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Board Advisory
AI is already making decisions your board is accountable for. Governing it well is the most under-used strategic lever on the agenda.
For directors and the executives who brief them
I work with boards, their strategy, audit and risk committees, and the leadership teams that report to them. The goal is to accelerate the benefit of AI, safely and with trust intact. That means treating the authority a company hands to AI systems the way a board treats any other delegation: deliberately, in stages, with evidence and a review date. Boards that do this well move faster than boards that don't. Their management teams know the guardrails and stay on the path.
AI and Regulatory Strategy
AI regulation shifts every quarter and rarely lands where the strategy assumed. The board's job is to know which bets depend on a rule staying put, and which markets open when a competitor can't clear the bar. I help boards see AI governance as a strategy question first and a compliance question second.
Questions I help boards answer
- Which parts of our growth plan assume a regulatory outcome we don't control?
- Where does being demonstrably trustworthy let us enter a market others can't?
Responsible Innovation
Most AI failures are culture failures with a technical symptom. Tone at the top, incentives, and whether bad news travels upward decide outcomes long before a model does. I help boards read the culture behind the AI program and set the expectations that shape it.
Questions I help boards answer
- How would an AI-harm concern actually reach this board?
- Do our incentives reward shipping AI faster or governing it well?
AI Governance and Oversight
Directors have a duty to maintain an information and reporting system that lets them judge whether the company is complying with the law and performing as intended. For AI, most boards don't have one yet. I help design the reporting, the key risk indicators, and the committee remit that make AI oversight real rather than ceremonial.
Questions I help boards answer
- What is our AI risk appetite, and has the board approved it?
- Which decisions does AI now make without a human signature, and who decided that?
From Principles to Evidence
A policy the board approved is a promise. Governance is the evidence the promise was kept. I help boards move from principles on paper to the monitoring, validation, and review cadence that regulators and auditors ask to see, so that every sentence in the AI policy has an owner and a record.
Questions I help boards answer
- For any line in our AI policy: who is accountable, what would we see if they were doing it, and when did anyone last look?
- What did the last governance review find, and what changed because of it?
Stakeholder and Regulator Engagement
Regulators, customers, investors, and civil society each hold a piece of the license to operate AI at scale. External advisory and governance boards are the most effective structure I know for managing that risk while keeping the upside. I help boards design them, staff them, and give them real authority.
Questions I help boards answer
- Who outside the company would we want on our side the day an AI decision goes wrong, and do they know us today?
- Does our external advisory body have authority, or an audience?
Infrastructure of Trust
Every business is now a digital business, and digital trust is table stakes. It is also systemic: security and reliability, accountability and oversight, and the ethical use of data cut across every function. The board's mandate has to be as broad as the exposure. I help boards frame that mandate and hold management to it.
Questions I help boards answer
- Where does trust in our AI depend on a single team, vendor, or dataset?
- What would our customers need to see to trust a decision our AI made about them?
How boards work with me
Board and committee briefings
A working session for the full board or the audit, risk, or technology committee: where AI is acting in your company today, what the oversight gaps are, and what to ask management next quarter.
AI oversight review
A structured look at the AI information and reporting system your board relies on, benchmarked against what regulators, auditors, and leading peers now expect, with a short list of changes in priority order.
Standing advisor
Ongoing access for chairs and committee leads between meetings: a second opinion on management's AI proposals, a read on new regulation, and help preparing the questions before the pack arrives.
Director education
Sessions for boards, NACD chapters, and director networks on governing AI autonomy, drawn from work with more than 60 organizations across 10 industries.
Take this to your next meeting
Twelve questions a director should ask about AI
- Is AI treated as an enterprise-wide risk and value issue at this board, or left to the technology function?
- What is our AI risk appetite, and has the board explicitly defined and approved it?
- What information and reporting system tells us, in a timely and accurate way, whether our AI systems are compliant and performing as intended?
- What are our key risk indicators for AI, who reports them to the board, and how often?
- Which decisions does AI now make without a human signature, and who decided that?
- What is management's target state on our AI maturity roadmap, and what is the 12- and 24-month plan to get there?
- What assumptions is management making about AI benefits and risks that the board should be pressure-testing?
- Who owns AI incident response, and has that plan been tested, not just written?
- Does the board have adequate access to AI expertise, on the board or through outside advisors?
- What options did management consider and not select in this AI initiative, and why?
- Are our compensation incentives inadvertently encouraging excessive AI-related risk-taking?
- What is the tone at the top on AI, and how would someone with an AI-harm concern actually reach this board?
