BOARD ADVISORY
AI Governance Advisor for Boards
An AI governance advisor helps boards define oversight, accountability, risk thresholds, evidence requirements, human controls, and reporting for consequential AI use.
WHO IT IS FOR
Who is this service designed for?
Boards, audit and risk committees, CEOs, and investors overseeing consequential AI adoption.
PROBLEM SOLVED
Which operating problem does it solve?
A board-ready governance model that makes AI risk, value, and accountability reviewable.
WHEN TO HIRE
When should leadership hire this service?
- The board cannot see where AI is materially used
- Model limitations are not translated into business exposure
- Policies exist without workflow enforcement
- Executives cannot explain ownership when AI fails
NOT A FIT
Who should not hire this service?
This is not legal advice, a compliance certification, or a substitute for cybersecurity, privacy, regulatory, and internal-audit specialists.
FIRST 90 DAYS
What happens in the first 30, 60, and 90 days?
- Map material AI systems, decisions, owners, vendors, and affected stakeholders
- Identify regulatory, customer, financial, and operating exposure
- Define immediate escalation and disclosure gaps
- Establish oversight roles, risk tiers, evidence standards, and approval thresholds
- Design board and committee reporting
- Connect policy to procurement, deployment, monitoring, and incident response
- Run governance reviews on selected high-impact systems
- Test escalation, human override, and evidence retention
- Train directors and executives using real decisions
METRICS AFFECTED
Which metrics should leadership measure?
- Material systems inventoried
- Risk reviews completed
- Exceptions and unresolved findings
- Human override effectiveness
- Incident response time
- Evidence and owner completeness
EXPECTED RESULT
What result should a client expect?
A board-ready governance model that makes AI risk, value, and accountability reviewable.
Results depend on market conditions, product, data, investment, team adoption, and execution. No commercial outcome is guaranteed.
WHY ANDRE MAGRINI
Why is Andre Magrini qualified to lead this work?
Andre combines executive operating responsibility, AI and LLM evaluation research, and experience translating technical behavior into commercial and board-level consequences.
CONCRETE CASE
What operating evidence supports the approach?
In model evaluation work, apparently strong benchmark performance can hide repeatable failure mechanisms. Board governance must therefore require evidence from the intended context, not only vendor averages.
Read the $35M to $150M+ operating caseENGAGEMENT OPTIONS
How can the work be structured?
| Engagement | Best used when | Primary deliverable | Decision at completion |
|---|---|---|---|
| Focused diagnostic | Leadership needs an independent baseline before committing resources | Evidence review, constraint map, scorecard, and decision memo | Stop, repair, sequence, or fund the next phase |
| 90-day operating build | The priority is known but definitions, cadence, controls, and ownership must be installed | Operating system, live reviews, documented decisions, and capability transfer | Continue internally, extend selectively, or define the permanent role |
| Fractional executive mandate | The company needs ongoing senior ownership while the market, team, or permanent position evolves | Executive leadership, board reporting, operating decisions, and team development | Transfer ownership, hire permanently, narrow scope, or renew against evidence |
Scope, availability, decision rights, confidentiality, implementation responsibility, and commercial terms are documented after the diagnostic. Pricing depends on mandate intensity and responsibility rather than a generic hourly package.
FAQ
What do buyers ask before engaging?
What should a board ask about AI?
Ask where AI is material, who owns each decision, what evidence supports deployment, how humans intervene, what failures are monitored, and when the board is notified.
Is an AI policy enough?
No. Governance requires decision rights, workflow controls, evidence, monitoring, exceptions, escalation, and accountable executive behavior.
Does this replace legal review?
No. The advisor coordinates operating governance and decision evidence; qualified legal and regulatory counsel must address jurisdiction-specific obligations.
What should leadership diagnose first?
Request a focused diagnostic of the operating constraint behind revenue or AI execution.
Request an AI Revenue DiagnosticWhich external evidence provides context?
NIST developed AI RMF 1.0 over 18 months with contributions from more than 240 organizations and structures risk management around Govern, Map, Measure, and Manage. For boards, the practical implication is that AI oversight must connect policies to real systems, owners, evidence, escalation paths, human controls, vendor exposure, and recurring executive reporting.