HTEC launches The HTEC AI Value Realization Report 2026, revealing a new challenge emerging as organisations move beyond AI experimentation: investment is accelerating faster than many companies’ ability to measure, govern and consistently realise its value.
The independent study finds that 79% of organisations have increased AI investment over the past year, with spending rising by 31% on average. Yet 77% of executives now believe AI value is constrained more by people and processes than by technology.
The findings point to a significant shift in the enterprise AI debate. The question is becoming less about whether organisations can deploy AI and more about whether they can turn it into sustained and measurable business performance.
“The AI conversation has moved on. The challenge is no longer simply getting access to AI or finding places to deploy it. It is proving that investment is translating into meaningful business outcomes,” said Alex Rumble, Chief Marketing Officer at HTEC.
“What stands out from this research is that the biggest barriers are increasingly organisational rather than technological. Companies need to be as deliberate about adoption, operating models, measurement and governance as they have been about the technology itself.”
AI value is moving beyond cost reduction
The research suggests the definition of AI value itself is changing. Just 18% of executives rank cost reduction among their most important AI outcomes. Improved decision-making, productivity, customer experience, innovation and faster time-to-market now rank more prominently.
But as expectations broaden, proving value becomes harder.
Only 27% of organisations have clearly communicated AI’s purpose and expected outcomes across the business, while organisations remain divided on how AI value should be measured. Strategic outcomes, financial returns, operational performance, employee measures and customer outcomes all feature prominently, with no single measurement model emerging as the standard.
At the same time, 71.5% of organisations lack comprehensive enterprise-wide visibility into AI adoption, usage patterns and outcomes, relying instead on partial reporting, function-level tracking, anecdotal feedback or having no visibility at all.
That visibility gap is beginning to have consequences. Around a quarter of executives report higher AI usage costs resulting from insufficient tracking, while 26% cite increased reliance on external partners as an unexpected consequence of adoption.
Greater AI autonomy is raising the stakes
The challenge becomes more acute as AI systems become more autonomous.
Only 14% of organisations systematically measure AI risk across their portfolio, while approaches to human oversight remain highly fragmented. The research suggests governance and accountability practices have not yet developed at the same pace as AI adoption.
“I have seen several technologies reshape the enterprise, but AI is different because it can increasingly act, not just inform,” said Lawrence Whittle, Chief Strategy Officer at HTEC.
“The greater that autonomy becomes, the more clearly organisations must define risk, oversight, and accountability.”
One AI market, very different industry challenges
The global picture also masks significant differences between industries.
Telecommunications appear further ahead in AI maturity, with 52% of organisations already scaling established initiatives or describing themselves as AI-native. Healthcare is progressing more cautiously, with 28% still at the early exploration stage.
Industries are also pursuing different kinds of value. Financial services and telecommunications place greater emphasis on improving decision quality, while manufacturing prioritises productivity. Automotive and healthcare and life sciences place greater emphasis on accelerating time-to-market.
And the barriers differ. Nearly a third of manufacturing executives identify data availability as their primary measurement challenge, automotive organisations are most constrained by tooling limitations, while retailers are particularly challenged by attributing outcomes to AI.
These differences will be explored in greater depth through a forthcoming series of HTEC industry-specific AI Value Realisation reports, examining how investment, adoption, measurement and governance are evolving across financial services and insurance, healthcare, automotive, telecommunications, retail, semiconductor, and manufacturing and utilities.
From deploying AI to realising value
The research suggests the next stage of enterprise AI will not be defined simply by adoption.
As investment grows, competitive advantage will increasingly depend on whether organisations can understand where AI is creating value, where costs and risks are emerging, and whether people, processes and operating models are changing sufficiently to capture its potential.
For HTEC, the findings reinforce the need to connect AI implementation with organisational transformation, governance, visibility, and measurable business outcomes.
The HTEC AI Value Realisation Report 2026 is available here.
