From AI ambition to AI performance: how UK businesses can close the gap to global leaders
Global AI leaders are pulling ahead. And UK businesses have what it takes to join them – if they move quickly.
There's no shortage of AI ambition among UK businesses. Most are actively experimenting, trialling tools and running pilots. But success at scale is proving elusive for many. In a new global study of more than 1,200 business leaders across 19 countries, PwC has found global AI leaders are ahead of a chasing pack where many UK businesses reside.
The research shows the top 20% of organisations in the study are capturing nearly three quarters of all AI-driven returns. The leaders are not simply deploying more tools or chasing productivity gains. They are using AI to create new sources of growth, reinvent business models, improve decision-making and generate stronger returns on investment.
For UK businesses, that should focus the mind. The ambition and appetite are there. But too much AI activity is still stuck in pilots and efficiency projects that never scale. The businesses pulling ahead aren't measuring how much AI they're using, but whether it's actually making the business better.
“AI is delivering real ROI now, but that value is being captured disproportionately by a leading group. For businesses behind the leaders, this is a timely reminder and a reason for sharper focus. The opportunity is significant, but it is moving quickly, and competitors will not wait. Now is the time to act with conviction.”
Leigh Bates
Global Risk AI Leader, PwC UK
Move from pilots to a value-led strategy with purpose and accountability
While productivity and efficiency remain important parts of the AI business case, leading organisations are going even further. They’re now using AI to identify and pursue growth opportunities, reinvent business models, generate new sources of revenue, and more.
Yet, the research reveals many businesses are still using AI without a clear plan mapped to business objectives. They are piloting tools and trialling use cases but doing so without a prioritised roadmap or accountability among senior leaders. The result is a lot of activity, but not enough impact. These are businesses who are undoubtedly excited about AI but prioritising usage over usefulness.
Among the UK businesses surveyed, there are gaps to global leaders on having a robust roadmap for AI (60% UK v 82% global leaders), an AI vision that aligns to business objectives (60% v 79%), and a focus on holding leadership accountable for AI outcomes (56% v 74%). Without a clear plan and someone accountable for delivery, businesses risk pouring time and money into AI pilots that may never pay off.
The businesses generating stronger returns are taking a different approach. They are identifying where AI can create the greatest value, prioritising use cases accordingly, and making clear decisions on what to scale, stop or redesign. They are not asking, ‘where can we apply AI?' but ‘where can AI materially improve business performance?’
That outcome-led mindset is crucial. A good AI strategy shouldn't be measured by how many pilots are running but instead whether they’re improving growth, margins or customer outcomes.
Gaps between UK businesses surveyed and global AI leaders
60% v 82%
have a robust roadmap for AI
60% v 79%
have an AI vision that aligns to business objectives
56% v 74%
hold leadership accountable for AI outcomes
Invest with intent – and give it time to pay off
If UK businesses want to close the gap to global leaders, they must be prepared to back their strategy with investment. Only around a third of UK respondents believe their current levels of investment are sufficient to achieve their AI goals.
But closing this gap to the AI leaders won’t be solved by just spending more money. While the leaders do spend more than others, how and where they invest matters as much. Our research shows these leaders are far more likely to manage their AI investment with agility, reallocating financial and human resources towards higher-value opportunities as priorities shift, and backing innovative projects aimed at long-term returns even when short-term ROI is uncertain. The biggest returns will come from backing use cases that change the trajectory of the business, not those that just optimise what already exists.
“Investment in AI needs to be treated like a portfolio, not a series of distinct projects. The organisations seeing the best returns aren't necessarily the biggest spenders. They're the ones making deliberate moves, reallocating resources to where value is emerging, and having the confidence to invest for long-term success.”
Mike Magee
Deals AI Leader, PwC UK
Build solid foundations of data and technology
Investing in AI isn’t just about the forward-looking need for new skills and emerging technologies. It will not deliver sustained ROI if it is layered onto weak foundations. Data, cloud, governance, technology architecture and business process design all determine whether AI can scale beyond isolated use cases. That means resolving legacy IT challenges and moving to cloud-based platforms that enable enterprise-wide data integration. This can include sovereign cloud services where data jurisdiction is a concern.
Around a quarter of UK respondents say they have eliminated outdated technology systems, compared with over half of global AI leaders. UK businesses are also behind global leaders when it comes to data strategy and use, with half as many saying they are making use of structured data than global leaders to drive decision-making. Global leaders already have an edge too when it comes to the more challenging use of unstructured data (30% UK vs 45% global leaders).
Interviewed for the 29th PwC UK CEO Survey, Graham Charlton, CEO of Softcat, said even if businesses “don't know which applications and use cases will be most important…data quality, governance and availability of the right compute and storage underpins AI readiness”.
“Businesses must look at their approach to AI holistically. Building an AI strategy on flawed processes is a recipe for failure, as is layering powerful AI tools onto ineffective data and technology foundations. Ensuring each layer is aligned and optimised will set businesses up for long-term success. And that alignment extends to ensuring you also have the critical human skills needed to translate AI into real, tangible value.”
Claire Reid
Chief Technology and Innovation Officer, PwC UK
Develop a culture for AI success
AI performance is a leadership, workforce and culture challenge as much as a tech challenge.
The research shows businesses getting the best returns from AI are the ones where employees are confident generating and acting upon trusted and tested AI insights. Value comes when people are willing and able to use AI to make better decisions, redesign work, innovate and act with confidence. As such, giving people the skills and confidence to use AI effectively and responsibly is critical.
A culture primed to embrace AI is also key to recruiting and retaining the technical talent needed, such as data scientists and machine-learning engineers. Nearly two thirds of global AI leaders are confident they can attract talent, and are also more likely to incentivise employees to experiment and incorporate trusted AI insights into their decisions making. For UK businesses, it’s confirmation that investment in skills, culture and leadership must therefore sit alongside investment in platforms and tools.
“Embedding AI is as much about business transformation as technology. Leadership and skills are critical, and the role of culture cannot be overlooked. Culture is the force that empowers your people, builds confidence in technology, unites people behind your strategy and connects your business with the talent needed to drive long-term growth.”
Phillippa O’Connor
Chief People Officer, PwC UK
Stay strong on governance to drive growth and innovation
One area where the UK already enjoys relative strength is around compliance and governance. UK businesses are generally performing well on the fundamentals of good governance: including strong security around data and AI, clear rules on AI use, active engagement with regulators, and senior-level oversight of higher-risk use cases.
Businesses that treat governance as a green light to proceed at pace, rather than a hurdle to clear reluctantly, are better placed to use AI at speed and scale.
There are practical reasons for this. Every AI use case needs to pass through checkpoints before it can scale: risk sign-off, regulatory comfort, user trust and organisational buy-in. The clearer and more proportionate those checkpoints are, the faster good ideas get through them and start delivering results.
It’s what makes the UK's governance strength a real opportunity for organisations. Clear rules, strong oversight and senior accountability give businesses the confidence to move faster, try bolder things, and scale what works without second-guessing themselves at every step.
“Governance shouldn’t hold AI back. It should give you licence to go further, faster and to innovate with confidence.”
Leigh Bates
Global Risk AI Leader, PwC UK
Know when to stick or twist
UK businesses also show relative strength in their willingness to review AI initiatives and make decisions on what to scale and what to stop. But without clear objectives to measure against, even good review discipline can lead to the wrong calls.
Our survey revealed global AI leaders are 1.5 times more likely to use AI to create entirely new business models. As such, rather than spreading AI thinly across their business and culling outliers and underperformers, AI leaders are increasingly focused on identifying priority use cases performing strongly against progressive business objectives and then scaling them to deliver significant wins.
In an interview for the 29th PwC UK CEO Survey, Lee Perkins, CEO of public sector technology provider Civica, said he discourages multiple speculative pilots across his business, in favour of rigorously testing hypotheses before fully committing to use cases where long-term value is clear. One such example has been augmenting the work of software developers with AI agents. “Conventional wisdom says building software takes time,” Perkins said. “That has been thrown up in the air with AI. The ability to work with amazing software engineers who can then oversee dozens of agentic developers changes time to value, changes speed, changes return on investment completely.”
Global AI leaders are
1.5 times
more likely to use AI to create entirely new business models
Be optimistic – but act now
The gap to AI leaders is already significant, yet they refuse to stand still. For those UK businesses outside that cohort, the key now is to ensure any gathering sense of urgency doesn’t drive panicked decisions or a fresh wave of disparate pilots. Rather, they need to channel their urgency into building a coherent AI strategy and moving decisively to deliver it.
The businesses that succeed will be those that ask harder commercial questions. Which AI investments are improving growth? Which are speeding up time to value? And which should be stopped because they are creating activity, not impact?
AI’s promise is not simply doing the same things faster. It is creating new ways to grow, compete and deliver returns. For UK businesses, the message is clear: act now, invest with intent, focus on outcomes over outputs, and turn AI into a measurable source of growth, ROI and competitive advantage.
“For many UK businesses, important building blocks such as strong governance and an appetite for change are already in place. Those strengths now need to be woven into a clear strategy, underpinned by investment, a roadmap for delivery and real business objectives. Work needs to be accelerated to develop the right culture and to build solid data and technology foundations. The race to AI success is far from run, and the businesses who can act now can undoubtedly turn AI into a genuine driver of growth.”
Leigh Bates
Global Risk AI Leader, PwC UK
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