedded across the product innovation pipeline. Using deep learning and computer vision, P&G tests packaging designs, optimizes formulations, and even simulates consumer product interactions before market launch. CEO Jon Moeller has championed an AI-first mindset, making data-driven creativity central to innovation.

Redefining customer engagement with AI

At the heart of AI’s power is personalization at scale. Business leaders can now:

  • Build real-time, omnichannel customer experiences

  • Use conversational AI to enhance service, sales, and loyalty

  • Predict customer needs before they express them

Sephora, under the leadership of CEO Jean-André Rougeot, has emerged as a global leader in AI-powered retail. Its Virtual Artist tool uses augmented reality and computer vision to help customers try on makeup digitally, while AI recommendation engines drive tailored product suggestions. This data-rich engagement strategy has transformed Sephora into a tech-enabled beauty platform.

In India, Reliance Jio, led by Mukesh Ambani, has used AI to provide millions of customers with personalized content, real-time support, and mobile commerce experiences — helping it go from telecom entrant to digital ecosystem leader in record time.

Reinventing the partner and supply ecosystem

AI doesn’t stop at the organization’s boundaries. It enables smarter, more adaptive networks of partners, suppliers, and collaborators. Leaders can use AI to:

  • Predict supply chain disruptions and optimize logistics

  • Match partners dynamically based on data signals

  • Build trust through transparent, AI-audited processes

Maersk, the global shipping giant, applies AI to optimize routes, reduce carbon emissions, and enhance visibility across its supply chain. By combining AI with blockchain and IoT, Maersk creates a responsive logistics network — and positions itself as a digital trade facilitator rather than just a shipping company.

Similarly, Unilever uses AI across its supply chain to manage inventory, predict demand, and even guide sustainable sourcing. CEO Hein Schumacher has continued the AI investments started by his predecessor, with a vision of building intelligent operations that align business growth with environmental responsibility.

The leadership shift

To lead AI-powered reinvention, business leaders must develop a new set of capabilities and behaviors. Here’s what it takes:

1. Digital Literacy at the Top

Leaders don’t need to be coders, but they must understand AI’s potential and limitations. They should be fluent in asking the right questions — about data quality, bias, model transparency, and use-case feasibility. Satya Nadella at Microsoft sets the standard here, championing AI across all business units while staying grounded in responsible AI principles.

2. Experimentation as a Leadership Norm

AI thrives in environments where leaders embrace testing, iteration, and learning. Leaders must create “safe zones” for rapid prototyping and encourage teams to take calculated risks. Ajay Banga, during his time at Mastercard, built innovation hubs around the world where teams explored AI in fraud detection, customer service, and financial inclusion — without fear of failure.

3. Ethics and Governance as Strategy

AI’s rise brings ethical and regulatory risks. Leaders must ensure AI is explainable, fair, and privacy-conscious. Embedding ethics into product design and decision-making is no longer optional. At DBS Bank, CEO Piyush Gupta ensures all AI initiatives undergo ethical reviews and adhere to a “responsible AI framework” — helping the bank retain trust as it digitizes.

4. Cross-functional Collaboration

AI can’t succeed in silos. Leaders must foster collaboration between data scientists, designers, marketers, and business strategists. At Amazon, teams work backward from customer needs, and AI is woven across everything — from Alexa’s NLP to warehouse automation and pricing algorithms. Jeff Bezos created a culture where tech, operations, and business were inseparable.

5. Vision Beyond the Hype

Leaders must cut through buzzwords and ground AI efforts in real business value. AI is not magic — it’s math, data, and execution. Those who succeed treat it as a capability, not a cure-all.

Economic potential of AI

Cathie Wood, of ARK Invest, is a leading thinker on the economic potential of AI in coming years. Her Big Ideas 2025 report envisions AI as a transformative force poised to drive unprecedented economic growth. She forecasts that AI, alongside other emerging technologies, will significantly enhance productivity and reshape the global economy.

She predicts that the USA economy is transitioning into a new era of productivity-led growth, powered by advances in AI, digital assets, and automation. She believes that these technologies will reduce costs, boost output, and help keep inflation under control even as growth resumes.

ARK’s report explores how AI is central to a convergence of five innovation platforms—AI, robotics, energy storage, DNA sequencing, and blockchain—that collectively have the potential to drive exponential economic growth.

Wood estimates that the US GDP could grow by 7.3%, the highest in modern history, as AI, automation, and cryptocurrencies reshape the global economy. She argues that these technological advancements will counter inflationary pressures while enhancing corporate efficiencies, marking the beginning of a long-term bull market.

As an example, in the pharmaceutical industry, companies like Recursion Therapeutics have seen the number of hypotheses a researcher can test increase from 20 per year to 200 per year, with drug development timelines potentially shrinking from 13 years to eight years and costs dropping from $2.4 billion to $600 million per drug.

Reimagining business with AI

AI offers more than productivity gains or incremental improvements. It offers the canvas for reimagining what a business is. But that transformation starts at the top. Leaders must disrupt their own thinking — moving from hierarchy to ecosystems, from static plans to adaptive systems, and from data-rich dashboards to insight-driven action.

The companies leading this revolution aren’t just using AI. They’re becoming AI-native in their strategies, cultures, and identities.

To harness the future, leaders must not only adopt AI — they must lead as if they were reinventing the business from scratch. Because in many ways, they are

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