Over 40% of Agentic AI Projects will be Cancelled by 2027
Over 40% of agentic AI projects will fail by 2027 due to escalating costs, unclear business value or inadequate risk controls, according to a Gartner report.
Many businesses are moving quickly, in the rush to adopt agentic AI. The promise is huge: systems that work for you, make judgments, and run things well without you having to keep an eye on them all the time.
But as the hype dies down, the problems start to show up.
According to Gartner, over 40% of agentic AI projects will be cancelled by the end of 2027. Why? Because the path to implementation isn’t just paved with new ideas; it’s also full of rising prices, unclear ROI, and big risk concerns.
The question now isn’t just “Can we build it?” but “Should we—and how do we keep it sustainable?”
Beyond the Buzz: What’s Going Wrong with AI
“Most agentic AI projects right now are early-stage experiments or proofs of concept that are mostly driven by hype and are often misapplied,” said Anushree Verma, Senior Director Analyst, Gartner.
“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.”
According to a January 2025 Gartner poll of 3,412 webinar attendees, 19% said their organisation had made significant investments in AI agents, 42% had made conservative investments, 8% no investments, with the remaining 31% taking a wait and see approach or were 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 that only about 130 of the thousands of agentic AI vendors are real, leaving most businesses still struggling to achieve true value.
“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 Anushree Verma.
“Many use cases positioned as agentic today don’t require agentic implementations.”
A Long-Term Payoff Still Worth Pursuing
Despite these initial challenges, the trend toward AI agents represents a leap forward in AI capabilities and market opportunity.
Agentic AI will provide new means to enhance resource efficiency, automate complex tasks and introduce new business innovations, beyond the capabilities of scripted automation bots and virtual assistants.
Gartner predicts that 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.
In this early stage, Gartner recommends that 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.
Final Word: Focus on Productivity, Not Hype
AI agents are still in their early stages, so it’s full of both opportunities and risks. The long-term potential is still strong, even though many projects may fail because of unrealistic hopes, wrong use cases, and vendor hype.
“To get real value from agentic AI, organisations must focus on enterprise productivity, rather than just individual task augmentation,” said Anushree Verma.
“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.”
To be successful, organisations need to be clear on their goals, follow through with their plans, and keep their focus on measurable results.
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