AI has quickly become a board-level priority, yet few members have knowledge or experience to make strategic decisions about its use. CIOs can take the lead in educating them. Here’s how.
More three-quarters of executives and board members (79%) say their boards have limited, minimal or no knowledge or experience with artificial intelligence (AI), according to a 2024 Deloitte Survey. Just as alarmingly, almost 45% of these respondents say AI is not even on their board’s agenda.
That’s a problem.
As AI reshapes the competitive landscape, boards are under growing pressure to determine what AI means for their organizations’ future. Yet many are ill-equipped to grapple with the strategic, ethical, and operational implications of a broad set of capabilities they barely understand.
That knowledge gap presents a significant risk. But it’s also an incredible opportunity for today’s CIOs to lead the conversation, helping their boards not only understand AI, but also make informed, mission-aligned decisions about how the companies they oversee adopt, govern, and scale AI.
Why CIOs Should Lead: A Win-Win Proposition
IT leaders are uniquely qualified to educate boards about AI — both how it works and how to best usher in its promise while protecting against potential perils. CIOs have decades of experience with technology-enabled transformation, from the internet to mobile computing to cybersecurity and cloud services. Today’s IT leader has the combination of business domain knowledge and technology knowhow to help their boards develop sound strategies to provide AI oversight and support AI-enabled innovation.
Leading the AI conversation with their boards offers benefits for both CIOs and their organizations. CIOs understand both the technical and business implications of AI. They are highly skilled at aligning mission-critical objectives and enterprise risk frameworks while maintaining regulatory compliance, ethical integrity, and operational resilience. Sharing this knowledge sets the CIO up as a trusted advisor – at a time when boards need straightforward insights into AI’s business potential and help understanding the most effective strategies for innovation. This further cements the CIO’s role as a strategic business leader, a prerequisite for long-term success and future CXO-track leadership roles.
A Framework to Guide the AI Conversation
To engage the board effectively, it’s essential to focus on strategy, risk, and value. It’s critical to elevate the conversation beyond a technical discussion.
Veteran CIOs have experience doing this with other technology-driven transformations. AI, however, presents both wide-reaching opportunities and considerable risks for the business. So, it’s important to think through how to lead an effective conversation with the board about AI. Following is a simple structure that can be useful:
- Context: Why This Matters Now
CIOs can highlight the disruptive impact of AI on the company’s industry, competitors, and customers. Sharing examples of how AI is driving value, improving efficiency, or enabling new business models can help to illustrate both the pace of change and the cost of inaction.
- Current State: External and Internal
Next, the IT executive can articulate the current state of the market and assess how the organization compares. This will involve sharing the external state of affairs: what the organization’s peer groups are doing, where AI investment is flowing, and what regulators are saying or doing. It will also include a primer on what’s taking place inside the company: what AI pilots or initiatives are already underway, what data gaps may exist, and what talent is required. It can be easy to get into the weeds here, so using a maturity model or visual snapshot will help to keep this concise and at an appropriately high level.
- Implications: Risks and Opportunities
This is the heart of the conversation, where CIOs can lay out both the promise and peril of AI. Boards want to know what could go wrong, what could go right, and how the organization is managing both. Examples of opportunities might include increased productivity driven by leaner, AI-augmented teams; faster execution of business workflows powered by AI processing and 24x7 capabilities, and re-imagined business models that can drive improved outcomes and new customer experiences. Risks are likely to include bias and ethical concerns in model outcomes, data privacy and compliance exposure, talent shortages, cultural resistance, and reputational damage resulting from irresponsible use of AI.
- Next Steps: Strategic Roadmap
Without overwhelming the board with too much detail, the CIO can then outline a suggested direction. This roadmap can cover the following.
a. Vision and priorities: An outline of the goals and desired outcomes of the program. In the short term, this may include an initial discovery phase. Longer term, it should include targeted business metric improvements (e.g., reduction in manual efforts, cost savings, improved customer satisfaction). Given the capabilities of AI, these improvements may also be qualitative and can include a vision of re-imagined business models and business processes to achieve the vision.
b. Investments: Funding, talent, platforms (e.g., Anthropic, OpenAI, Google, Microsoft), and partnerships required.
c. Governance: The framework, constructs, and processes the organization will use to oversee and ensure responsible and ethical AI development and use, security, regulatory compliance, and ROI.
d. Timeline: High-level milestones or checkpoints, aligned to key deliverables and outcomes and delivered at quarterly intervals (at a minimum).
A CIO’s Call to Action
Boards don’t need a crash course in large language models; they need a strategic lens on how AI will shape performance, growth, and risk over the next one to three years. The IT leader’s role is to equip them with knowledge, align AI with business priorities, and lead responsibly.
CIOs can keep a few principles in mind when presenting to the board:
- Always speak in business terms, not technical jargon. For example, don’t outline the latest performance of the AI models such as MMLU (Massive Multitask Language Understanding) scores; rather discuss the business outcomes (e.g., cost savings, revenue increase) that they will enable.
- Align the AI discussion with the organization's mission and strategy.
- Use visuals like charts and graphs (not spreadsheets) to explain data and risk.
- Provide real examples of use cases and outcomes.
- Keep things at a strategic level and resist diving into detailed discussions. For example, instead of going deep into the pros and cons of GPT vs Anthropic LLMs, instead discuss how the AI toolsets will be integrated into the company’s ecosystem, including organization change management considerations.
Winning in the age of AI isn’t only about speed — it’s about smart, aligned decisions backed by strong leadership and governance. The future will be shaped in boardrooms that grasp the power of AI—and CIOs can make sure theirs is among them.
