Technology and AI governance remains a top concern for corporate directors and executives in 2025 relative to safeguarding data, managing new technologies and ensuring the necessary skills in the boardroom and across the organization. Effective board members understand the importance of technology for their businesses and their role in governing it.
According to the National Association of Corporate Directors 2025 Trends and Priorities Survey, three of the 10 Director's Top Trends for 2025 involve technology governance. Cybersecurity threats and AI remain at the center of director concerns around technology. In WTW’s November 2024 Emerging and Interconnected Risks Survey, executives worldwide listed AI and cyber risk as the top two out of 752 emerging risks. Additionally, WTW’s 2025 Directors' and Officers' Risk Survey reports data loss and cyberattacks are both within the top three risks.
Dynamic and responsible governance models for AI
As covered in AI requires dynamic governance to seize opportunities and manage risks, effective leaders have shifted from traditional risk management protocols to more dynamic and responsible governance models for managing AI’s growth across industries and applications, and adhering to their values.
Classical rules-based governance structures and processes often fail to address AI’s unique challenges and opportunities and cannot keep pace with rapid advancements. Effective leaders adopt guiding principle-based governance practices that allow their organizations to benefit from AI technologies while reducing risks and increasing trust and accountability.
What is ‘responsible AI’?
Effective leaders employ responsible AI – the process of developing and operating AI systems that align with organizational purpose and values while achieving desired business impact. Responsible AI governance models are flexible and responsive and include mechanisms for regular updates, feedback loops and continuous improvement. These models enable leaders to design governance practices specifically addressing AI, adapt to internal and external changes and remain effective and relevant in both the short and long term.
Recently, at an AI roundtable in London hosted by TWIN Global, professor and corporate director Dr. Helmuth Ludwig shared insights from his research conducted in partnership with professor Dr. Benjamin van Giffen regarding board effectiveness in governing AI.
Ludwig and van Giffen reported that although AI is top of mind even for nontechnical business executives and board members, most boards struggle to understand both the implications of AI for their businesses and their role in governing it. The authors identified four categories of board-level AI governance issues and examples of effective practices for each.
