In the AI era, legacy governance practices are no longer sufficient. As artificial intelligence becomes deeply embedded in decision-making, risk management, and operational efficiency, boards must evolve. Treating AI as merely a technical issue relegated to IT teams exposes organizations to reputational, regulatory, and fiduciary risk. Effective oversight now requires board-level literacy, clearly defined governance roles, ethical risk frameworks, and a proactive shift from passive supervision to informed stewardship. The choices boards make—or fail to make—around AI will directly shape long-term value and trust.

Elevate AI Governance to a Board-Level Priority

• Treat AI as a strategic enterprise risk—on par with cybersecurity or compliance.

• Form an AI oversight committee or embed AI literacy into existing risk or tech committees.

1. Invest in AI Fluency

   • Ensure board members understand foundational AI concepts: bias, explainability, risk modeling, data lineage, and governance frameworks.

   • Bring in external advisors or create board education programs on emerging technologies.

2. Mandate Responsible AI Policies

   • Implement ethical use policies aligned with organizational values and regulatory frameworks.

   • Demand transparency and auditability in algorithmic decision-making.

3. Link AI Strategy to Long-Term Enterprise Value

   • Encourage AI initiatives that improve operational efficiency, client insight, and risk control—not just short-term cost savings.

4. Ask the Right Questions

   • Who owns AI risk? Who validates models? Are data sources secure and unbiased?

   • Are vendors and internal teams aligned on ethical AI standards?

What Should Boards Stop Doing?

1. Stop Delegating AI Oversight Solely to IT or Data Teams

   • AI decisions increasingly affect reputation, compliance, and fiduciary responsibility—this is board territory.

2. Stop Underestimating AI’s Reputational Risk

   • Bias in algorithms, misused customer data, or lack of explainability can erode trust faster than any technical error.

3. Stop Treating AI as a “Black Box”

   • Boards must move beyond blind trust in technologists or third-party vendors and demand explainability.

4. Stop Prioritizing Speed Over Integrity

   • Rushing AI deployment without testing for bias or fairness can lead to long-term liabilities.

How Should Boards Adjust?

• Shift from a Control Mindset to a Stewardship Mindset
  Boards must balance innovation enablement with value preservation—especially in multi-generational family enterprises.

• Reframe Technology as a Cross-Cutting Governance Issue
  Like ESG, AI now affects every corner of the business: from operations and investment decisions to legal risk and public trust.

• Integrate AI Risk into Enterprise Risk Management (ERM)
  Make AI governance part of the same process used for cyber, legal, or operational risk.

As stewards of enduring capital and legacy, boards—particularly in family offices and private enterprises—must ensure that AI enhances, rather than endangers, their institution’s purpose. That means embracing AI governance not as a compliance exercise, but as a cornerstone of strategic leadership. Boards that embed AI responsibility into their core oversight functions will be better equipped to harness innovation while upholding the values, accountability, and resilience that define lasting institutions. The time to act is now—responsibly, transparently, and deliberately.