Gartner Forecasts High Cancellation Rate for Agentic AI Projects by 2027

Brickinfo News Agency – Over 40% of agentic AI projects are expected to be canceled by the end of 2027, according to a recent analysis by Gartner, Inc. This significant cancellation rate is attributed to a combination of escalating costs, unclear business value, and insufficient risk controls associated with these early-stage AI initiatives.

Many of these projects are currently in experimental or proof-of-concept phases, often driven more by industry hype than by a clear understanding of their practical application and scalability. Anushree Verma, Senior Director Analyst at Gartner, stated, “Most agentic AI projects right now are early stage experiments or proof of concepts that are mostly driven by hype and are often misapplied.” She added that 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.”

A January 2025 Gartner poll involving 3,412 webinar attendees revealed varied levels of investment in agentic AI across organizations. While 19% reported significant investments, 42% had made conservative investments, and 8% had made no investments. The remaining 31% were either taking a wait-and-see approach or remained unsure about their strategies. This caution may be well-founded, as many vendors are contributing to the inflated expectations through “agent washing,” which involves rebranding existing products like AI assistants, robotic process automation (RPA), and chatbots as agentic AI without genuinely advanced capabilities. Gartner estimates that only approximately 130 of the thousands of purported agentic AI vendors offer legitimate solutions.

Verma also highlighted a key issue regarding the current state of the technology. “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,” she noted, further stating, “Many use cases positioned as agentic today don’t require agentic implementations.” This suggests a mismatch between the capabilities of existing agentic AI models and the ambitious goals often set for them.

Despite these initial hurdles, agentic AI is still seen as a crucial advancement in AI capabilities and a source of future market opportunities. It is anticipated to enhance resource efficiency, automate complex tasks, and drive business innovations beyond what traditional scripted automation bots and virtual assistants can achieve. Gartner projects that by 2028, at least 15% of daily work decisions will be made autonomously through agentic AI, a significant increase from 0% in 2024. Furthermore, 33% of enterprise software applications are expected to incorporate agentic AI by 2028, up from less than 1% in 2024. To mitigate risks and maximize value, Gartner advises organizations to pursue agentic AI only where it demonstrates clear value or ROI, recommending that instead of integrating agents into legacy systems, organizations should consider re-thinking workflows from the ground up with agentic AI in mind for successful implementation. “To get real value from agentic AI, organizations must focus on enterprise productivity, rather than just individual task augmentation,” Verma concluded. “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.”