Advisory

AI Governance and Accountability

When AI moves from pilots to enterprise decisions, governance must move from policy to operating model.

The Issue

Most AI governance efforts begin with policies, principles, and review processes. But AI risk becomes material when it affects decisions, customers, employees, operations, compliance, or reputation.

The gap between having an AI policy and having an AI accountability model is where most organizations are exposed.

Boards are asking sharper questions. Regulators are paying closer attention. AI is embedded in more decisions than most organizations can clearly map. And the executives responsible for AI outcomes often lack the authority, sponsorship, or operating context required to deliver what leadership is expecting.

AI governance is not a documentation exercise. It is an operating model for accountability, escalation, risk visibility, and board-level oversight.

How I Help

Dr. David Marco works with boards, CEOs, CIOs, CDOs, CTOs, CAIOs, and executive teams to design AI governance structures that clarify who owns what, who decides what, where risk sits, and how the organization maintains accountability as AI scales.

AI Governance Framework Design

Designing governance structures that go beyond committees and policies to create real operating models with clear ownership, decision rights, escalation paths, and board visibility.

Board-Level AI Risk and Oversight

Helping boards understand how to oversee AI without becoming technologists or overstepping into management's role. Translating AI risk into language that boards can act on.

AI Accountability and Decision Rights

Mapping who is accountable for the business, risk, and decision consequences of AI use, and whether that accountability is explicit, distributed, or merely implied.

Responsible AI Operating Model

Designing governance that allows responsible AI adoption to accelerate rather than slow down. Governance should create confidence, reduce rework, and clarify decision rights so the business can move faster without losing accountability.

Who This Is For

  • Boards and audit/risk committees evaluating AI oversight readiness
  • CEOs and executive teams scaling AI adoption
  • CIOs, CDOs, CTOs, and CAIOs building or inheriting AI governance mandates
  • Organizations where AI pilots are expanding without a clear enterprise operating model
  • Leadership teams preparing for regulatory, compliance, or board scrutiny on AI

The Question This Advisory Answers

Is the organization's AI governance and accountability model strong enough to support the outcomes leadership is promising?

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