Acceptable use cases
Boards and executives need a clear view of which agent use cases are acceptable, conditional, restricted, or outside appetite.
Board & Executive Oversight
AI governance should not only reduce risk. It should prove value.
Scaled Agents™ helps organizations connect every registered AI worker to ownership, oversight, Passport evidence, risk exposure, policy exceptions, incidents, lifecycle posture, and measurable business value.
Board Oversight Dashboard
A portfolio view of governed AI agents.
Board and executive views should summarize which AI workers exist, why they exist, who owns them, what risk they create, what evidence exists, and what requires attention before scale.
These views are reporting and readiness aids. They do not approve deployment, certify compliance, or replace management, legal, audit, security, privacy, or compliance review.
Board-visible indicators
- Total registered agents and active Passports
- High-risk or sensitive agents
- Agents pending review or missing evidence
- Human approval coverage and open policy exceptions
- Material incidents and unresolved remediation
- Regulatory readiness posture and evidence completeness
AI Risk Appetite
Define what agents may do before authority expands.
Human-owned decisions
Risk appetite should identify actions that always require human approval, including consequential, external, regulated, financial, legal, or customer-impacting activity.
Pause and retirement triggers
Executives should know when an agent must be paused, reviewed, redesigned, restricted, or retired because scope, evidence, ownership, risk, or incidents changed.
Agent Accountability
Every durable AI worker needs named accountability.
| Expectation | Board-ready question | Scaled Agents record |
|---|---|---|
| Business and technical ownership | Who owns the outcome, operation, escalation, and retirement path? | Agent Registry and Passport owner fields |
| Purpose and scope | What is the agent allowed to do, and what is explicitly prohibited? | Passport purpose binding, scope, permissions, and prohibited actions |
| Traceable autonomy | Which actions are drafted, recommended, approved, executed, blocked, or escalated? | Toll Gates, Runtime Permits, Action Broker decisions, Stamps, and Evidence Records |
| Human review | Where is human approval required, and what evidence supports the decision? | Human Review items, approval state, evidence references, and lifecycle events |
Regulatory Readiness
Framework-aware evidence without certification claims.
Scaled Agents can be mapped to selected governance expectations, including NIST AI RMF Govern, Map, Measure, and Manage concepts; ISO/IEC 42001 AI management system concepts; EU AI Act readiness themes; and internal audit or compliance preparation.
NIST AI RMF
Organize ownership, mapping, risk measurement preparation, monitoring expectations, and management review evidence.
ISO/IEC 42001
Support AI management system readiness through inventory, roles, lifecycle records, controls, review evidence, and improvement loops.
EU AI Act readiness
Support preparation for risk awareness, transparency, human oversight, documentation, incident review, and lifecycle governance. August 2, 2026 is a major applicability milestone for many EU AI Act obligations.
Boundary: Scaled Agents supports readiness, evidence organization, and governance preparation. It does not certify compliance, provide legal advice, issue audit opinions, or guarantee regulatory outcomes.
Evidence & Passport Reporting
Board reporting should come from the same governed record.
Passport, Registry, Toll Gate, Human Review, Stamp, incident, exception, and evidence records should support board reporting without creating a second approval system.
A board-ready export should summarize inventory, risk distribution, high-risk agents, open exceptions, pending approvals, incidents, evidence gaps, value posture, and recommended management decisions.
Report pack contents
- AI agent inventory and Passport coverage
- Top risks, high-exposure agents, and sensitive-data workflows
- Open findings, policy exceptions, and material incidents
- Evidence completeness and renewal status
- Recommended scale, govern, monitor, redesign, or retire decisions
Governance Economics
Measure the business value of governing AI agents.
AI governance should connect risk reduction and evidence generation to operational value. Board and executive reporting should use estimated, modeled, or risk-adjusted language unless financial inputs have been validated by the organization.
Value realization
Track expected hours saved, cost reduced, revenue protected, customer impact, audit effort reduced, and risk reduced.
Risk exposure
Show exposure by agent, business unit, data classification, regulatory impact, tool or connector, oversight dependency, and critical workflow dependency.
Investment portfolio
Classify agents into scale, govern and grow, monitor, redesign, or retire paths based on value, risk, evidence, control coverage, and confidence.