Genpact report finds agentic AI adoption hindered by organizational readiness, not technology
The AMW Read
Incremental update: adds survey evidence to known barrier pattern for agentic AI deployment; segment-level significance as it quantifies organizational readiness gap.
Genpact report finds agentic AI adoption hindered by organizational readiness, not technology
Genpact, the global professional services firm spun off from GE, published a report on April 28, 2026, based on a survey of 545 executives and interviews across 11 industries. The report finds that 92% of respondents believe agentic AI will fundamentally change how work gets done, yet only 22% feel confident operating it at scale. The top barriers are not technical but organizational: unclear accountability (31%), impact on people (36%), and inadequate business process redesign (33%). Key risks identified include lack of governance for autonomous decision-making, overreliance on legacy KPIs, and insufficient data confidence.
Why it matters: This report underscores a recurring pattern in the AI industry substrate: the gap between technology capability and enterprise deployment readiness. While foundation model labs and agent platforms race to push the frontier, enterprises are stuck on non-technical friction — accountability design, performance metrics, and human role redefinition. The finding aligns with the "organizational readiness bottleneck" pattern seen in prior enterprise AI rollouts, where the slowest step is not model accuracy but change management and process reengineering. It also updates the open debate on agentic AI's real-world timeline: the technology may be ready, but the enterprise context is not.
Expert take: Genpact's conclusion that agentic AI's full value will not be realized without deliberate organizational redesign — covering accountability, measurement, and human placement — is grounded in its consulting experience. The four leadership decisions it prescribes (clear responsibility, measurement evolution, role redesign, process rearchitecture) mirror the structural forces that have historically determined the success of large-scale automation programs. For AI market watchers, this signals that the next phase of competitive advantage may shift from model capability to organizational change management capability.