Nearly two-thirds of executives surveyed by Deloitte say their organizations are reevaluating their business models because of advances in agentic AI. Yet fewer than half say their organizations are prepared for agentic AI across the six areas of the business examined in the study. The report finds business processes and workforce readiness are the weakest areas.

The findings come from a survey of 501 U.S. senior managers and C-suite executives directly involved in their organizations’ agentic AI strategy or implementation. All of the organizations surveyed were at least piloting agentic AI. Deloitte also interviewed 20 executives and AI and data-science leaders at large organizations across industries.

The research suggests that companies are progressing through the early stages of agentic adoption at different speeds. Forty-two percent of respondents said their organizations are still testing small numbers of agents or have a few deployments underway. Another 43% said they are expanding deployment across functions. Just 15% said they have reached scaled, orchestrated, multi-agent adoption.

Where scaling is occurring, Deloitte says organizations are concentrating primarily on lower-risk, repeatable use cases with near-term returns, including applications in engineering, customer service and IT.

The challenge is that moving from individual applications to an enterprise built around autonomous systems requires a heck of a lot more than deploying yet another layer of technology.

The report’s authors say an agentic enterprise is likely to operate fundamentally differently from today’s organizations. That means organizations will need to redesign the work and the associated systems around AI agents rather than simply inserting agents into existing processes.

This transition is proving difficult.

Only about half of the executives surveyed say they have a clear view of their future operating model with AI agents. Three factors are identified as the biggest obstacles to scaling: 72% cite a lack of a unified and accessible data foundation, 70% cite an inability to trust and govern agents, and 67% cite the cost and complexity of integration.

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