For leadership, risk, legal, and IT teams that need to approve AI without blocking it.
We inventory the AI in use, sort each system into a risk tier, and write the rules for who may use it, on what data, with whose approval. Then we enforce them in Microsoft Purview and Azure Policy, so useful AI can go ahead safely.
The AI governance review shows what you already run, the governance framework decides what oversight each system needs, and enforcement and monitoring keep it that way.
Estimated 4–6 weeks
Each AI workload documented and assessed against responsible AI principles, with an impact assessment for the priority use cases.
AI is already in use and nobody can list what each workload does, or with what data.
Risk tiers and lifecycle gates that scale controls with impact, and written policies and standards your people can follow, reviewed by your counsel.
One approval process for all AI, so low-risk work waits and high-risk work slips through, and no written rules behind it.
Rules enforced automatically where they can be, and reviewed on a schedule where they can’t.
The policy exists on paper and nothing checks whether it is followed.
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The HR department at a major New York City university knew AI could help but had no shared way to decide where.
Not if the controls match the risk. Lower-risk, reversible uses get standard controls and an owner review. Higher-risk uses get cross-functional review and human oversight. That keeps the heavy process for the cases that need it.
No. We run a gap assessment against ISO/IEC 42001 and build the implementation roadmap. Certification is done by an accredited certification body.
The NIST AI Risk Management Framework and its Generative AI Profile, ISO/IEC 42001 and 42005, and Microsoft Cloud Adoption Framework guidance for governing AI. We map them onto the risk, security, and audit structures you already have rather than building a separate bureaucracy.
No. We design governance requirements and controls and flag where regulation applies. Legal interpretation stays with your counsel.
It depends mostly on how much AI is already in use. The AI governance review above lists its estimated length, and policies and controls then roll out in waves, highest-priority AI first. Keeping the agent inventory current and monitoring agents once they are live is part of Azure AI Platform and Operations.
Two people: a named business owner for its outcome and a named technical owner for its operation. Both go in an agent inventory with the risk tier, data sources, and an emergency contact who can disable the agent. The risk tiers and approval gates come from the governance framework above.
Mostly how much AI is already in use, whether an inventory exists, and whether you need ISO/IEC 42001 alignment or a lighter set of rules. How many systems sit in the higher risk tiers, and who enforces the rules, decide the rest.
It starts with a 60-minute call. If we need more to scope it, a short questionnaire follows. Then a written proposal and statement of work. Once you approve, we begin with the Assess phase.
