Deloitte’s 2026 Tech Trends research says enterprise AI agents are struggling to move beyond pilot programs, with an 89% failure rate from pilot to production. A separate Teradata survey found that 78% of companies have run at least one AI agent pilot, yet only 14% have expanded those deployments across the organization. The research points to six main barriers: scope creep, data access problems, missing evaluation frameworks, unclear ownership, uncontrolled costs, and security approval issues.
Other 2026 studies cited in the report show the same pattern. Gartner’s April 2026 survey of 782 infrastructure and operations leaders found that about 120 out of every 1,000 funded AI projects made it into production, and only 34 achieved return-on-investment targets. McKinsey said just 11% of companies had truly scaled AI agent use. Forrester reported rollback rates of 47% for production AI agents without automated evaluation, compared with 9% for agents covered by full evaluation systems. An industry survey also found that 83% of enterprises need infrastructure upgrades to support agentic AI deployments.
Deloitte’s 2026 Tech Trends research found that enterprise AI agents face an 89% failure rate when moving from pilot programs into production, according to Techub News.
A Teradata survey added that 78% of enterprises have run at least one AI agent pilot project, but only 14% have expanded those efforts for organization-wide use. The research identified six main obstacles to deployment: scope creep, data access, lack of evaluation mechanisms, unclear accountability, runaway costs, and security approval issues.
Surveys from multiple firms show the same bottleneck
Gartner said in an April 2026 survey of 782 infrastructure and operations leaders that about 120 out of every 1,000 funded AI projects reached production. Of those, only 34 met return-on-investment targets.
McKinsey’s 2026 research said only 11% of companies had genuinely achieved AI agent deployment at scale.
Forrester’s 2026 data showed that production AI agents without automated evaluation mechanisms posted a rollback rate of 47%, while agents with full evaluation coverage had a rollback rate of 9%.
An industry survey also found that 83% of enterprises need infrastructure changes to support agentic AI deployment.
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