The Digital Transformation Playbook · 2026-07-13 · 14 min
More than 40% of agentic AI projects may be cancelled by 2027, with cost, unclear value, and weak controls driving many failures. The central challenge lies in turning promising demonstrations into accountable, scalable operating models. This episode explores how organisations can grant autonomy progressively while protecting performance, economics, and governance. TLDR / At a Glance • Organisational readiness over model capability • Demo-to-operating-model gap • Authority, access, and accountability • Five-stage Authority Ladder • Evidence-based increases in autonomy • Proportionate human oversight A flashy agentic AI demo can make almost any workflow look solved, right up until it hits real data, real users, real risk, and real cost. We dig into Gartner’s headline prediction that more than 40% of agentic AI projects may be cancelled by 2027 and explain why that number is less interesting than the mechanisms behind it: escalating spend, fuzzy business value, and controls that never kept pace with the authority being granted. Agentic AI succeeds when leaders choose suitable workflows, establish clear ownership, and expand authority only when performance and controls justify it.
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