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Regulatory map

AI governance regulatory readiness map

Use this map to translate major AI governance rules, standards, and agency expectations into practical vendor workflow requirements.

What to map first

Start with the use cases in scope, the applicable rule or framework, the required evidence, the decision owner, and the workflow that proves review happened before deployment.

Common buyer workflows

Most teams need inventory, risk tiering, impact assessment, policy mapping, human oversight, issue tracking, evidence storage, and reporting that can be reused across EU, U.S., and internal governance requirements.

VerifyWise

Strong fit for framework-led teams that want EU AI Act, ISO 42001, and NIST AI RMF mapping to drive the operating model.

Credo AI

Strong enterprise fit when regulatory readiness must connect to policy enforcement, approval workflows, and auditable artifacts.

Saidot

Good EU-oriented fit for organizations translating AI Act accountability into inventories, controls, and review workflows.

Modulos

Useful where cross-framework control mapping and evidence reuse are the core regulatory-readiness problem.

OneTrust

Good fit for enterprises that want AI governance mapped into a broader privacy, risk, and trust operating stack.

IBM watsonx.governance

Enterprise option for lifecycle governance, compliance management, and reporting across large model and AI estates.

Trustible

Strong fit for operational governance teams that need inventories, assessments, controls, and evidence tied to named obligations.

Holistic AI

Good fit when regulatory readiness also requires assurance depth, testing, and independent risk review around higher-impact systems.

Editorial takeaway

Do not buy against a regulation name alone. Buy against the workflows the regulation creates: intake, classification, assessment, oversight, evidence, monitoring, and reporting.