Amid the technological surge of Artificial Intelligence, organizations are pushing projects that influence customer service and marketing strategies to management-level decision-making and security aspects. However, when it comes to governance, the board of directors still seems to struggle with keeping pace. A recent report suggests that almost a third of director-level business leaders lack AI education, which raises questions about how informed their governance decisions can be.

This gap in AI governance at the highest levels can only be handled by forming an effective board that can navigate the complexities of AI adoption. In this blog, we explore the challenges of establishing such a board and share best practices to overcome these challenges. With a smart and forward-looking AI governance board, organizations can more effectively steer safely through the AI era.

Boardroom Brain Freeze

Certainly, Artificial Intelligence is a strategic and governance priority requiring expert guidance. Such guidance will help with better AI risk assessments, governance consulting, and executive education. Here are the current challenges in forming an AI governance board that can help organizations navigate AI responsibly and strategically.

• Knowledge Gap Among Directors: Boards are not expected to be technical experts, but they must possess enough understanding of AI to evaluate its risks and limitations. Without this foundational knowledge, directors are unable to ask probing questions or challenge management decisions in meaningful ways. Many directors are still grappling with the basics, seeking clarity on core concepts, and trying to understand the strategic implications of AI deployment.
• Rapid Pace of AI Adoption: AI adoption in enterprises is moving at a speed that often outstrips the capacity of boards to stay informed. Generative AI and agentic AI are evolving in real time, introducing new capabilities and risks that were previously unimaginable. For boards, this fast-paced environment transforms governance into a moving target. The strategies and policies are required to continuously adapt to keep up with technological change. Directors often feel pressured to understand emerging tools and assess their impact on business strategy.
• Cross-Functional Complexity: AI touches nearly every part of an organization, from strategy and customer experience to workforce planning and legal risks. This breadth of impact requires boards to integrate perspectives from multiple functions, including CIOs, legal counsel, risk officers, HR leaders, and data teams. Coordinating these viewpoints is challenging, particularly when each function approaches AI from a different lens.
• Lack of Frameworks and Standards: Many organizations have yet to develop clear policies and frameworks for responsible AI use, leaving boards unsure of how to systematically evaluate initiatives. In the absence of standardized criteria, directors may struggle to determine which projects align with strategic priorities.  This lack of structure complicates oversight and increases the likelihood of inconsistent or reactive decision-making.
• Cultural and Strategic Misalignment: AI initiatives are often driven by the C-suite, which can leave boards feeling reactive rather than proactive in governance. When strategic alignment is weak, oversight may be superficial and risks may go unmitigated. Misalignment between executive priorities and board expectations also risks missed opportunities for innovation or competitive advantage.

Education, Collaboration, and Strategy

The disconnect between AI adaptation and AI education stems from the perception that AI is just another operational tool with no strategic influence beyond that. Therefore, for an effective AI governance board, there is a need for leaders who question assumptions, guide long-term strategies, and assess risks proactively.

• Structured AI education: The AI governance board can engage with workshops, executive bootcamps, or external courses designed to build foundational knowledge. Understanding AI’s capabilities, limitations, risks, and responsible use frameworks equips directors to ask informed questions and provide meaningful oversight.
• Cross-Functional Expertise: AI affects multiple dimensions of an organization, making cross-functional collaboration essential. Boards should actively involve CIOs, legal counsel, risk officers, HR leaders, and other key executives in briefings and discussions about AI initiatives.
• Continuous Learning: AI is evolving rapidly, and boards must commit to continuous learning to stay ahead of emerging technologies and associated risks. This involves regular briefings on new developments, participation in industry conferences, engagement with peer boards, and consultation with advisory networks.
• AI Governance With Business Strategy: AI governance should be fully integrated with corporate strategy rather than treated as a standalone function. Boards must ensure that AI initiatives support organizational goals while also evaluating their impact on workforce planning, customer experience, and operational efficiency.
• Culture of Responsible AI: Beyond oversight, boards should champion a culture of ethical and responsible AI adoption across the organization. By fostering responsible AI practices, boards help ensure that technology deployment aligns with organizational values, mitigates potential harms, and builds trust with stakeholders.

How Boards Can Govern AI Effectively

Forming an AI governance board is undoubtedly challenging, given knowledge gaps, rapid technological change, and cross-functional complexity. Yet, by taking a structured, educated, and collaborative approach, organizations can transform these hurdles into strengths. Forward-looking governance enables boards to guide enterprises safely and effectively into an AI-enabled future, ensuring that adoption delivers value while mitigating risks and fostering trust across stakeholders.