The board's role has expanded: From AI awareness to AI accountability
The board's role has expanded: From AI awareness to AI accountability
There is little doubt that artificial intelligence (AI) is one of the most significant technological innovations of our time. Its impact is already being felt across businesses and virtually every facet of human life, transforming how organisations operate, make decisions, serve customers, compete and grow.
What has changed is not simply the sophistication of the technology, but its strategic significance. AI is no longer a technology experiment or proof of concept sitting within the IT function. It is becoming embedded in business models, investment decisions, customer experiences, operations and risk management. This makes AI not just a management issue but rather a board-level responsibility.
The opportunity is significant. Used effectively, AI can accelerate innovation, sharpen decision-making, improve productivity, enhance customer experiences and strengthen operational resilience. But as its influence and disruption grows, so does the responsibility to ensure that AI is deployed in a way that is trusted, transparent, accountable and aligned with the organisation’s strategic objectives.
This is where the role of the board becomes increasingly important. Board oversight of AI must move beyond awareness to accountability. Boards cannot provide effective oversight if they do not understand how AI is being used, where value is being created, what risks are emerging and whether the organisation has the appropriate controls in place. If they have not done so already, boards now need to develop a sufficient understanding of AI to engage meaningfully with management on both its opportunities and its risks.
The board’s role is not to put the brakes on AI. It is to create the conditions that give the organisation the confidence to accelerate its AI journey responsibly. Winning with AI requires visibility, accountability, trust and evidence. Without these, the risks associated with AI can scale faster than the value it creates.
Unmanaged AI does not simply introduce another category of risk; it can multiply existing risks. Data exposure, flawed or biased decisions, opaque third-party models, cybersecurity vulnerabilities, regulatory challenges and reputational damage can all spread at machine speed. The answer, however, is not to become overly cautious or slow innovation. It is to pursue disciplined ambition. This requires establishing governance that allows lower-risk applications to move quickly while requiring higher-impact uses of AI to demonstrate that they can be trusted.
For boards, this means ensuring that AI governance is connected to the broader business strategy rather than treated as a standalone technology initiative. Organisations need a clear AI portfolio linked to strategic priorities, investment decisions and measurable value. Accountability should be clearly assigned for AI use cases, decisions, controls, risk acceptance and escalation. There should be fast lanes for lower-risk applications and appropriate gating for higher-impact uses.
Governance must also extend across the AI lifecycle. This includes data, privacy, identity, cybersecurity, third parties, technology integrations, AI agents and operational resilience. Most importantly, boards should ensure that AI is controlled, reliable, operating within the organisation’s risk appetite and delivering sufficient value to justify continued investment.
Against this backdrop, five board responsibilities stand out.
1. Strategic stewardship
Boards should treat AI as a potential growth and competitiveness engine rather than a side experiment. This means understanding where AI can support the organisation’s strategic objectives, where investment is justified and how AI can create sustainable value.
2. Governance and accountability
Ownership must be clear before AI decisions scale. Boards should ensure that management has established appropriate decision rights, accountability structures, risk thresholds and escalation mechanisms for AI deployment and use.
3. Responsible and trusted AI
AI must operate within the organisation’s legal, ethical, privacy and broader trust commitments. In this regard, considerations such as fairness, transparency, data protection and responsible are critical because they need to be embedded into AI governance.
4. Assurance and oversight
Boards should demand proof, not promises. They need sufficient assurance that AI systems are performing as intended, that appropriate controls are operating, that risks are understood and managed, and that investments are delivering measurable value.
5. Resilience and preparedness
No AI governance framework can eliminate failure or unexpected outcomes. Organisations therefore need the resilience and response capabilities to act when AI fails, produces unexpected results, is compromised or is misused. Boards should understand whether the organisation has the systems, skills and processes needed to respond effectively.
As AI continues to evolve, the question for boards is no longer whether their organisations should engage with it, but how they can do so responsibly and strategically. This requires boards to continually engage with management to use AI to future-proof their business by identifying where AI can best support business objectives, unlock new opportunities, strengthen competitiveness and improve resilience. Ensuring that AI use is always transparent, fair and accountable is an equally critical board imperative.
Because AI, its use and impact is now extending beyond the IT function, governance and oversight has become an important part of the board’s fiduciary responsibility, which cannot simply be management responsibility
What has changed is not simply the sophistication of the technology, but its strategic significance. AI is no longer a technology experiment or proof of concept sitting within the IT function. It is becoming embedded in business models, investment decisions, customer experiences, operations and risk management. This makes AI not just a management issue but rather a board-level responsibility.
The opportunity is significant. Used effectively, AI can accelerate innovation, sharpen decision-making, improve productivity, enhance customer experiences and strengthen operational resilience. But as its influence and disruption grows, so does the responsibility to ensure that AI is deployed in a way that is trusted, transparent, accountable and aligned with the organisation’s strategic objectives.
This is where the role of the board becomes increasingly important. Board oversight of AI must move beyond awareness to accountability. Boards cannot provide effective oversight if they do not understand how AI is being used, where value is being created, what risks are emerging and whether the organisation has the appropriate controls in place. If they have not done so already, boards now need to develop a sufficient understanding of AI to engage meaningfully with management on both its opportunities and its risks.
The board’s role is not to put the brakes on AI. It is to create the conditions that give the organisation the confidence to accelerate its AI journey responsibly. Winning with AI requires visibility, accountability, trust and evidence. Without these, the risks associated with AI can scale faster than the value it creates.
Unmanaged AI does not simply introduce another category of risk; it can multiply existing risks. Data exposure, flawed or biased decisions, opaque third-party models, cybersecurity vulnerabilities, regulatory challenges and reputational damage can all spread at machine speed. The answer, however, is not to become overly cautious or slow innovation. It is to pursue disciplined ambition. This requires establishing governance that allows lower-risk applications to move quickly while requiring higher-impact uses of AI to demonstrate that they can be trusted.
For boards, this means ensuring that AI governance is connected to the broader business strategy rather than treated as a standalone technology initiative. Organisations need a clear AI portfolio linked to strategic priorities, investment decisions and measurable value. Accountability should be clearly assigned for AI use cases, decisions, controls, risk acceptance and escalation. There should be fast lanes for lower-risk applications and appropriate gating for higher-impact uses.
Governance must also extend across the AI lifecycle. This includes data, privacy, identity, cybersecurity, third parties, technology integrations, AI agents and operational resilience. Most importantly, boards should ensure that AI is controlled, reliable, operating within the organisation’s risk appetite and delivering sufficient value to justify continued investment.
Against this backdrop, five board responsibilities stand out.
1. Strategic stewardship
Boards should treat AI as a potential growth and competitiveness engine rather than a side experiment. This means understanding where AI can support the organisation’s strategic objectives, where investment is justified and how AI can create sustainable value.
2. Governance and accountability
Ownership must be clear before AI decisions scale. Boards should ensure that management has established appropriate decision rights, accountability structures, risk thresholds and escalation mechanisms for AI deployment and use.
3. Responsible and trusted AI
AI must operate within the organisation’s legal, ethical, privacy and broader trust commitments. In this regard, considerations such as fairness, transparency, data protection and responsible are critical because they need to be embedded into AI governance.
4. Assurance and oversight
Boards should demand proof, not promises. They need sufficient assurance that AI systems are performing as intended, that appropriate controls are operating, that risks are understood and managed, and that investments are delivering measurable value.
5. Resilience and preparedness
No AI governance framework can eliminate failure or unexpected outcomes. Organisations therefore need the resilience and response capabilities to act when AI fails, produces unexpected results, is compromised or is misused. Boards should understand whether the organisation has the systems, skills and processes needed to respond effectively.
As AI continues to evolve, the question for boards is no longer whether their organisations should engage with it, but how they can do so responsibly and strategically. This requires boards to continually engage with management to use AI to future-proof their business by identifying where AI can best support business objectives, unlock new opportunities, strengthen competitiveness and improve resilience. Ensuring that AI use is always transparent, fair and accountable is an equally critical board imperative.
Because AI, its use and impact is now extending beyond the IT function, governance and oversight has become an important part of the board’s fiduciary responsibility, which cannot simply be management responsibility