How do you govern enterprise AI?
Workable AI governance has four parts: an inventory of every AI use case, a risk tier per use case, evaluation gates that a release must pass, and monitored controls in production. Map those to NIST AI RMF and ISO/IEC 42001 so audit and procurement recognise the artefacts, and keep the gates automated so governance speeds delivery instead of blocking it.
Last reviewed 2026-08-31 · pronix.ai — specialized AI & CX systems integrator
What the numbers show
First-party figures from Pronix research. Each links to the report or playbook that publishes it.
- Board-level
- AI governance moved from committee slide to board obligation in 2026 as the EU AI Act, NIST AI RMF and ISO/IEC 42001 converged on a common baseline.Source: AI Governance & Risk Benchmarks 2026 →
- Faster, not slower
- Healthcare institutions that mapped their AI portfolio to federal and state AI frameworks early are moving faster in 2026, not slower.Source: Healthcare AI Adoption Benchmarks 2026 →
- 24%
- Engineering and product talent absorbs about 24% of enterprise AI spend — more than the models themselves.Source: State of Agentic AI in the Enterprise 2026 →
External references
- NIST — AI Risk Management Framework (AI RMF 1.0) (2023)The govern / map / measure / manage structure Pronix uses to organise AI controls.
- ISO/IEC — ISO/IEC 42001 — AI management systems (2023)The certifiable management-system standard enterprise procurement increasingly asks about.
- European Union — Regulation (EU) 2024/1689 (AI Act) (2024)Defines the risk tiers and transparency duties that shape scope for EU-facing deployments.
- OWASP — Top 10 for LLM Applications (2025)The threat list our prompt-injection, output-handling and tool-permission guardrails map to.
How we know
Inventory first
You cannot tier or monitor what is not listed. The inventory captures owner, data classes, model, integrations and escalation path per use case.
Gates are automated tests
Evaluation suites, red-team prompts and policy checks run in the release pipeline, so the same evidence exists for every deployment.
Monitoring is the control that lasts
Drift, refusal rates, escalation quality and cost are tracked continuously; governance without production telemetry is documentation only.
Related questions
- Does the EU AI Act apply to us?
- It applies to AI placed on the EU market or affecting people in the EU, with obligations scaled by risk tier — scope it per use case, not per company.
- Do we need ISO/IEC 42001 certification?
- Not to start. Building the management-system artefacts early makes certification an audit rather than a programme if procurement later requires it.
- Who owns AI governance?
- A named accountable owner per use case, supported by a cross-functional review board — risk, security, legal and the delivery team.