By 2027, more than 40% of agentic AI projects will be abandoned because of poor risk management, unclear business benefits, or growing costs.
Many of the current agentic AI projects, according to Gartner’s Anushree Verma, are hype-driven early experiments that are frequently misused.
Verma states, “This can blind organizations to the real cost and complexity of deploying AI agents at scale, stalling projects from moving into production.”
High Failure Rate Predicted: Over 40% of Agentic AI Projects Set to Be Abandoned by 2027
When deciding whether to use agentic AI, organizations should exercise caution and strategic judgment rather than succumbing to the hype.
According to a January 2025 Gartner survey of 3,412 webinar participants, 19% said they had made large investments in agentic AI, 42% said they had made conservative investments, 8% had made no investments, and 31% were unsure or waiting to see what happened.
By rebranding current technologies (such as chatbots, RPA, and AI assistants) without incorporating actual agentic features, vendors are inflating the market for agentic AI through a practice known as “agent washing.”
Only roughly 130 vendors out of the vast number of agentic AI providers, according to Gartner, genuinely provide authentic agentic AI capabilities.
According to Verma, because current models are not yet able to handle complex tasks or instructions on their own, the majority of agentic AI solutions do not provide strong business value or ROI.
True agentic AI implementation is not necessary for many so-called agentic AI use cases.
Agentic AI: A Transformative Leap Beyond Traditional Automation Despite Early Challenges
Notwithstanding its present drawbacks, agentic AI is a noteworthy development in AI that presents fresh chances for innovation and business automation.
Agentic AI can handle more complicated tasks and improve resource efficiency, in contrast to conventional automation bots and virtual assistants.
According to Gartner, by 2028, 33% of enterprise software applications will incorporate agentic AI, up from less than 1% in 2024, and 15% of daily business decisions will be made autonomously using agentic AI (up from 0% in 2024).
According to Gartner, agentic AI should only be implemented when it offers a definite return on investment or business value.
Because it disrupts workflow, integrating agentic AI with legacy systems can be costly and technically challenging.
Redesigning workflows with agentic AI in mind is frequently a better strategy than attempting to retrofit it into already-existing systems.
Verma says, “To get real value from agentic AI, organizations must focus on enterprise productivity, rather than just individual task augmentation.”
To optimize business value in terms of cost, quality, speed, and scale, she suggests using AI agents for decision-making, automating repetitive workflows, and using assistants for basic information retrieval.
