Agentic AI Will Break the Human-in-the-Loop Model
Techstrong.ai, Thursday, October 29th, 2026
Techstrong.ai argues agentic AI makes blanket human-in-the-loop review obsolete and proposes risk-calibrated governance of agent reasoning.
Maureen Doyle-Spare argues that reviewing every agentic AI decision either slows systems to human speed or turns review into a formality that creates false confidence.
She says output-based guardrails miss the core risk, which arises at the reasoning layer where an agent decides what a regulated term means.
Her alternative is risk-based governance in which institutions approve versioned Reasoning Baselines, a Semantic Deviation Index measures how far an agent's interpretation diverges, and a Deterministic Gate holds divergent decisions for human review.
High-consequence decisions such as sanctions dispositions default to mandatory holds, concentrating human authority on targeted adjudication.