Most agentic Artificial Intelligence (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, says Anushree Verma, senior director analyst at Gartner. According to Gartner estimates, over 40% of agentic AI projects will be cancelled by the end of 2027 due to escalating costs, unclear business value, and inadequate risk controls.
Most agentic AI projects now are early-stage experiments or proofs of concept 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," Verma adds. Adding to the problem, 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.
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, it said.
“To get real value from agentic AI, organisations must focus on enterprise productivity, rather than just individual task augmentation,” says 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," she adds.
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.