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Published on
June 25, 2025
5 min read
Agentic AI Faces Setbacks as New Gartner Reports Warns 40% of Projects Could Fail
A new report by tech research and advisory firm Gartner shows that over 40% of agentic AI projects will have been terminated by the end of 2027. According to Reuters, some of the reasons why these projects will be cancelled include rising costs, insufficient risk controls, and the lack of clarity regarding the business value that AI agents offer.
Early Stage Experiments
AI agents are tech systems that can complete tasks autonomously. Gartner’s research polled more than 3,400 respondents early this year. The findings showed that 19% of companies have made significant investments in AI agents.
About 42% of participating companies said they had made conservative investments while 8% had made none. 31% of respondents said they were unsure about investing in agentic AI or were taking a wait-and-see approach.
Tech companies like Oracle and Salesforce have already spent billions on the technology and are looking to optimize costs and boost their margins. However, Gartner’s agentic AI forecast 2027 shows it might be difficult for such companies to realize their profit goals.
“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,” Gartner’s Senior Analyst Anushree Verma said.
The Agent Washing Challenge
Gartner’s research report highlighted an emerging problem called agent washing. This refers to the practice of rebranding existing AI products like robotic process automation (RPA), AI assistants, and chatbots without developing their agentic capabilities substantially. The tech research and consulting firm estimated that out of the thousands of autonomous AI agent providers available, only 130 are real.
“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,” Verma added.
The Value Question
Even with these challenges, agentic AI provides a wide scope of advanced AI capabilities while presenting a significant market opportunity. At the current stage, Gartner advises companies to consider pursuing agentic AI in areas where the technology delivers clear value or offers real returns on investment.
According to the research and consulting company, integrating AI agents in legacy systems can disrupt workflows due to the highly complex and technical processes involved. In some instances, companies may be required to modify their processes, which can be extremely costly. However, the best way to implement agentic AI is to rethink workflows from the ground up.
“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,” Verma added.
Analysts in Gartner predict that agentic AI will be used to make at least 15% of daily work decisions autonomously by the end of 2028. The research firm also expects 33% of enterprise software applications to feature agentic AI by the end of 2028. This is a huge increase from the less than 1% of applications that included AI agents in 2024.
