By Sonny Iroche
In today’s corporate environment, the expectation on boards is evolving: no longer enough to be stewards of finance and compliance, board directors increasingly must bring, or at least grasp, artificial intelligence (AI) and technology literacy. In Africa, where digital transformation is accelerating, the question is not just whether boards should have AI-trained members, but how quickly they must adapt.
Below is a breakdown of why this shift is happening, examples from global and African practice, caveats, and the path forward for African boards.
Why the Expectation Is Rising
1. Strategic imperative of AI
As AI becomes central to business models, operations, and competitive advantage, boards must supervise AI strategy, investments, risk management, governance, and integration.
2. Risk, ethics & regulatory pressure
The adoption of AI brings new challenges: algorithmic bias, data privacy, regulatory compliance, reputational risks, robustness of Large Language Models (LLM) and Machine Learning (ML) models, and explainability. Boards must either have competence on these issues or ensure access to reliable expert scrutiny.
3. Signaling to investors & stakeholders
Having AI or data science expertise on a board signals seriousness about digital transformation. Many investors, especially institutional ones, are beginning to expect boards to list “AI, data, tech background” among desired qualifications.
4. Evolving governance frameworks
Regulators, central banks, and governance bodies (e.g. banks’ regulators, insurance commissions) are beginning to issue AI governance roadmaps and maturity models. Over time, they may require more explicit board-level AI oversight structures.
That said, today it is rarely a formal requirement to have a full AI scientist as a director. Still, appointing one or two certified, qualified experts is becoming a serious consideration. Many boards still depend on external advisors, special committees, or training of existing directors.
Examples of Boards with AI / Technical Expertise
Below are some real illustrative cases.
• Amazon: In April 2024, Amazon announced the appointment of Andrew Ng, a globally recognized AI researcher and entrepreneur, to its board of directors.
• OpenAI: In January 2025, Adebayo “Bayo” Ogunlesi, Nigerian-born infrastructure investor and financier, joined the board of OpenAI.
• Fortune 100 firms: It is becoming increasingly important for many large companies now to include AI or data background among director qualification criteria (or “desired attributes”).
• Algorithmic observers / virtual board members: Some commentators refer to experimental practices, such as firms appointing algorithmic agents or “bots” as non-voting observers in board meetings or using automated evaluation.
• Deep Knowledge Ventures (Hong Kong): One oft-cited provocative example is that Deep Knowledge Ventures used an algorithm (“VITAL”) to vote or help evaluate decisions. However, whether that is strictly equivalent to a “board seat” or typical governance standard is debated. (This remains more of a curious case study than a best practice benchmark.)
Caveats & Practical Realities
• Not every board member needs to be a full AI scientist. What matters more is AI literacy, plus structured access to expert support (e.g. advisors, committees, external reviewers).
• The sector and scale matter: companies deeply invested in AI (technology firms, fintechs, data-driven businesses) will make this shift earlier.
• Governance architecture often evolves first: many firms establish AI / algorithm review committees, internal audit of ML models, ethics oversight units, or AI risk functions before reconstituting board composition.
• Symbolic vs substantive roles: the mere presence of an AI expert is insufficient. True effectiveness depends on integration, whether the expert is included in key deliberations, committee mandates, due diligence, assessments, and strategy.
Boards and AI in Africa: Current Landscape
• Governance codes: South Africa’s King IV code places emphasis on technology and information governance under Principle 12, which many listed companies in Africa adopt or reference.
• Corporate policies and structures: MTN Group has published a Responsible AI Policy and created executive-level subcommittees focusing on AI and governance.
• Banking sector momentum: Some banks in Africa are publicly discussing AI posture at shareholder meetings; others are rolling out internal AI risk or ethics training that would fall under board oversight.
Notable African / Nigerian disclosures and practices
• Vodacom (South Africa): As a company subject to King IV, its board oversight of “technology and information governance” is standard; this is a foundation upon which AI oversight can be layered.
• MTN Group: Its governance disclosures and public statements reference “responsible AI” in its digital, tech, or ethics agenda.
• Standard Bank: Leadership statements and reports indicate board-level attention to AI and data risks; internal training and reporting are being elevated.
• Nigeria (banks and insurers): Many listed banks and insurers already maintain board-level IT / Technology / Digital committee structures as part of their compliance with the Nigerian Code of Corporate Governance (NCCG). That makes them well-positioned to evolve into AI oversight roles:
• UBA: Discloses ongoing director training and technology oversight within its committee structures
• Access Bank / Access Holdings: Board Digital & Information Technology Committee (charter includes strategy, risk, reporting)
• Fidelity Bank: Board Information Technology Committee oversees IT/digital strategy, investments, governance, risk
• GTCO (Guaranty Trust Holding Co.): Maintains an Information Technology Strategy Committee
• Zenith Bank: Recognizes IT risk as a standing board oversight category
•Heirs Insurance Group already has an AI expert on its board and has had few board level trainings on AI use cases in the insurance sector.
• AXA Mansard: Includes board-level risk & technical committee structures, where AI risk can be integrated
These examples validate that the institutional foundation (board-level tech/IT oversight) largely exists; the challenge is advancing from “IT governance” to “AI governance” in a deliberate, structured manner.
Why This Matters Globally & for Africa
• Disclosure in global markets is evolving: many companies now identify that AI oversight is allocated to a board committee (e.g. audit, risk, technology). External reviews (e.g. by Big Four firms) show growing emphasis on board AI competence.
• African issuers will not be insulated from cross-border investor expectations, ESG (environmental, social, governance) criteria, and capital flows. As more investors insist on robust AI governance, boards lacking competence may be viewed as weak or under-governed.
Bottom Line & Recommendations
• There is no universal rule today requiring every board to include a fully AI-trained director.
• But for regulated, data-intensive, or tech-led sectors (e.g. banking, telecoms, insurance, fintech), investors and governance codes will increasingly expect:
1. Board-level AI literacy
2. Clear committee ownership (risk, technology, audit) for AI oversight
3. Access to qualified AI advisors or directors when AI is material to strategy, operations, or risk
If Nigerian and indeed African boards can move in this direction proactively, they will not just be catching up, they may leapfrog, building governance that is fit for the AI age.
About the Author & Credentials
Sonny Iroche is the CEO of GenAI Learning Concepts Ltd, a leading AI consulting and training firm in Nigeria; a Senior Academic Fellow (2022–2023) at the African Studies Centre, University of Oxford; holds a Postgraduate Degree in Artificial Intelligence for Business from Saïd Business School, Oxford; and serves as a Member of Nigeria’s National AI Strategy Committee and of the UNESCO Technical Working Group on AI Readiness Assessment Methodology.
He also sits on the boards of Heirs General Insurance and Arco Group Nigeria.
