Organisations are under growing pressure to adopt artificial intelligence, but new research from Gartner shows many are using AI in areas where it delivers little value, leading to stalled projects and missed return on investment.
Gartner’s latest survey of infrastructure and operations (I&O) leaders reveals that only 28% of AI use cases fully meet ROI expectations, while around 20% fail outright. More than 57% of organisations report at least one failed AI initiative, underscoring the scale of the challenge.
The research points to a common issue that organisations are trying to fit AI into problems it is not designed to solve, often driven by hype or unrealistic expectations about automation and cost savings.
The study also shows that many AI projects struggle not because the technology doesn’t work, but because organisations lack clear goals or the preparation needed to support these tools. Issues such as poor data quality and weak governance were major contributors to these failures.
In contrast, organisations that succeed with AI tend to take a more practical approach. Research found that 33% of successful leaders embed AI directly into existing systems and workflows, rather than treating it as a standalone initiative.
More than 53% of successful deployments occur in mature, proven areas such as IT service management (ITSM) and cloud operations, where the business value is already well established.
Leadership support is also critical as 26% of successful leaders report full executive backing, and 25% cite strong cross functional collaboration as a key success factor.
Jason Kurtz, CEO of Basware, commented: “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.”
Gartner’s research reinforces the need for organisations to prioritise realistic business cases, strong governance, and clear operational alignment before rolling out AI tools.
Without these foundations, organisations risk adding unnecessary complexity and missing out on the benefits AI can offer.
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