The maturity gap: Leaders operationalize agents differently

AI adoption has rapidly expanded across enterprises, with 99% of organizations utilizing AI in some form, and a significant impact is evident as 80% report moderate or significant ROI from AI implementations. The report highlights a maturity gap, with leading-edge companies achieving greater returns by using AI for innovative purposes rather than just efficiency improvements. These advanced organizations are not only automating tasks but are also engaging in entirely new types of work, seeing broader impacts on productivity, workflow innovation, and new revenue streams. A distinct operational model for AI is emerging, with a "managed digital workforce" approach, where AI agents are integrated and managed like employees, supported by a structured AI leadership role in 95% of organizations. A hybrid economic model for AI costs, where IT manages infrastructure while business units cover application-level expenses, is becoming prevalent, facilitating a convergence between IT and business objectives. Despite structured management and incentives for AI use, the most successful AI initiatives often arise from collaboration across business units and IT functions, rather than solely from centralized AI or data-science teams.

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