Gartner predicts 40% of agentic AI projects will fail by 2027
A Gartner report forecasts over 40% of agentic AI projects will be cancelled by 2027 due to high costs, unclear ROI, and security concerns.
A new Gartner report warns of significant project failures in the agentic AI space.
Key Findings
- 40% failure rate: Gartner predicts more than 40% of agentic AI projects will be cancelled by 2027
- Primary reasons: Growing costs, elusive business value, and insufficient security
- Survey data: Based on January 2025 poll of 3,412 webinar attendees
Current Investment Landscape
- 19% of organizations made significant investments
- 42% took conservative approaches
- 8% have no investments
- 31% are adopting wait-and-see strategies
Expert Commentary
"Most agentic AI projects are early-stage experiments driven by hype," said Anushree Verma, Senior Director Analyst at Gartner. "Organizations need to make strategic decisions about where and how to apply this technology."
Vendor Challenges
- Agent washing: Many vendors rebrand existing products as AI agents
- Market reality: Only about 130 of thousands of agentic AI vendors have substantial offerings
Future Outlook
Despite current challenges, Gartner forecasts:
- 15% of daily work decisions will be autonomous by 2028 (up from 0% in 2024)
- 33% of enterprise software will include agentic AI by 2028 (up from <1% in 2024)
Published: June 25, 2025 | Read more about Oracle's AI developments
Related News
Agentic AI Disrupts Digital Advertising Landscape
This article explores the rise of agentic AI and its transformative impact on digital marketing, including autonomous decision-making and industry adaptation.
Agentic AI Revolution Demands New Governance and Trust Frameworks
GenAI is evolving from Copilots to autonomous Agents, transforming enterprise software development and raising critical trust and governance challenges.
About the Author
Michael Rodriguez
AI Technology Journalist
Veteran technology journalist with 12 years of focus on AI industry reporting. Former AI section editor at TechCrunch, now freelance writer contributing in-depth AI industry analysis to renowned media outlets like Wired and The Verge. Has keen insights into AI startups and emerging technology trends.