More than 40% of agentic AI projects will be canceled by the end of 2027 due to rising costs, unclear business value or inadequate risk controls, according to the Gartner, Inc..
“Most agentic AI projects at the moment are early-stage experiments or proof-of-concepts that are driven primarily by hype and are often poorly applied,” he says Anushree Verma, Senior Director Analyst at Gartner. “This can blind companies to the true cost and complexity of implementing AI agents at scale, preventing projects from going into production. They need to overcome the hype to take strategic decisions and careful about where and how to apply this emerging technology.”
According to a January 2025 Gartner survey of 3,412 webinar participants, 19% said their companies have made significant investments in agentic AI, 42% have made conservative investments, 8% have made no investments, and the remaining 31% are taking a wait-and-see approach or are unsure.
Many suppliers are contributing to the hype by engaging in “agent laundering” (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.
"Most agentic AI proposals lack significant value or return on investment (ROI) because current models lack the maturity and capability to autonomously achieve complex business goals or follow differentiated instructions over time," says Verma. "Many use cases positioned as agentic today do not require agentic implementations."
Delivering value to the business
Despite these initial challenges, the trend toward agentic AI represents a leap forward in AI capabilities and market opportunities. Agentic AI will provide new ways to improve resource efficiency, automate complex tasks, and introduce business innovations beyond the capabilities of bots automation with script and virtual assistants.
Gartner predicts that at least 15% of everyday work decisions will be made autonomously through agentic AI by 2028, compared to 0% in 2024. Furthermore, 33% of enterprise software applications will include agentic AI by 2028, up from less than 1% in 2024.
At this early stage, Gartner recommends adopting agentic AI only where there is clear value delivery 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 outset is the ideal path to successful implementation.
“To get real value from Agentic AI, companies should focus on company productivity, not just improving individual tasks,” says Verma. “They can start by using AI agents when decisions are needed, automation for routine workflows, and assistants for simple recovery. It's about driving business value through cost, quality, speed, and scale.”
Gartner clients can read more in the report Emerging Tech: Avoid Agentic AI Failure: Build Success Using Right Use Cases.
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