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AI Governance Consulting
The AI Risk Management Framework Consulting Partner for the Teams Who Build and the Teams Who Oversee
We design and implement governance frameworks that your engineers, your general counsel, and your board can all stand behind. Engagements begin at $20,000, and you will know exactly what drives the number before we ever send a proposal.
Your organization is already running AI in decisions that matter: admissions and enrollment, research operations, product features, data pipelines your customers never see. What most organizations are not running is the infrastructure that governs any of it. No review board, no accountability map, no defined process for the moment a model does something it should not.
Legal and compliance know the exposure is real. The EU AI Act, NIST AI RMF adoption, and a growing patchwork of state legislation are turning informal AI practices into board level questions. Meanwhile the teams building AI and the teams responsible for overseeing it are working in separate rooms with separate vocabularies.
Closing that gap is not a policy document. It is an operating structure, and it can be built deliberately.
An AI risk management framework your organization actually operates
We build the working structure with you: a governance gap assessment that maps every AI system in your portfolio, a framework aligned to the NIST AI RMF functions and ISO/IEC 42001, an AI review board with a charter fitted to how your organization really makes decisions, and an accountability model that gives builders and gatekeepers a shared process instead of a standoff.
The result is not a binder on a shelf. It is faster, defensible AI decisions: deployments that clear review because the review process exists, questions from regulators and auditors answered from documentation instead of scramble, and a board that hears governance described as infrastructure rather than exposure.
Complete AI system inventory and risk map
NIST AI RMF and ISO 42001 alignment
Review board charter, membership, cadence
Accountability model bridging builders and gatekeepers
What an engagement costs and why
Engagements begin at $20,000. Three variables set the number, and we walk through all three in the scoping call.
Portfolio
How many AI systems, and at what stage
Governing two production models is a different job than governing fifteen systems spread across pilots, development, and deployment. The size and maturity of your portfolio is the largest driver of scope.
Industry
Whether your industry is regulated
Organizations in regulated environments carry heavier documentation, audit, and oversight requirements. The framework has to meet them, and the engagement scopes accordingly.
Timeline
How fast you need it
Standard engagements run eight to sixteen weeks depending on complexity. Compressed timelines are possible and carry a priority engagement premium.
No rate card, no mystery. A 30 minute conversation about your portfolio is enough for us to quote precisely.
How the work runs
1
Assess the governance gap
Weeks one to four map your AI landscape, catalog every system, and identify exactly where governance infrastructure is missing.
2
Design the framework and review board
Weeks five to twelve build the framework, the review board charter, and the accountability structures with your teams in the room.
3
Implement and hand off
The closing weeks operationalize the structure, train the people who will run it, and leave your organization governing its own AI.
Organizations that govern AI well do not slow down. They build faster.
Our founder brings more than ten years of enterprise AI program leadership across Fortune 10 organizations, including serving as vice chair of a Fortune 500 AI review board and AI governance committee. This engagement model is built from structures that have actually operated at that scale.
AIML Governance contributed to an AI product governance engagement spanning Harvard Business School and Harvard Business Publishing, work that covered publishing data, student lifecycle data, alumni networks, and job placement analytics.
Our healthcare depth is in data and analytics: our founder led enterprise AI program work at McKesson across pharmacy sales data and medical device output governance, the exact terrain where inference risk and device telemetry ethics live.
Common questions
Our engagements begin at $20,000. The final number depends on how many AI systems you operate and at what stage, whether your industry is regulated, and your timeline, with compressed timelines carrying a priority premium. We quote after a 30 minute scoping conversation rather than publishing a rate card, because a two model portfolio and a fifteen system portfolio are different engagements.
The gap assessment runs two to four weeks. Full framework design and implementation runs eight to sixteen weeks depending on organizational complexity. You will have a concrete timeline before the engagement begins, and it will be one your teams helped shape.
They answer different questions and work well together. NIST AI RMF defines the risk management practice: govern, map, measure, manage. ISO/IEC 42001 defines a certifiable management system around that practice. We design frameworks aligned to both, so if certification becomes a requirement later, the foundation is already in place.
Then the engagement is smaller, and that is reflected in the price. Small portfolios are the best time to build governance, because the framework scales with you instead of being retrofitted after your tenth deployment. Our Governance Fundamentals tier exists for exactly this situation.
Know exactly what your framework will take before you commit to anything
A 30 minute scoping call covers your portfolio, your regulatory context, and your timeline, and ends with a precise quote. No deck, no pressure, no follow up sequence you did not ask for.