AI investment continues to surge despite sluggish returns

Organisations across the globe are accelerating their investment in artificial intelligence, even as many continue to report underwhelming returns.

Despite rising costs, inconsistent performance, and growing concerns about data quality, businesses are pressing ahead with AI adoption largely under competitive pressure and to avoid falling behind.

New analysis from IDC, commissioned by Expereo, shows that enthusiasm for AI is outpacing operational readiness.

With 70 per cent of organisations now investing heavily in AI, many still lack the data foundations, governance structures and infrastructure maturity required to support AI at scale, resulting in limited productivity and inconsistent outcomes.

The findings highlight a widening gap between AI ambitions and AI outcomes, with only 19 per cent of organisations reporting that their AI projects have exceeded expectations, and more than half citing poor-quality training data as a key barrier to performance.

Sheila Flavell, CBE, COO of FDM Group said: “As AI adoption accelerates across industries, organisations must ensure their workforce has the skills to work effectively alongside these technologies. Our research highlights that over half (54 per cent) of organisations now say AI skills will be required in all early-career roles; however, only 6 per cent of teams currently have high AI proficiency.”

“This gap underscores the urgent need for upskilling both existing staff and graduates entering the workforce. AI is not a replacement for human expertise; it amplifies it. By embedding practical AI training into professional development, organisations can equip employees to critically assess, guide, and collaborate with AI tools, rather than outsourcing thinking to technology.”

Richard Bovey, Chief for Data at AND Digital said: “AI investment is accelerating fast, especially with the rise of agentic AI platforms. However, without strong data governance, business leaders are effectively flying blind risk losing oversight of critical value streams. Currently, 58 per cent of organisations describe their data as ‘chaos’, which is more concerning as AI becomes increasingly autonomous.”

“The organisations leading in AI are the ones investing in high-quality data foundations. Without governance and reliable data platforms, AI workloads become brittle, costly, and difficult to audit. As agentic AI takes on more independent tasks, poor data becomes a systematic risk (in addition to threatening compliance). Strong data governance is therefore more essential than ever to ensure AI operates reliably, safely and at scale.”

Jason Kurtz, CEO of Basware, said: “Enterprises are right to rethink how and where they deploy AI as organisations often try to force AI into processes where it simply doesn’t add value, leading to overly ambitious projects, unclear outcomes, and disappointing returns. Recent research shows that many initiatives fail not because of the technology itself, but because they are poorly scoped and driven by expectation rather than clear use cases.”

“To deliver meaningful ROI, businesses should focus first on the areas where AI can be applied most effectively, typically highly standardised, data-rich processes within finance. Starting with use cases that are easier to automate, such as invoice processing or payment workflows, allows organisations to realise faster returns while building confidence and capability over time.”

“Where there are no competitive differentiation or proprietary data at stake, and value can be demonstrated quickly, it is sometimes actually better to build rather than buy. Ultimately, organisations that prioritise targeted, ROI-driven adoption starting small, scaling what works, and aligning technology decisions with real business outcomes will be best positioned to move beyond the hype and unlock sustainable value from AI.”