Gartner has warned that over 40% of agent-based artificial intelligence (AI) projects will be abandoned by 2027. The report points to soaring implementation costs, weak business alignment, and poor risk frameworks as major reasons behind the projected failure rate. While the market remains bullish on the long-term promise of autonomous AI, the present reality suggests that a wave of early projects may collapse under inflated expectations and immature execution.
Early-Stage Projects Driven by Hype, Not Value
Today’s agentic AI initiatives are still in the early experimental phase. Gartner highlights a pattern where companies rush to deploy AI agents without fully understanding their actual costs, complexity, or business applications. “Organisations are still treating autonomous AI as a novelty,” said Anushree Verma, Senior Director Analyst at Gartner. “That mindset leads to stalled rollouts, abandoned trials, and massive resource waste.” Gartner’s January 2025 survey of 3,412 webinar participants revealed a cautious approach across the board.
While 19% of companies had made significant investments in agentic AI, 42% were proceeding slowly. Another 31% remained undecided or adopted a ‘wait and see’ stance, and 8% admitted they had not invested. As indicated by Verma, much of this work is never actually made real because outcomes are not properly defined. Companies wanting to be seen as innovative often underestimate the time taken, changes in engineering, and operational nuances that can bring agentic AI to scale.
Agent Washing and RPA Rebranding Undermine Credibility
Gartner also flagged a deceptive trend: agent washing. This refers to companies falsely marketing legacy tools, like robotic process automation (RPA) bots, chatbots, or basic AI assistants as agentic AI solutions. This wave of RPA rebranding has diluted trust in the market.
“Vendors are calling simple rule-based tools autonomous AI when they are anything but,” Verma said. “That makes it harder for enterprises to identify real agentic solutions.” Gartner estimates that only about 130 vendors globally offer legitimate agentic AI, despite thousands claiming otherwise. Many tools lack the agency to follow nuanced instructions or execute business goals independently. This branding confusion not only misleads decision-makers but also results in wasted budgets, missed goals, and reputational risk for companies betting on false AI maturity.
Long-Term Potential Remains Strong
Gartner believes agentic AI will become a long-term force in enterprise tech, predicting AI agents will handle 15% of daily business decisions by 2028, up from almost none in 2024. Furthermore, Gartner claims that then, one-third of all enterprise software applications will have some agentic capability.
This anticipated growth aligns with a couple of caveats. Gartner urges that leaders must ensure adoption is always tied to business value, as opposed to conjecture. If enterprise organizations move ahead and deploy without alignment of AI capability and business process, the outcomes will continue to be stalled deployment or poor returns on investment. Real transformation won’t take place until organizations accept autonomous AI as part of their digital roadmap, as opposed to an experiment.
Strategic Focus Needed to Realise Value
To avoid project abandonment, Gartner advises organizations to rethink their entire approach. Rather than patching AI into outdated systems, businesses must redesign workflows with autonomy and scale in mind. Verma recommends a layered model, using autonomous AI for complex decisions, automation for repetitive tasks, and AI assistants for basic functions.
The path forward requires technical maturity and strategic clarity, not rushed investments in repackaged tools. Gartner’s latest report is a reality check for the AI sector. Amid rising hype, agent washing, and widespread RPA rebranding, companies must focus on substance over style. While autonomous AI holds massive potential, success depends on clear goals, trusted tools, and enterprise-wide alignment. Only those who deploy it with strategy, not spectacle, will stay ahead in the evolving AI landscape.
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