This paper applies the AI Authority Maturity Model (AAMM), introduced in Huseby (2025), to four documented enterprise AI deployments across financial services, logistics, and consumer goods: BlackRock’s Aladdin Copilot, JPMorgan Chase’s LLM Suite and agentic systems, Maersk’s NavAssist vessel routing platform and Pactum supplier negotiation system, and Unilever’s Project Sky agentic supply chain. Through structured case analysis, the paper demonstrates the AAMM’s utility as an analytical instrument and identifies a consistent cross-industry pattern: enterprise AI deployments are advancing from Level 1 toward Level 2–3 faster than governance frameworks are keeping pace. The paper introduces the concept of the “governance premium” — the measurable performance advantage associated with AI-savvy board oversight, quantified by MIT CISR (2025) at 10.9 percentage points in return on equity — and operationalizes the central argument of the first paper in this series: that AI governance capability is a form of strategic infrastructure that generates measurable competitive advantage. The paper also proposes two extensions to the AAMM: function-specific rather than organization-wide classification, and a governance maturity dimension that measures oversight architecture against deployment level. Keywords: AI Authority Maturity Model, AAMM, enterprise AI deployment, AI governance, agentic AI, bounded autonomy, governance premium, supply chain AI, financial services AI, corporate governance
Alexander Huseby (Thu,) studied this question.