AI agents: promise vs realityAgentic AI – Intelligent software which is designed to take action on its own without human intervention is gaining momentum in tech. From automation of tasks to making routine decisions, AI agents are being explored across most of the industries. But according to a recent&nbsp;<a href="https://www.gartner.com/en/newsroom/press-releases/2025-06-25-gartner-predicts-over-40-percent-of-agentic-ai-projects-will-be-canceled-by-end-of-2027">Gartner report</a>, the excitement may be running ahead of results.&nbsp;The report predicts that around 40 per cent of agentic AI projects will be cancelled by 2027, mainly due to rising costs, vague business outcomes, and the lack of mature risk and governance frameworks.<h2>What is agentic AI, and why is it trending?</h2>Agentic AI is not like traditional automation tools. These systems can make decisions, initiate tasks, and adjust over time based on inputs. Companies are experimenting with these agents to improve productivity, reduce human error, and scale operations.&nbsp;However, according to Anushree Verma, Senior Director Analyst at Gartner, many current projects are driven by hype rather than a clear understanding of business need. “Most agentic AI projects as of now are early-stage experiments that are mostly driven by hype and are often misapplied,” she said.<h2>Why are so many projects failing?</h2>Despite growing interest, implementation is proving challenging. Gartner’s 2025 survey of over 3,400 professionals found that only 19 per cent had made significant investments in agentic AI. A further 42 per cent were investing cautiously, while 31 per cent remained undecided.<h2>Issues which are holding back progress: &nbsp;</h2>High costs: Beyond development, companies face expenses related to infrastructure, compliance, and training.&nbsp;Legacy systems: Many traditional businesses struggle to integrate agentic AI into older platforms without major redesign.&nbsp;Lack of clear ROI:&nbsp; No measurable outcomes; many projects lose momentum.&nbsp;Misuse of the term: Many companies are relabelling chatbots or process automation tools as “AI agents”. &nbsp;Gartner reports highlight that only around 130 providers globally offer agentic solutions that truly meet the criteria of autonomy.<h2>Where agentic AI could succeed</h2>Despite current setbacks, reports also say it remains optimistic about the long-term impact. By 2028, it forecasts that 15 per cent of routine business decisions will be made by AI agents, and a third of enterprise software will include some level of agentic functionality.&nbsp;Areas where agentic AI is already showing potential include:&nbsp;Decision-making assisting in fraud detection or supply chain alerts.&nbsp;Workflow automation – managing complex claims or approvals.&nbsp;Productivity tools – automating IT or HR support at scale.&nbsp;Agentic AI is not a passing trend, but success depends on clear goals, strong governance, and a willingness to redesign how work gets done. While many projects may fail in the near term, those that align the technology with real-world problems stand a better chance of delivering long-term value.

Agentic AI, software that acts without human input, is trending but often fails due to high costs, unclear goals, and poor integration. Gartners report says 40 per cent of projects may be cancelled by 2027, but long term success is possible with clear use cases and governance.

AI agents: promise vs reality Agentic AI – Intelligent software which is designed to take action on its own without human intervention is gaining momentum in tech. From automation of tasks to making routine decisions, AI agents are being explored across most of the industries. But according to a recent Gartner report, the excitement may be running ahead of results. The report predicts that around 40 per cent of agentic AI projects will be cancelled by 2027, mainly due to rising costs, vague business outcomes, and the lack of mature risk and governance frameworks. What is agentic AI, and why is it trending? Agentic AI is not like traditional automation tools. These systems can make decisions, initiate tasks, and adjust over time based on inputs. Companies are experimenting with these agents to improve productivity, reduce human error, and scale operations. However, according to Anushree Verma, Senior Director Analyst at Gartner, many current projects are driven by hype rather than a clear understanding of business need. “Most agentic AI projects as of now are early-stage experiments that are mostly driven by hype and are often misapplied,” she said. Why are so many projects failing? Despite growing interest, implementation is proving challenging. Gartner’s 2025 survey of over 3,400 professionals found that only 19 per cent had made significant investments in agentic AI. A further 42 per cent were investing cautiously, while 31 per cent remained undecided. Issues which are holding back progress: High costs: Beyond development, companies face expenses related to infrastructure, compliance, and training. Legacy systems: Many traditional businesses struggle to integrate agentic AI into older platforms without major redesign. Lack of clear ROI: No measurable outcomes; many projects lose momentum. Misuse of the term: Many companies are relabelling chatbots or process automation tools as “AI agents”. Gartner reports highlight that only around 130 providers globally offer agentic solutions that truly meet the criteria of autonomy. Where agentic AI could succeed Despite current setbacks, reports also say it remains optimistic about the long-term impact. By 2028, it forecasts that 15 per cent of routine business decisions will be made by AI agents, and a third of enterprise software will include some level of agentic functionality. Areas where agentic AI is already showing potential include: Decision-making assisting in fraud detection or supply chain alerts. Workflow automation – managing complex claims or approvals. Productivity tools – automating IT or HR support at scale. Agentic AI is not a passing trend, but success depends on clear goals, strong governance, and a willingness to redesign how work gets done. While many projects may fail in the near term, those that align the technology with real-world problems stand a better chance of delivering long-term value.

Agentic AI, software that acts without human input, is trending but often fails due to high costs, unclear goals, and poor integration. Gartner's report says 40 per cent of projects may be cancelled by 2027, but long-term success is possible with clear use cases and governance.

Future of agentic AI: Why most AI agent projects aren't ready for real-world use

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Future of agentic AI: Why most AI agent projects aren't ready for real-world use