Series context. This is Part 2 of Beyond Automation, a multi-part examination of the risks that emerge when organizations remove human judgment from AI-enabled decision systems. Building on Part 1’s analysis of over-automation and silent failure modes, this installment examines how these failures manifest in enterprise risk management. [1]
The Illusion of Precision in AI-Driven Risk Programs
Risk management is among the most aggressively automated enterprise functions. AI-driven platforms now score third-party risk, prioritize fraud alerts, manage AML and KYC screening, and populate enterprise risk registers at machine speed. These systems promise consistency, efficiency, and objectivity in environments that have historically relied on human judgment.
The problem is not automation itself. The problem arises when AI-generated outputs are treated as decisions rather than inputs.












































































