Dive Brief:

  • Enterprises are finding it difficult to move from narrow, generative AI use cases to broad deployment of agentic systems, according to a Deloitte report published Wednesday. The professional services firm surveyed more than 500 technology leaders and conducted interviews with 20 executives and data science leaders to gather insights.
  • While roughly half of technology leaders say they have a clear view of their future AI operating models, only 15% of organizations have actually scaled multiagent systems. Most respondents admitted they are unprepared in areas such as workforce readiness, business processes, ecosystem partnerships, security, and governance policies.
  • Tech leaders should recognize that the shift is not about adding more agents, but about fundamentally changing how work is done within their organizations, said China Widener, vice chair and U.S. technology, media, and telecommunications industry leader at Deloitte, in an interview with CIO Dive. “It's a multiyear journey because it's going to continue to evolve, frankly, as the technology around the agents continues to improve.”

Dive Insight:

Enterprise spending has increasingly shifted toward agentic systems in 2026, but most organizations remain far from full-scale deployment readiness.

According to the Deloitte survey, technology leaders indicated that most organizations are at least three to four years away from having half of their business processes redesigned around AI agents, and from having those agents operate autonomously and collaboratively with each other.

Currently, many companies are layering AI agents onto existing processes rather than redesigning those processes from the ground up—a shortcut that may speed implementation but fails to unlock the technology's full potential, the report notes.

Technical hurdles cited by companies include a lack of a unified and accessible data foundation, inability to trust and govern agents, and the cost and complexity of integration. Organizational challenges include workforce readiness and underprepared business processes, according to Deloitte.

Given AI's rapid pace, CIOs are in a constant state of evolution, Widener said. AI strategies should be developed in parallel with the changing technology landscape, she added.

“You have the technical components, the governance components, the data components, and the human components all evolving at the same time,” Widener said. “That is what contributes to the difficulty in the transformation.”

Agentic AI is delivering some positive impact for most companies, according to a recent Accenture report, but few organizations report sustained business value—impact that can be presented to a company's board—from their AI investments.

CIOs aiming to deepen their agentic AI use meaningfully should understand that this is a fundamentally different type of technology compared to the linear, generative AI models most companies have deployed over the past few years, Widener said.

With automated models, a task or query follows the same steps each time, but agentic models operate less predictably. It becomes the user's responsibility to validate outcomes—a working style that differs significantly from what most are accustomed to, Widener explained.

“We're entering a different time where the technology and the agentic solution has the ability to think and take those outcomes and arrive at the best path of travel to get there without being told all the steps,” Widener said.