310 West 14th North Street, NY
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AI GOVERNANCE SERVICES
Governance infrastructure that makes AI safe to scale
We design and implement the frameworks, review boards, and accountability structures that connect your AI teams with the people responsible for what those systems produce. Strategic governance built with your organization, not bolted on from the outside.
AI is already embedded in enterprise operations. Clinical decision support, research workflows, admissions screening, financial underwriting, product recommendations. But in most organizations, the governance infrastructure around those deployments does not exist. No formal review process. No defined accountability for model outputs. No institutional structure connecting the teams that build AI with the teams responsible for what it does.
The result is exposure on every front. Regulatory exposure as the EU AI Act moves into enforcement and NIST AI RMF adoption becomes the baseline expectation. Reputational exposure when an ungoverned model produces a biased output in a high-stakes decision. Operational exposure when legal, compliance, and risk teams have no process for evaluating AI systems before they go live.
The organizations closing this gap are not waiting for a crisis to force the conversation. They are building governance infrastructure now, while the strategic window is still open.
AI governance services designed for how enterprise organizations actually work
AIML Governance LLC is a boutique consulting firm that works at the intersection of AI build teams and legal, compliance, and risk functions. We do not sell software platforms or compliance checklists. We design and implement the governance infrastructure your organization needs to deploy AI responsibly at scale.
Every engagement is tailored to your regulatory landscape, organizational structure, and AI maturity. The frameworks we build are operational from day one because your teams help design them, your stakeholders have a seat at the table, and the processes integrate with the way your organization already works.
AI Governance Framework Design and Implementation
NIST AI RMF Alignment and Gap Assessment
AI Review Board Structure and Charter
Cross-functional Accountability Frameworks
Our services
AI Governance Gap Assessment
Every engagement begins here. We map your current AI landscape, catalog the models and systems in production, identify where governance infrastructure is missing, and benchmark your maturity against NIST AI RMF. The assessment delivers a prioritized roadmap that tells your leadership team exactly where the risk exposure is and what to address first.
Deliverables
- Comprehensive AI inventory and risk exposure map
- NIST AI RMF maturity benchmark
- Prioritized remediation roadmap
- Executive summary for leadership and board reporting
AI Governance Framework Design and Implementation
We design the institutional structure that makes governance operational. This includes defining roles and responsibilities, building decision-making processes for AI deployment, creating risk classification criteria, and establishing the workflows that connect AI development teams with legal, compliance, and risk functions. We implement alongside your teams so the framework is owned internally from day one.
Deliverables
- Governance framework documentation and operating procedures
- AI risk classification and tiering model
- Cross-functional workflow design and RACI matrix
- Implementation playbook and team training
NIST AI RMF Alignment
For organizations targeting formal alignment with the NIST AI Risk Management Framework, we provide end-to-end implementation support. We map your existing practices to the four core functions (Govern, Map, Measure, Manage), identify gaps, and build the processes, documentation, and monitoring structures needed to demonstrate alignment to auditors, regulators, and board stakeholders.
Deliverables
- NIST AI RMF function-by-function gap analysis
- Governance process design aligned to Govern, Map, Measure, Manage
- Audit-ready documentation and evidence framework
- Ongoing monitoring and continuous improvement process
AI Review Board Design
We design and stand up the institutional body that governs AI decisions. This includes defining the board charter, membership criteria, meeting cadence, escalation paths, and the decision framework the board uses to evaluate AI deployments. The review board becomes the organizational center of gravity for AI governance, giving leadership a clear, accountable structure for oversight.
Deliverables
- Board charter with scope, authority, and decision criteria
- Membership model and role definitions
- AI use case intake and evaluation process
- Escalation and exception handling procedures
Cross-functional Accountability Framework
The most common governance failure is not a missing policy. It is a missing connection between the people who build AI and the people who are accountable for what it does. We design the accountability structures that close this gap: shared ownership models, defined handoff points, joint risk review processes, and the communication frameworks that make governance a living part of how your teams operate.
Deliverables
- Accountability mapping across AI lifecycle stages
- Shared ownership model with defined handoff points
- Joint risk review process for AI and oversight teams
- Communication and reporting framework
How an engagement works
1
Assess
We begin with a governance gap assessment that maps your AI landscape, catalogs risk exposure, and benchmarks your governance maturity against NIST AI RMF. This step produces the roadmap that drives every decision that follows.
2
Design
We design the governance framework tailored to your organization: review board structure, accountability roles, risk management processes, and the cross-functional workflows that connect your AI and oversight teams.
3
Implement
We build alongside your teams, not from the outside. Governance playbooks, operating procedures, and training are delivered so your organization owns the framework from day one.
4
Sustain
We establish the monitoring, reporting, and continuous improvement processes that keep governance current as regulations evolve, models change, and your AI portfolio grows.
Built on a decade of enterprise AI leadership
We bring deep, hands-on experience implementing governance at the world’s most sophisticated organizations. Our founder has spent the last decade solving these problems at scale: building accountability frameworks for institutional AI deployment, structuring governance across regulated industries, and operating AI programs at the velocity and complexity of enterprise organizations.
Harvard
Contributed to AI product governance at Harvard Business School and Harvard Business Publishing as a subcontractor, building accountability frameworks for responsible AI deployment at institutional scale.
McKesson
Led enterprise AI program management at McKesson, structuring governance across complex, regulated healthcare operations.
Meta
Brought AI governance and program leadership to Meta, operating at the scale and velocity of one of the world’s largest AI organizations.
Carrier
Served as Vice Chair of the AI Review Board and Vice Chair of the AI Governance Committee at Carrier, while leading the Fortune 500 company’s AI Center of Excellence as Program Manager.
IAPP Certified AI Governance Professional. Practitioner expertise backed by institutional certification.
Common questions
What is AI governance and why does my organization need it?
AI governance is the set of frameworks, processes, and institutional structures that define how your organization develops, deploys, monitors, and is accountable for AI systems. Without governance infrastructure, AI decisions happen without oversight, risk assessment, or clear accountability. As regulatory requirements accelerate (EU AI Act, NIST AI RMF, state legislation), organizations without governance face compliance gaps, liability exposure, and reputational risk.
How is AIML Governance different from a compliance firm or an AI software platform?
We are not a law firm, an audit firm, or a software vendor. We are a strategic implementation partner. Compliance firms tell you what the rules are. Software platforms give you tools to manage models. We build the organizational infrastructure that connects your AI teams with your legal, compliance, and risk functions so governance actually works in practice. We design and implement with your teams, then hand you the keys.
How long does a governance engagement take?
A governance gap assessment typically takes two to four weeks. A full framework design and implementation engagement ranges from eight to sixteen weeks depending on organizational complexity, the number of AI systems in scope, and how many stakeholder groups need to be involved. We scope every engagement individually and provide a clear timeline before work begins.
Do you work with organizations that already have some governance in place?
Yes. Many organizations have informal governance practices, partial frameworks, or early-stage review processes. We assess what exists, identify the gaps, and build on your foundation rather than starting from scratch. The goal is to strengthen and formalize what is working and fill the structural gaps that create risk.
What does a governance gap assessment actually deliver?
The assessment delivers a comprehensive AI inventory, a risk exposure map tied to your specific regulatory landscape, a NIST AI RMF maturity benchmark, and a prioritized remediation roadmap. It also includes an executive summary designed for leadership and board reporting. Organizations use it to understand exactly where they stand and to make informed decisions about what to build next.
See where your AI governance stands today
A governance gap assessment maps your AI landscape, identifies your risk exposure, and delivers a prioritized roadmap your leadership team can act on. Two to four weeks. Clear deliverables. No ambiguity about what comes next.
Schedule My Assessment
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