Stuttgart, September 29, 2026 – A new AI study from GFT Technologies, an AI-centric global digital transformation company, finds that legacy infrastructure is one of the biggest obstacles to enterprise AI success, with the vast majority of technology leaders reporting it has already forced them to abandon AI initiatives outright.
The GFT survey, conducted by Wakefield Research among 945 CIOs and CTOs across 19 countries at companies with at least $500M in annual revenue (fielded August 11-31, 2026), reveals that AI's promise and its risks are accelerating in tandem. Key themes from the research include legacy infrastructure undermining AI initiatives, mounting scepticism over AI's return on investment, geopolitical and regulatory uncertainty reshaping vendor strategy, growing distrust of how companies explain AI-related workforce decisions, and rising personal risk for the technology leaders responsible for getting it right.
“AI adoption is moving quickly, but our research shows that enterprises are increasingly recognising the importance of the foundation underneath it. For many organisations, legacy infrastructure is becoming a real constraint—not only on innovation, but also on security and scalability. Closing that gap between AI ambition and infrastructure readiness is critical to turning AI investment into sustainable business value,” said Marco Santos, Global CEO, GFT Technologies.
Key findings from the report include:
Legacy infrastructure is holding AI back
Respondents view outdated systems as hindering AI progress and creating serious security risks.
- 84% say limitations in their legacy systems have caused their organisation to cancel an AI pilot or project
- 93% believe failing to modernise before running AI on old infrastructure will eventually trigger an enterprise-wide security crisis
AI investment is outpacing realistic value
Technology leaders express concern that AI spending is surpassing the value it can actually deliver, potentially pointing to an “AI bubble.”
- 89% are concerned that global AI investment may be growing faster than the business value it can realistically deliver
Geopolitical uncertainty is reshaping vendor strategy
Recent disruptions to AI model access are prompting a fundamental rethink of how enterprises source AI capability. While recent tensions in the U.S. have brought these risks into sharp focus, their implications extend well beyond any single market.
- 99% say potential government restrictions on AI access increase the importance of not depending on a single AI provider, following the U.S. government's dispute with Anthropic over access to its Mythos and Fable models earlier this year
- Against this backdrop, 42% of respondents are now leaning toward building AI infrastructure internally rather than buying from outside vendors
Scepticism over AI-driven workforce narratives
Technology leaders are pushing back on the idea that AI alone explains recent workforce changes.
- 91% believe some public companies cite AI to justify workforce changes that are primarily intended to boost their share price
Personal risk for technology leaders
As AI scales, CIOs and CTOs are increasingly concerned the fallout of failure could land on them personally.
- 89% are concerned a wrong workforce decision made while scaling AI could put their own job at risk
- Only 20% say their organisation's other C-suite executives and board members fully understand the security risks of running AI on legacy systems
What the data shows
GFT's analysis points to a widening AI implementation gap. While enterprises continue to accelerate AI adoption, many are scaling AI faster than the foundation underneath it can support. Legacy systems cause repeated project failures, single-provider dependence leaves AI roadmaps exposed to forces outside any one company's control, and the technology leaders responsible for getting it right increasingly bear the personal and professional cost when it doesn't go to plan.
Adoption is still accelerating despite all of this. Enterprises seeing real value from AI are treating it as the outcome of deliberate, ground-up investment rather than a layer added on top of infrastructure, governance, and workforce strategy built for a different era.
The findings point to a clear priority for enterprises seeking to close the AI implementation gap: preparing the foundations needed to scale AI securely and sustainably. That means modernising legacy environments, strengthening governance, managing technology dependencies, and aligning AI adoption with broader business and workforce strategies.
"The pressure to show AI results is real, but rushing ahead of your own infrastructure just moves the risk downstream. Building the foundation first is what makes the value and speed that comes later sustainable and scalable," said Santos.
Methodology
The GFT Survey was conducted by Wakefield Research among 945 CIOs and CTOs across 19 countries at companies with at least $500M in annual revenue, between August 11 and August 31, 2026, using an email invitation and online survey.
Results of any sample are subject to sampling variation. The magnitude of the variation is measurable and is affected by the number of interviews and the level of the percentages expressing the results. For the interviews conducted in this particular study, the chances are 95 in 100 that a survey result does not vary, plus or minus, by more than 3.2 percentage points on the global level from the result that would be obtained if interviews had been conducted with all persons in the universe represented by the sample.
