Lessons from the world’s leading AI transformations and what they mean for the UK
Bhavya Kapoor, president of Asia Pacific for Avanade – a joint venture between Microsoft and Accenture, where he runs the business across a region that has consistently outpaced the West on digital adoption. Having seen high-growth markets leapfrog legacy infrastructure, he explains what that comparison looks like from the outside, and what UK business can learn from APAC.
What can the UK learn from global enterprises’ approach to AI and digital transformation?
One of the most consistent observations from advising organisations globally is that the conversation has moved beyond AI ambition and into AI execution. Competitive advantage increasingly belongs to organisations that can operationalise AI at scale, while connecting it directly to business outcomes.
Many organisations are now focused on scaling AI and generating measurable business outcomes, rather than simply developing strategies or running pilots.
Governments increasingly view AI as critical economic infrastructure and a foundation for future growth and competitiveness. This has helped create alignment between public policy, business investment and digital transformation programmes.
Across both mature and emerging markets, organisations are accelerating AI adoption at different speeds, but the common success factors remain remarkably consistent: strong executive sponsorship, modern digital platforms, workforce readiness and clear business outcomes.
In some cases, organisations have been able to leapfrog older infrastructure altogether, accelerating cloud adoption, digital services and AI implementation.
Ultimately, the key differentiator is no longer whether organisations have an AI strategy. The organisations creating the most value are those that have learned how to execute AI at scale across the business.
Is the UK becoming too cautious about AI, and could that put British businesses at a competitive disadvantage?
There is an understandable focus on responsible AI, governance and risk management, but the greater danger may be moving too slowly while competitors accelerate adoption.
Business leaders globally recognise this risk. Research shows that 85% of mid-market leaders worry about losing competitive advantage if they fail to adopt AI quickly enough. The challenge is finding the right balance between innovation and responsibility.
Responsible AI should not be viewed as a barrier to progress. Instead, it should provide the guardrails that allow organisations to innovate confidently and at scale.
The businesses best positioned for success are those that balance strong governance with speed of execution. They understand that trust and innovation are not opposing forces, they are mutually reinforcing.
Many organisations have experimented with AI, but few have scaled it. What’s holding businesses back?
A significant number of organisations remain trapped in the proof-of-concept phase. While experimentation has been widespread, scaling has proved far more challenging.
Nearly half of mid-market organisations are still building their AI business case, while many others have yet to move beyond pilot programmes. The challenge is rarely the technology itself.
Successful AI transformation requires a combination of governance, data readiness, cloud infrastructure, security, workforce preparation and sustained executive sponsorship. Weakness in any one of these areas can slow progress significantly.
Across industries and geographies, the organisations that successfully scale AI take an integrated approach, aligning AI, cloud, data, security and workforce transformation initiatives around strategic business outcomes.
You’ve spoken about the shift from ‘AI ON’ to ‘AI IN’. What does that mean, and why does it matter?
Many organisations today are focused on what can be described as “AI ON”, using AI tools to improve individual productivity and help employees work faster and more efficiently.
While these gains are important, productivity improvements alone rarely create sustainable competitive advantage.
“AI IN” represents the next stage of maturity. It means embedding AI directly into workflows, decision-making processes and core business operations. Rather than sitting alongside the business, AI becomes part of how the business actually functions.
This distinction matters because real transformation occurs when AI is integrated into the operating model. Moving from AI ON to AI IN is therefore not simply a technology decision: it is fundamentally a business strategy decision.
Across boardrooms and leadership teams globally, I increasingly see organisations moving beyond AI as a productivity tool and embedding it directly into business operations.
As AI becomes more autonomous, how can organisations innovate while maintaining trust and control?
Trust remains one of the most important foundations of successful AI adoption.
As AI systems become increasingly autonomous, organisations need governance frameworks that extend across data, models, infrastructure and AI agents. Leaders must be able to understand how systems behave, make decisions and take action.
The rise of agentic AI introduces additional considerations, requiring behavioural, operational and cognitive controls alongside traditional technology safeguards.
At the same time, human oversight, accountability and transparency must remain central. Organisations need clear ownership of AI-driven decisions and mechanisms for intervention when required.
Strong governance should not be viewed as a constraint. In practice, it provides the confidence needed for organisations to scale AI more assertively and responsibly. Leading global enterprises increasingly recognise that governance is not a compliance exercise, it is a strategic capability that enables AI to be deployed confidently across markets, business units and functions.
What separates organisations creating real business value from AI from those that are simply experimenting?
The most successful organisations start with business outcomes rather than technology.
Instead of deploying AI for its own sake, they focus on solving meaningful business challenges and creating measurable value. They move beyond pilots and embed AI into core operational processes where it can drive lasting impact.
As a result, AI success is increasingly measured through productivity improvements, quality gains, operational efficiency and customer outcomes.
The most advanced organisations go a step further, connecting AI performance directly to enterprise KPIs. This creates clear accountability and ensures AI investments remain closely aligned to strategic priorities.
How will AI change the workforce over the next five years, and what are leaders getting wrong today?
As AI takes on more routine and repetitive tasks, employees will increasingly focus on oversight, judgement, problem-solving and other higher-value activities that require human expertise.
One of the most underestimated barriers to AI adoption remains workforce readiness. Many organisations invest heavily in technology while underinvesting in change management and capability building.
The organisations leading AI transformation globally are prioritising transparent communication, continuous learning, workforce reskilling and AI literacy at scale.
Ultimately, AI transformation succeeds when leaders recognise it as a people transformation. Technology may enable change, but people determine whether that change delivers value.
Working with organisations and leadership teams around the world, what trends do you believe will have the greatest impact on the future competitiveness of UK businesses?
The clearest trend is the shift from experimentation to enterprise-wide execution. Organisations globally are increasingly focused on scaling AI across functions, business units and operating models.
At the same time, governments and businesses alike are treating AI as strategic infrastructure, recognising its importance to long-term economic competitiveness and growth.
Another notable development is the move from productivity-focused AI initiatives towards operationally embedded AI. Organisations are no longer asking how individuals can work faster - they are asking how AI can transform the way the business operates.
As adoption matures, trust, governance and workforce transformation are becoming decisive success factors rather than afterthoughts.
The organisations that will lead the next era of growth are those that successfully combine innovation, responsible AI and disciplined execution. The lessons emerging from leading enterprises around the world are increasingly consistent: AI success depends less on the technology itself and more on leadership’s ability to scale, govern and operationalise it. For UK businesses, the opportunity is not simply to adopt AI, but to use it as a catalyst for long-term competitiveness, growth and reinvention.
