Gartner Predicts Over 40% of Agentic AI Projects Will Be Canceled by End of 2027

Over 40% of agentic AI projects will be canceled by the end of 2027, due to escalating costs, unclear business value or inadequate risk controls, according to Gartner, Inc.

“Most agentic AI projects right now are early stage experiments or proof of concepts that are mostly driven by hype and are often misapplied,” said Anushree Verma, Senior Director Analyst, Gartner. “This can blind organizations 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.”

According to a January 2025 Gartner poll of 3,412 webinar attendees, 19% said their organization had made significant investments in agentic AI, 42% had made conservative investments, 8% no investments, with the remaining 31% taking a wait and see approach or are unsure.

Many vendors are contributing to the hype by engaging in “agent washing” – the rebranding of existing products, such as AI assistants, robotic process automation (RPA) and chatbots, without substantial agentic capabilities. Gartner estimates only about 130 of the thousands of agentic AI vendors 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,” said Verma. “Many use cases positioned as agentic today don’t require agentic implementations.”

Gartner predicts at least 15% of day-to-day work decisions will be made autonomously through agentic AI by 2028, up from 0% in 2024. In addition, 33% of enterprise software applications will include agentic AI by 2028, up from less than 1% in 2024.

Gartner clients can read more in the report, “Emerging Tech: Avoid Agentic AI Failure: Build Success Using Right Use Cases.”

Channel Impact^®
In this early stage, Gartner recommends agentic AI only be pursued where it delivers clear value or ROI. Integrating agents into legacy systems can be technically complex, often disrupting workflows and requiring costly modifications. In many cases, rethinking workflows with agentic AI from the ground up is the ideal path to successful implementation.