What Evidence Must Exist Before You Increase an Agent’s Authority?

An AI agent should not receive more authority just because the pilot was impressive.

The more an agent can access data, select tools, update systems, communicate externally, approve transactions, or initiate actions, the greater the potential business impact. Accuracy matters, but it is only part of the decision. Leaders must also know whether the agent operates within defined boundaries, produces reliable outcomes, protects company data, and can be stopped when something goes wrong.

This AI maturity scorecard shows how organizations can evaluate evidence before increasing an AI agent’s authority. It connects NIST AI RMF’s Govern, Map, Measure, and Manage functions with the ISO/IEC 42001 Plan-Do-Check-Act cycle.

The central question is simple: What evidence proves this agent is ready for more authority?

A Lightweight AI Authority Scorecard

Score each item from 0 to 3:

• 0 — No evidence

• 1 — Informal or incomplete

• 2 — Documented and tested

• 3 — Proven through monitored operation

Function	Evidence Required
Govern	A named business owner and technical owner are accountable for the agent.
	Authority limits, prohibited actions, approval requirements, and escalation paths are documented.
	Security, privacy, regulatory, vendor, and data-residency requirements have been reviewed.
Map	The complete workflow—including systems, tools, data, users, and downstream effects—is documented.
	Failure scenarios identify who could be harmed, what data could be exposed, and what business processes could be disrupted.
	Agent permissions are limited to what is necessary for the approved use case.
Measure	Business value is measured against an approved baseline—not demonstration performance.
	Accuracy, bias, security, privacy, reliability, and unauthorized-action tests meet defined thresholds.
	Testing includes unusual inputs, tool failures, adversarial behavior, and attempts to exceed authority.
Manage	Production monitoring can detect abnormal actions, declining performance, and control failures.
	Logs provide a complete record of prompts, decisions, tool use, approvals, and system changes.
	Human intervention, rollback, incident response, and recovery procedures have been tested.

The maximum score is 36, but the number alone should never authorize expansion. A high score cannot compensate for a missing kill switch, excessive permissions, weak audit records, or an unresolved high-impact risk.

Turning the Score Into an Authority Decision

Score	Appropriate Authority
0–12	Analysis and experimentation only; no production actions
13–23	Draft recommendations for human review
24–30	Execute limited, reversible actions with approval
31–36	Operate within tightly defined boundaries with continuous monitoring

Some actions should still require human approval regardless of score. These may include financial commitments, employment decisions, legal representations, access changes, safety-related actions, or releasing sensitive information.

The scorecard is a decision aid—not a substitute for judgment.

This is a practical alignment, not a claim that the NIST functions and ISO clauses are identical. NIST’s AI RMF organizes AI risk work around Govern, Map, Measure, and Manage, while ISO/IEC 42001 provides a management system for establishing responsibilities, operating controls, evaluating performance, and improving them over time. NIST AI RMF Core ISO/IEC 42001 overview

For more discussion contact DanRuggles@proton.me