Over 40% of agentic AI projects set for cancellation by 2027
More than 40% of agentic AI projects are forecast to be cancelled by the end of 2027, secondary to increasing costs, uncertain business value and insufficient risk controls, according to research from Gartner.
The prediction highlights growing concerns around the proliferation of agentic AI initiatives. Despite the rapid uptick in interest, many current projects remain exploratory and are often propelled by market hype rather than demonstrable business outcomes.
Anushree Verma, Senior Director Analyst at Gartner, commented on the current state of agentic AI deployment. She said:
"Most agentic AI projects right now are early stage experiments or proof of concepts that are mostly driven by hype and are often misapplied. This can blind organisations to the real cost and complexity of deploying AI agents at scale, stalling projects from moving into production. They need to cut through the hype to make careful, strategic decisions about where and how they apply this emerging technology."
A recent Gartner poll from January 2025, with responses from 3,412 webinar attendees, found a varied investment landscape for agentic AI. Of those surveyed, 19% reported their organisations had made significant investments in agentic AI, 42% noted conservative investments, 8% had made no investments, and the remaining 31% were either taking a wait-and-see approach or were unsure about their stance.
Market identity
The research identified a considerable disconnect between perceived and actual agentic AI vendors. Gartner estimates only about 130 vendors in the agentic AI space are genuine, despite claims from thousands. A common trend, referred to as "agent washing", involves the rebranding of existing products such as AI assistants, robotic process automation (RPA), and chatbots as agentic AI, irrespective of their actual capabilities.
Verma addressed the status of current agentic AI solutions and their real-world effectiveness, stating:
"Most agentic AI propositions lack significant value or return on investment (ROI), as current models don't have the maturity and agency to autonomously achieve complex business goals or follow nuanced instructions over time. Many use cases positioned as agentic today don't require agentic implementations."
Adoption and use cases
Despite these obstacles, agentic AI is projected to gain traction in daily business operations. Gartner expects at least 15% of day-to-day work decisions will be made autonomously through agentic AI by 2028, compared to essentially none in 2024. Similarly, it is forecasted that 33% of enterprise software applications will incorporate agentic AI features by 2028, up from less than 1% currently.
Gartner recommends that companies should pursue agentic AI projects only when there is clear value or a strong ROI justification. The integration of agentic agents into established systems poses significant technical challenges, often resulting in workflow disruptions and potentially high modification costs. In many instances, Gartner advises that re-evaluating and redesigning workflows from the ground up, with agentic AI as a central component, may lead to greater implementation success.
Verma elaborated on how organisations should approach adoption, noting:
"To get real value from agentic AI, organisations must focus on enterprise productivity, rather than just individual task augmentation. They can start by using AI agents when decisions are needed, automation for routine workflows and assistants for simple retrieval. It's about driving business value through cost, quality, speed and scale."
Broader context
The surge in agentic AI interest comes amidst wider trends across the IT sector focussed on expanding automation and enhancing enterprise software capability. However, the findings signal caution for organisations considering new agentic AI projects, highlighting the necessity for a rigorous evaluation of use cases, clear measurement of returns, and close management of implementation risks.
