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
Executive context
Boards, audit and risk committees, CEOs, and investors overseeing consequential AI adoption.
PROBLEM SOLVED
What this engagement changes
A board-ready governance model that makes AI risk, value, and accountability reviewable.
WHEN TO HIRE
Signals the timing is right
- 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
A different operating objective every 30 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
What leadership should measure
- Material systems inventoried
- Risk reviews completed
- Exceptions and unresolved findings
- Human override effectiveness
- Incident response time
- Evidence and owner completeness
EXPECTED RESULT
What a client should 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
Authority grounded in operating work
Andre combines Wharton corporate-governance education, executive operating responsibility, AI and LLM evaluation research, and experience translating technical behavior into commercial and board-level consequences.
CONCRETE CASE
Operating evidence with clear limits
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 caseFAQ
Questions buyers ask
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.
Start with evidence, not assumptions.
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