Dimension 01
Weight 18
Trust & Safety
Guardrails, red teaming, misuse detection and the measurable prevention of unsafe actions in production.
The Methodology v2.0 published reference for AI agent certification. Seven dimensions. Weighted scoring. Independent assessment. One registry. The Digital Omnibus proposal does not affect this framework. Operators with documented certification are in a stronger position regardless of how the EU AI Act timeline resolves, because certification evidence underwrites both regulatory readiness and insurance underwriting requirements independent of any activation date.
The published reference for AI agent certification. Seven dimensions. Five tiers. Standards crosswalk. Assessment process. The document law firms, insurers, and regulators cite.
Europe is deploying autonomous agents into production faster than any governance framework can track. Agent Certified exists so that insurers, regulators, boards and counterparties have a common way to read whether an agent is safe to rely on.
A structured benchmark that produces a defensible position on governance, oversight, technical controls and operating readiness before an incident, not after.
A consistent signal of risk posture across portfolios. Certification maps to the governance, transparency and human oversight obligations emerging under the EU AI Act.
A clear artefact directors can reference in risk committees, vendor reviews and annual reports without having to construct one from scratch.
Every certified agent is evaluated against seven dimensions. Each dimension carries a weight reflecting its importance to operational safety and regulatory exposure. Together they total one hundred points.
Guardrails, red teaming, misuse detection and the measurable prevention of unsafe actions in production.
How the agent sources, verifies and keeps fresh the data it reasons over, including provenance and lineage.
Who can invoke the agent, under what authority, and how downstream actions are bounded.
Reliability of the agent as a product surface: uptime, regression discipline, evaluation coverage and versioning.
Board oversight, documented policies, risk registers, role accountability and audit trails at the operating level.
How responsibly the agent sits inside existing systems of record, identity, approval and escalation.
The explicit boundary between autonomous action and human confirmation, including revocation, rollback and hard stops. The single most important constraint on operational risk.
The weighted score across all seven dimensions places the agent into one of five recognised tiers. The band is the signal that counterparties read.
Baseline acknowledged. Governance, oversight and technical evidence are not yet sufficient for a certification call.
Operator has initiated formal controls. Recognised as an active candidate, not yet certified.
The agent meets the operating floor. Counterparties may rely on the mark for standard commercial use.
Materially above floor. Suitable for higher exposure deployments including regulated sectors.
Exemplar. Used as a reference profile for insurer underwriting models and for sector standards work.
Long form writing on certification, conformity assessment, and the standards landscape that Agent Certified connects to. Updated as the methodology evolves.
Intake, evidence gathering across seven dimensions, scoring, tier outcome, the final report, and how the result feeds an insurer underwriting file. Practical orientation for a risk lead preparing for assessment.
Read analysis → 14 June 2026 · MethodologyThe canonical guide to the Agent Certified methodology: seven dimensions, five tiers, 100-point scoring, ISO 42001 and NIST AI RMF crosswalks, and how certification feeds insurance underwriting.
Read analysis → 14 June 2026 · ProcurementEnterprise procurement teams in financial services, healthcare, and public sector are requiring AI governance certification from AI vendors. What certification frameworks they use and how to prepare.
Read analysis → 13 June 2026 · MethodologyA clause-by-clause crosswalk mapping ISO/IEC 42001 Annex A controls to NIST AI RMF functions and AIUC-1 domains, with a real control-mapping table operators can use to reuse evidence across frameworks.
Read analysis → 12 June 2026 · MethodologyHow long does AI agent certification actually take? A realistic timeline for operators facing August 2026 EU AI Act deadlines, with the critical path from gap analysis to certification issuance.
Read analysis → 10 June 2026 · CertificationWhat enterprises need to assemble before a formal AI agent certification assessment. The seven documentation categories, common gaps, and how to close them before the assessment begins.
Read analysis → 4 June 2026 · MethodologyHow Agent Certified evaluates security and resilience in AI agents: adversarial robustness, cyberattack resistance, failsafe behaviour, and the Article 15 EU AI Act framework.
Read analysis → 2 June 2026 · MethodologyEU AI Act Article 14 mandates human oversight of high-risk AI systems. How does certification assess whether human oversight obligations are genuinely met? A guide to the evidence hierarchy.
Read analysis → 1 June 2026 · MethodologyThe Data Governance dimension of Agent Certified evaluates training data quality, bias testing, and data provenance against EU AI Act Article 10 requirements.
Read analysis → 29 May 2026 · MethodologyThe performance and reliability dimension of AI agent certification assesses accuracy baselines, drift detection, robustness testing, and failure mode documentation against EU AI Act Article 15.
Read analysis → 27 May 2026 · MethodologyThe trust and transparency dimension of AI agent certification maps explainability, human oversight, and transparency obligations directly to EU AI Act Articles 13, 14, and 50.
Read analysis → 22 May 2026 · MethodologyAgent Certified's Governance dimension: what it evaluates, how it is scored, and why governance documentation is the key to AI insurance eligibility in Europe.
Read analysis → 13 May 2026 · MethodologyHow to certify AI agents built on GPAI foundation models: assessing inherited risks, supply-chain transparency, and the seven certification dimensions for model-dependent systems.
Read analysis → 11 May 2026 · MethodologyA deep dive into the Autonomy Envelope dimension of AI agent certification: how to specify, test, and document the boundaries of autonomous action for EU AI Act Article 14 compliance.
Read analysis →The framework is built on existing, recognised instruments rather than in parallel to them. Every dimension traces back to at least one primary reference.
| Reference | Issuer | Relevance |
|---|---|---|
| ISO/IEC 42001:2023 | International Organization for Standardization | AI management system requirements. Informs Governance and Product Maturity dimensions. |
| NIST AI Risk Management Framework | US National Institute of Standards and Technology | Risk function model. Informs Trust & Safety and Context Integrity dimensions. |
| EU AI Act, Articles 9, 10, 14, 15 | European Parliament and Council | Risk management, data governance, human oversight and accuracy. Maps directly to dimension scoring. |
| EU AI Act, Article 26 | European Parliament and Council | Deployer obligations. Informs Distribution Control and Autonomy Envelope dimensions. |
| EIOPA supervisory statements on AI in insurance | European Insurance and Occupational Pensions Authority | Sector alignment for insurer reliance on the framework. |
Assessments are scheduled in quarterly cohorts. Q3 2026 slots are open to European enterprises and scale ups operating agents in production environments. Submit a request to receive an intake briefing.
The Agent Certified framework is calibrated to Article 26 of the EU AI Act, the revised Product Liability Directive, and the supervisory expectations of EIOPA and the AI Office. Agent Liability EU is the operator desk on those instruments.