Importance of AI Governance for Boards

Your board does not have an AI risk framework. If it did, someone would have asked about it in the last six months. Three in four boards have approved major AI investments. Fewer than half have set governance expectations for them. (Grant Thornton, 2026.) Usage is not the problem. Most companies already run AI somewhere — often in more places than the board has been told. Sit in a board meeting and you will hear adoption numbers and a slide about productivity gains. Everyone nods, and the agenda moves on. Adoption is not governance. Governance is the part where the board can answer who is accountable when an AI-driven decision goes wrong. Ask that in most boardrooms and you get a pause — then a look towards whoever manages IT. A real framework has five parts, and most companies have none of them: ✅ A model inventory: every AI system you actually run, including the tool your CMO bought on a credit card ✅ A human-in-the-loop policy: which decisions need a person to sign off, and which do not ✅ An incident playbook: what happens when the model misbehaves at 11pm on a Sunday ✅ Vendor accountability: when a third-party AI breaks, the accountability is still yours. PDPA does not let you contract it away ✅ A decision audit trail: could you reconstruct a customer-impacting AI decision if a regulator asked tomorrow · Frontier models change weekly. Your board meets quarterly. That maths only works if governance is structural: checked at every meeting, owned by a named director, stress-tested at least once a year. If you want a starting point that already exists, look at IMDA's Model AI Governance Framework. It now covers AI agents specifically. The boards that sort this out in 2026 are the ones not writing apology letters in 2027. Take those five into your next board meeting and count how many you can answer without leaving the room. Under three and you have an AI strategy with no governance underneath it. Tell me your number. #AIGovernance #BoardLeadership #AIRisk

I just read the McKinsey and NACD panel on the Board's role in managing AI risk. One line from Guy Gecht, Board Chair at Logitech, was impactful: “For 25 years, we protected data. Now, we need to protect judgment.” The Boards that win will protect good judgment and build more of it. Those figures are a wake-up call:   • 𝗖𝗼𝗺𝗽𝗮𝗻𝗶𝗲𝘀 𝘄𝗶𝘁𝗵 𝗱𝗶𝗴𝗶𝘁𝗮𝗹 𝗮𝗻𝗱 𝗔𝗜-𝘀𝗮𝘃𝘃𝘆 𝗕𝗼𝗮𝗿𝗱𝘀 𝗯𝗲𝗮𝘁 𝗽𝗲𝗲𝗿𝘀 by 10.9 points on return on equity (MIT, 2025)   • Only 𝟴% 𝗼𝗳 𝟯,𝟬𝟬𝟬 𝗨𝗦 𝗟𝗶𝘀𝘁𝗲𝗱 𝗙𝗶𝗿𝗺𝘀 𝗱𝗶𝘀𝗰𝗹𝗼𝘀𝗲 𝗮 𝗕𝗼𝗮𝗿𝗱-𝗹𝗲𝘃𝗲𝗹 𝗔𝗜 oversight (ISS, January 2026)   • 𝟳𝟴% 𝗼𝗳 𝗲𝘅𝗲𝗰𝘂𝘁𝗶𝘃𝗲𝘀 𝗮𝗿𝗲 𝗻𝗼𝘁 𝗰𝗼𝗻𝗳𝗶𝗱𝗲𝗻𝘁 𝘁𝗵𝗲𝘆 𝗰𝗼𝘂𝗹𝗱 𝗽𝗮𝘀𝘀 𝗮𝗻 𝗶𝗻𝗱𝗲𝗽𝗲𝗻𝗱𝗲𝗻𝘁 𝗔𝗜 governance audit (Grant Thornton, 2026) Better judgment is now a competitive edge, not a compliance task. Four ways to build it: ✅ 𝗕𝘂𝗶𝗹𝗱 𝘁𝗵𝗲 𝗾𝘂𝗮𝗹𝗶𝘁𝘆 𝗼𝗳 𝗷𝘂𝗱𝗴𝗺𝗲𝗻𝘁   • Invite outside experts twice a year   • Map Board skills against where the company is going, then close the gaps   • P&G, a consumer goods company (not a tech firm!) runs a Board Innovation and Technology Committee ✅ 𝗗𝗲𝗰𝗶𝗱𝗲 𝘄𝗵𝗮𝘁 𝗔𝗜 𝗰𝗮𝗻 𝗷𝘂𝗱𝗴𝗲   • Define where AI acts alone, where a human decides, and who is accountable if AI fails   • Test agents and plan for when they act wrongly   • Meta's internal agent published wrong information and exposed data in March 2026 ✅ 𝗦𝗲𝗰𝘂𝗿𝗲 𝘀𝗽𝗮𝗰𝗲 𝗳𝗼𝗿 𝗷𝘂𝗱𝗴𝗺𝗲𝗻𝘁 𝗼𝗻 𝘁𝗵𝗲 𝗮𝗴𝗲𝗻𝗱𝗮   • Move AI out of a crowded audit agenda into a committee with the right people   • Track AI risk continuously, not once a quarter   • United Airlines runs AI risk in real time, not a quarterly look-back. Problems are addressed as they appear. ✅ 𝗦𝗵𝗮𝗿𝗽𝗲𝗻 𝗷𝘂𝗱𝗴𝗺𝗲𝗻𝘁 𝘄𝗶𝘁𝗵 𝗯𝗲𝘁𝘁𝗲𝗿 𝗲𝘃𝗶𝗱𝗲𝗻𝗰𝗲   • Review how an AI decision was made, and trace what went wrong   • Ask management for the cost and the return, not soft productivity stories   • California's new law, effective Jan. 2026, removes “AI did it” as a defense. Boards must be able to explain the decision Good Boards protect judgment. Great Boards keep growing it. 💡 𝗪𝗵𝗮𝘁 𝗶𝘀 𝗼𝗻𝗲 𝘁𝗵𝗶𝗻𝗴 𝘆𝗼𝘂𝗿 𝗕𝗼𝗮𝗿𝗱 𝗱𝗼𝗲𝘀 𝘁𝗼 𝗸𝗲𝗲𝗽 𝗶𝘁𝘀 𝗷𝘂𝗱𝗴𝗺𝗲𝗻𝘁 𝘀𝗵𝗮𝗿𝗽? #BoardDirectors #CorporateGovernance #AI #BoardEffectiveness #RiskManagement #Leadership

To perform their duties responsibly, boards must function as Humans + AI. Adopting new working structures and evolved governance structures incorporating AI can lead to substantial performance improvement. Much of my current work with boards is on strategic framing for AI and in AI-augmented decision-making, but there is considerably more potential. A very nice HBR piece brings real-world insights to bear. The first finding was that directors and chairs largely failed to recognize the value and potential of AI in their work. However still many boards and directors are using AI in useful ways. MEETING PREPARATION Directors who use LLMs reported significantly improved understanding of agenda items and reduced workload. One director across five Danish boards uses AI to structure presentations and run simulations; another in Switzerland uses it to refine board discussion questions from the board book. SCENARIO PLANNING GenAI, used well, can be an excellent tool for rapid scenario planning. One board in Austria used an LLM to analyze geopolitical risk in an acquisition proposal. This led to it rejecting the deal, and resulted in management attaching scenario analyses to future proposals. ADDITIONAL PERSPECTIVES Boards in Finland and the Netherlands used AI to test their own strategic conclusions, finding significant overlap between AI-generated insights and their human decisions. This boosted both their confidence in the decisions and their trust in AI’s utility, particularly for validating or challenging complex judgments. IMPROVING BOARD DYNAMICS AI can offer real-time feedback on boardroom dynamics. For example, a Swiss industrial company uses AI to analyze speaking time, tone, and engagement during meetings, creating recommendations for better group engagement. The article addresses potential risks: 🔐 Information leaks. These stem not from AI itself but from poor data governance, which can be mitigated with proper access controls and security training. ⚖️ Sample bias. Regular audits and user awareness are key to avoiding flawed, discriminatory, or incomplete insights. 🧭 Anchoring in the past. AI can be overly reliant on historical data. Scenario simulations and reasoning models can help boards anticipate and adapt to future shifts. And concludes with recommendations on learning to use AI well: 1️⃣ Create engagement. Chairs should start with one-on-one conversations to assess AI literacy and follow up with tailored training to build confidence and interest. 2️⃣ Practice collective experimentation. Boards should test AI tools together in low-stakes settings, debrief their experiences, and gradually integrate AI into governance processes. 3️⃣ Maintain momentum. Chairs must lead by example, celebrate AI use regardless of outcomes, and embed AI progress into board evaluations. I am currently working on a 'GenAI in the Boardroom' mini-report that I will be sharing soon, addressing these and a range of other issues and possibilities.

#AskDrTim 🔆 | AI Will Not Replace Boards. But Boards That Don’t Understand AI May Be Replaced. Artificial intelligence is no longer just an IT initiative. It is now a boardroom responsibility. A recent The Straits Times article highlighted Singapore’s new guidance on AI governance for boards, and I believe it comes at exactly the right time. Minister Josephine Teo made a powerful observation: many employees are already using AI more effectively than their organisations. The challenge for leaders is not whether AI exists. It is whether we can harness the creativity and productivity already emerging within our workforce while putting the right governance around it. As someone who has served on hospital and corporate boards, I have learned that every disruptive technology follows a similar pattern. The winners are not those who adopt technology the fastest. They are those who govern it the wisest. The new guidance rightly shifts the conversation from AI adoption to AI accountability. Boards should no longer ask: • How many AI licences have we purchased? • How many pilots have we launched? Instead, they should ask: • Are we improving patient outcomes, customer experience or operational efficiency? • Are our AI systems transparent, secure and free from unacceptable bias? • Where must human judgement always remain non-negotiable? • Do we have directors who can challenge management on AI strategy, governance and risk? Perhaps the most important recommendation is that AI oversight cannot sit with just one “AI expert” on the board. Every director needs sufficient AI literacy to ask better questions. Because governance is not about having all the answers. It is about asking the questions that protect long-term value. In healthcare, where AI increasingly influences diagnostics, clinical workflows, workforce planning and patient engagement, this becomes even more critical. AI should augment human expertise, not replace human responsibility. Technology can scale intelligence. Only people can remain accountable. As we enter the era of agentic AI, boards will increasingly be remembered not for how quickly they embraced AI, but for how wisely they governed it. The future belongs to organisations that combine innovation with trust. #AskDrTim

AI in the Boardroom: What Charity Trustees Need to Do Now 🚨 Too many boards are sleepwalking into the risks, while missing the opportunities. I've just finished reading the new Institute of Directors (IoD)’s 'AI Governance in the Boardroom report' and it makes one thing clear: trustees can’t delegate this. AI is a board-level issue. Here are the key takeaways from the report every charity board should act on: 🧠 Stay Curious. Stay Learning. Boards don’t need to be technical experts, but they must understand enough to ask the right questions. Build a culture of digital curiosity at board level. ⚖️ AI = Risk AND Opportunity. Don’t just see AI as a shiny tool to save time. Trustees must weigh efficiency gains against bias, privacy, reputational harm, and compliance risks. ❓ Governance Starts with Questions. Who owns AI in your organisation? How is data being used? What safeguards are in place? Boards need simple checklists and regular oversight, not a one-off discussion. 📜 Know the Law. Regulation is tightening. - The EU AI Act is rolling out, with obligations on transparency, risk classification, and human oversight. - The UK is moving towards sector-led regulation, but trustees are still on the hook for data misuse under GDPR and the ICO’s guidance. - Trustees should be clear: ignorance won’t protect your charity from fines, reputational damage or, worst of all, harm to beneficiaries. 🎯 Impact Before Hype. Does this AI tool align with our mission, or is it just a gimmick? Focus on how tech helps people - service users, staff, and volunteers. 🛡️ Build Oversight Structures. Some boards are creating AI subcommittees or ethics groups. At the very least, AI should be a standing agenda item. Oversight isn’t optional anymore. 🔐 Data is Everything. AI governance is data governance. If your board isn’t confident on data protection, cybersecurity, and safeguarding sensitive information, that’s the place to start. The report is blunt: AI governance is now a fiduciary duty. Trustees don’t get a free pass. ✅ If you sit on a charity board, make AI part of your next meeting agenda. ✅ If you’re a Digital Trustee, help your board translate principles into practice. ✅ If you’re a CEO, empower your trustees to ask the hard questions. This is about safeguarding the people we serve, and making sure technology works for charities, not against them. 👉 If you need to find an AI, data or cyber expert for your board check out the funded Digital Trustees programme from Third Sector Lab. 👏 Thanks to all the authors of the report, including: Michael Ambjorn Phil Clare Paul Corcoran Pauline Norstrom LLB (Hons) FRSA FIoD FBCS Niran Olarinde Institute of Directors (IOD), India Institute of Directors (IoD) ❓What's your simple advice for boards looking to start their AI conversation?

Responsible AI begins with governance. It belongs in the boardroom. In FT Agenda, the Financial Times’ platform for corporate directors, Julia Dhar and I speak directly to boards and executive leaders facing decisions about how AI is changing their organizations. AI is already shaping core functions, from operations and customer experience to workforce management and strategic planning. Oversight can’t be deferred. It must be exercised by those who define institutional values and direction. Boards should be setting expectations now. That means asking how AI is introduced across the organization, how it is experienced by employees, and whether it reflects the commitments we’ve made to transparency, inclusion, and long-term impact. We’re working alongside leaders who understand that AI isn’t just a technical issue. It’s a question of leadership. And values-based leadership is what connects innovation to human progress. That’s what will shape the future of work - and the future of institutions. Read and share the full piece here: https://lnkd.in/e4XJkA6v #ResponsibleAI #CorporateLeadership #EthicalTechnology #AIandBoards #Governance The Patrick J. McGovern Foundation NACD (National Association of Corporate Directors) Mark A. Pfister - 'The Board Architect' Latino Corporate Directors Association (LCDA) Ozzie (Oswaldo) Gromada Meza Wendi X. Zhang

A signal I’m seeing show up consistently in boardroom conversations is that AI has moved from an interesting agenda item to a governance priority. It’s no longer something boards are monitoring. It’s something they’re being asked to actively shape.   This Bloomberg Law piece (https://deloi.tt/3L7sQzh) captures that shift well, especially the points that Deloitte’s Beena Ammanath make on how boards can move beyond deployment questions to driving measurable value, mitigating risks, and maintaining accountability.   As AI investments scale, boards may no longer be satisfied with activity metrics or pilot updates. They’re focused on return, the risks associated, and whether AI is actually creating value.     The challenge: Move too fast and risk trust. Move too slowly and risk irrelevance. And unlike past technology cycles, there’s no neutral middle ground where costs stay contained, and outcomes stay optional.   The boards leaning in most effectively aren’t trying to become AI experts overnight. They’re clarifying governance, setting expectations for interim value signals, and pressing management to connect AI decisions back to strategy – not just technology. 

In the midst of the AI hype and the frenzy around the latest model innovations, too often the importance of governance is overlooked. Having a solid set of AI policies and guidelines is not just some administrative checkbox or a fancy trim on your AI strategy. It’s the bedrock upon which successful, scalable, and sustainable AI is built. Ignore it, and you’re essentially setting yourself up for failure. In a world with constant headlines about the latest AI breakthroughs, pausing to set up “guardrails” might seem like slamming the brakes on innovation. But failing to establish a clear governance framework is the real momentum killer. Why? Well, for starters: 1. Trust is Everything First off, without trust, your AI project is going nowhere fast. This isn’t just about making sure your AI doesn’t go rogue; it’s about gaining the confidence of everyone involved, from the people on the ground floor to your customers and partners. Trust is the currency of the AI realm. Without it, you can’t expect widespread adoption or enthusiasm for new technology, internally or externally. Governance ensures that your AI initiatives are transparent, ethical, and, most importantly, trustworthy. 2. The Need for Common Ground Think of governance as your AI strategy’s North Star. A lack of governance leads to a Wild West scenario where everyone is doing their own thing, leading to confusion, inefficiency, and a mishmash of efforts that don’t quite add up. Governance provides a common framework that aligns AI development with your company’s goals, ensuring coherence both in terms of business-driven use cases and the technical foundation upon which these innovations are built. 3. Dodging the Compliance Bullet And let’s not forget the looming shadow of compliance and regulatory requirements. With governments and regulatory bodies waking up to the implications of AI, the rules of the game are changing—and they’re changing fast. Without governance, you’re essentially flying blind into a storm of potential legal and ethical challenges. Governance ensures you’re prepared and protected, keeping you ahead of the curve and out of the regulatory crosshairs. Failing to govern your AI initiatives is a one-way ticket to failure. It’s not just about preventing mishaps; it’s about ensuring your AI journey is built on a solid, sustainable foundation that fosters trust, ensures coherence, and navigates the waters of compliance. #IBM #IBMiX #GenAI #GenerativeAI #AI

By 2028, Boards of Directors will not be able to treat AI as a side conversation or a delegated technical issue. AI is becoming a core governance responsibility. As risk velocity accelerates and corporate complexity deepens, boards must develop algorithmic awareness, AI fluency, and new oversight muscles. Fiduciary duty will increasingly depend on how well directors understand AI driven risk sensing, ethical governance, strategic foresight, board effectiveness, and stakeholder sentiment. The boards that lead will not just react faster. They will govern smarter, anticipate disruption earlier, and build long term trust with investors, regulators, and society. I break this down in the latest piece, 2028 Boardroom Playbook: Using AI to Lead, Govern, and Win, with five concrete AI use cases every board should understand now. Read more about it here: https://lnkd.in/evUMrFR2 AI is no longer just a tool for management. It is becoming a compass for modern governance.

𝟗𝟒% 𝐨𝐟 𝐠𝐥𝐨𝐛𝐚𝐥 𝐂𝐄𝐎𝐬 𝐛𝐞𝐥𝐢𝐞𝐯𝐞 𝐀𝐈 𝐜𝐨𝐮𝐥𝐝 𝐨𝐟𝐟𝐞𝐫 𝐛𝐞𝐭𝐭𝐞𝐫 𝐜𝐨𝐮𝐧𝐬𝐞𝐥 𝐭𝐡𝐚𝐧 𝐚𝐭 𝐥𝐞𝐚𝐬𝐭 𝐨𝐧𝐞 𝐨𝐟 𝐭𝐡𝐞𝐢𝐫 𝐛𝐨𝐚𝐫𝐝 𝐦𝐞𝐦𝐛𝐞𝐫𝐬. I came across this in an Harvard Business Review and it struck me as a wake-up call for boards and a sharp reflection of today’s governance reality. Modern boards face a paradox: 𝐭𝐡𝐞𝐲 𝐜𝐚𝐫𝐫𝐲 𝐞𝐧𝐨𝐫𝐦𝐨𝐮𝐬 𝐫𝐞𝐬𝐩𝐨𝐧𝐬𝐢𝐛𝐢𝐥𝐢𝐭𝐲 𝐲𝐞𝐭 𝐨𝐩𝐞𝐫𝐚𝐭𝐞 𝐰𝐢𝐭𝐡 𝐥𝐢𝐦𝐢𝐭𝐞𝐝 𝐩𝐫𝐨𝐱𝐢𝐦𝐢𝐭𝐲 𝐭𝐨 𝐭𝐡𝐞 𝐛𝐮𝐬𝐢𝐧𝐞𝐬𝐬. Most meet a few times a year, across time zones and agendas. Even the most seasoned directors can struggle to connect cross-functional dots, reconcile competing views and keep pace with the complexity of today’s enterprises. 𝐈𝐧 𝐭𝐡𝐞 𝐠𝐚𝐩 𝐛𝐞𝐭𝐰𝐞𝐞𝐧 𝐨𝐯𝐞𝐫𝐬𝐢𝐠𝐡𝐭 𝐚𝐧𝐝 𝐮𝐧𝐝𝐞𝐫𝐬𝐭𝐚𝐧𝐝𝐢𝐧𝐠, 𝐀𝐈 𝐢𝐬 𝐬𝐭𝐚𝐫𝐭𝐢𝐧𝐠 𝐭𝐨 𝐟𝐢𝐧𝐝 𝐢𝐭𝐬 𝐟𝐨𝐨𝐭𝐢𝐧𝐠. In an experiment by The Wharton School and INSEAD, researchers compared human boards with an AI “board” trained on the same governance protocols. The results were telling: - The AI board made 𝐜𝐥𝐞𝐚𝐫𝐞𝐫, 𝐟𝐚𝐬𝐭𝐞𝐫 𝐝𝐞𝐜𝐢𝐬𝐢𝐨𝐧𝐬, moving naturally from facts to trade-offs to implementation. - It surfaced data in 𝐫𝐞𝐚𝐥 𝐭𝐢𝐦𝐞, flagged inconsistencies and proposed concrete next steps. - It even ensured 𝐞𝐯𝐞𝐫𝐲 “𝐯𝐨𝐢𝐜𝐞” 𝐢𝐧 𝐭𝐡𝐞 𝐫𝐨𝐨𝐦 𝐰𝐚𝐬 𝐡𝐞𝐚𝐫𝐝. But 𝐰𝐡𝐞𝐫𝐞 𝐭𝐡𝐞 𝐚𝐥𝐠𝐨𝐫𝐢𝐭𝐡𝐦𝐬 𝐞𝐱𝐜𝐞𝐥𝐥𝐞𝐝 𝐢𝐧 𝐬𝐭𝐫𝐮𝐜𝐭𝐮𝐫𝐞, 𝐭𝐡𝐞𝐲 𝐟𝐞𝐥𝐥 𝐬𝐡𝐨𝐫𝐭 𝐢𝐧 𝐬𝐮𝐛𝐬𝐭𝐚𝐧𝐜𝐞, 𝐩𝐚𝐫𝐭𝐢𝐜𝐮𝐥𝐚𝐫𝐥𝐲 𝐨𝐧 𝐭𝐡𝐞 𝐡𝐮𝐦𝐚𝐧 𝐞𝐥𝐞𝐦𝐞𝐧𝐭𝐬 𝐭𝐡𝐚𝐭 𝐝𝐞𝐟𝐢𝐧𝐞 𝐞𝐟𝐟𝐞𝐜𝐭𝐢𝐯𝐞 𝐠𝐨𝐯𝐞𝐫𝐧𝐚𝐧𝐜𝐞: 𝐭𝐫𝐮𝐬𝐭, 𝐞𝐦𝐩𝐚𝐭𝐡𝐲, 𝐜𝐨𝐮𝐫𝐚𝐠𝐞, 𝐞𝐧𝐜𝐨𝐮𝐫𝐚𝐠𝐞𝐦𝐞𝐧𝐭. The relational dynamics of governance are irreplaceable. Yet boards can should learn from AI when it comes to structure: 𝐁𝐫𝐢𝐧𝐠 𝐦𝐨𝐫𝐞 𝐝𝐢𝐬𝐜𝐢𝐩𝐥𝐢𝐧𝐞 𝐭𝐨 𝐝𝐞𝐥𝐢𝐛𝐞𝐫𝐚𝐭𝐢𝐨𝐧. Use AI to support better sequencing from facts → options → trade-offs → decisions, rather than jumping straight to opinions. 𝐁𝐞 𝐢𝐧𝐭𝐞𝐧𝐭𝐢𝐨𝐧𝐚𝐥𝐥𝐲 𝐢𝐧𝐜𝐥𝐮𝐬𝐢𝐯𝐞 𝐨𝐟 𝐚𝐥𝐥 𝐯𝐨𝐢𝐜𝐞𝐬. AI “chairs” pulled every participant into the discussion; human chairs often default to the loudest or most senior voice. 𝐄𝐦𝐛𝐫𝐚𝐜𝐞 𝐜𝐨𝐦𝐩𝐥𝐞𝐱𝐢𝐭𝐲. Instead of detaching from difficult topics, boards should use AI to break down complexity with frameworks, scenarios and relevant insights. 𝐀𝐈 𝐰𝐢𝐥𝐥 𝐧𝐨𝐭 𝐫𝐞𝐩𝐥𝐚𝐜𝐞 𝐛𝐨𝐚𝐫𝐝𝐬, 𝐛𝐮𝐭 𝐛𝐨𝐚𝐫𝐝𝐬 𝐭𝐡𝐚𝐭 𝐟𝐚𝐢𝐥 𝐭𝐨 𝐢𝐧𝐭𝐞𝐠𝐫𝐚𝐭𝐞 𝐀𝐈 𝐢𝐧𝐭𝐨 𝐡𝐨𝐰 𝐭𝐡𝐞𝐲 𝐩𝐫𝐞𝐩𝐚𝐫𝐞, 𝐝𝐞𝐥𝐢𝐛𝐞𝐫𝐚𝐭𝐞 𝐚𝐧𝐝 𝐝𝐞𝐜𝐢𝐝𝐞 𝐫𝐢𝐬𝐤 𝐛𝐞𝐜𝐨𝐦𝐢𝐧𝐠 𝐚 𝐛𝐨𝐭𝐭𝐥𝐞𝐧𝐞𝐜𝐤 𝐫𝐚𝐭𝐡𝐞𝐫 𝐭𝐡𝐚𝐧 𝐚 𝐯𝐚𝐥𝐮𝐞-𝐚𝐝𝐝𝐢𝐧𝐠 𝐚𝐬𝐬𝐞𝐭. The mandate is clear: 𝐛𝐨𝐚𝐫𝐝𝐬 𝐦𝐮𝐬𝐭 𝐚𝐜𝐭𝐢𝐯𝐞𝐥𝐲 𝐚𝐝𝐨𝐩𝐭 𝐀𝐈 𝐚𝐬 𝐚 𝐜𝐨𝐫𝐞 𝐠𝐨𝐯𝐞𝐫𝐧𝐚𝐧𝐜𝐞 𝐭𝐨𝐨𝐥, embedding it into board packs, committee work and strategy discussions, to enhance the quality, speed and inclusivity of their oversight.