UK businesses struggle to turn AI investment into strategic advantage

Despite heavy investment in AI, UK firms are lagging in developing cohesive, enterprise-wide strategies, hampered by data, skills, and governance challenges, industry reports reveal.

Artificial intelligence is reshaping UK business, but enthusiasm has not yet translated into coherent, enterprise-wide strategies, industry and government data show. According to the original report from SAP and Oxford Economics, UK firms are investing heavily in AI, an average of £15.94m ...

this year with plans to lift spending by around 40 per cent over the next two years, but only a small minority are pursuing a unified approach. The report found that just seven per cent of businesses have an enterprise-wide AI strategy, while many describe investment as piecemeal, department-led or ad hoc.

That fragmentation sits alongside strong pockets of progress. Government figures indicate roughly 15 per cent of UK businesses have adopted at least one AI technology, with adoption rising steeply by company size: around two-thirds of large firms use AI compared with far lower rates among small and medium-sized enterprises. In manufacturing, for example, the UK is reported to be a European leader, with the majority of factory-floor operators using or planning to deploy AI for tasks such as computer vision for quality control and predictive maintenance, applications already delivering measurable reductions in defects and operating costs.

The gap between interest and effective use often comes down to data, skills and governance. Industry analysis highlights that while businesses generate vast amounts of contextual data from core systems, many remain digitally immature: talent shortages, fragmented data estates and limited staff training hinder scalable AI deployment. The SAP–Oxford Economics survey found widespread “shadow AI” use, with employees turning to unapproved tools in the absence of comprehensive training, an indication that worker appetite for AI outstrips formal organisational readiness.

Bridging that divide requires three linked priorities, according to industry commentary. First, organisations need a clear, cross-functional strategy that ties AI to measurable business processes rather than isolated pilots. Second, firms must invest in data foundations and integration so models work with accurate, business-contextual information. Third, people and governance matter: dependable returns depend on upskilling staff, managing shadow use, and embedding responsible controls around accuracy, privacy and security.

Vendors and platforms say they can accelerate that shift by embedding AI into business workflows. According to the announcement from one major enterprise software provider, their Business AI and role-based Joule Agents deliver process-aware intelligence inside transactional systems, aiming to speed routine tasks and surface insights within familiar applications. The company claims these agents can dramatically reduce task times and hasten insight generation, but industry analysts caution that platform capabilities must be paired with organisational change to realise promised gains.

For many UK companies the path to value will therefore be organisational as much as technical. Data and platform investments can multiply returns only when aligned with enterprise-wide objectives, workforce development and clear governance. As one industry report put it, a focus on digital maturity, closing skills gaps, unifying data and formalising strategy, is essential if AI is to move from a collection of promising experiments to a sustained driver of growth and productivity.

Until that alignment is more widespread, businesses risk paying for technology without securing the operational change needed to capture its benefits. The evidence points to a practical, phased approach: define enterprise goals for AI, shore up the data and skills that support them, and embed trusted AI into the systems and roles that run the business. When those elements come together, the promise of AI, faster processes, richer insights and measurable cost reductions, becomes far more attainable.

Source: Noah Wire Services