Most Enterprise Agentic Projects Are Doomed, Here's Why — Jess Grogan-Avignon & Jack Wang, Accenture
May 28, 2026 · 20:35
Jess Grogan-Avignon and Jack Wang, Accenture, argue that most enterprise agentic projects fail not because of bad code but because organizational scaffolding designed for human pace chokes machine-speed AI delivery. They built an agentic application in two weeks, then spent twelve months aligning infrastructure, security, AI gateway, data governance, and application teams before it shipped—a pattern they say will worsen as GitHub's 275 million weekly commits flood approval infrastructure built for humans. They name five predictive tensions: human approval chains must become executable code, not longer meetings; finance should back a portfolio of AI bets like a VC, not demand committed returns from each project; delivery should run on hypothesis-driven loops building statistical confidence, not fixed milestones; trust is built through progressive autonomy—shadow, advisory, controlled autonomy—gated by outcome evidence, not plan completion; and the real moat is living memory from real customer signals, not static CRM or ERP data. Their prescription: bet like a VC, upgrade governance for machine speed, and engineer for trust with feedback loops from day one.
