AI gaps in the boardroom are becoming a reputational risk; Axios, April 2, 2026

Eleanor Hawkins, Axios; AI gaps in the boardroom are becoming a reputational risk

"The big picture: Companies across every industry are being forced into rapid AI-driven transformation, but many corporate boards lack the expertise to guide strategy, manage risk or communicate decisions credibly to stakeholders.

By the numbers: Only 39% of Fortune 100 boards have any form of AI oversight, such as committees, a director with AI expertise, or an ethics board, according to McKinsey research.

Another recent report found that only 13% of S&P 500 companies have at least one director with AI-related expertise.

Similarly, McKinsey's survey of directors found that 66% say their boards have "limited to no knowledge or experience" with AI, and nearly one in three say AI does not even appear on their agendas.

And a report from the National Association of Corporate Directors (NACD) found that only 17% have established an AI education plan for directors, and 6% have a dedicated committee to oversee AI.

Between the lines: Having an AI-savvy board is a major competitive advantage, according to a recent MIT study."

Ethical and Responsible AI: A Governance Framework for Boards; Directors & Boards, August 27, 2024

Sonita Lontoh, Directors & Boards; Ethical and Responsible AI: A Governance Framework for Boards 

"Boards must understand what gen AI is being used for and its potential business value supercharging both efficiencies and growth. They must also recognize the risks that gen AI may present. As we have already seen, these risks may include data inaccuracy, bias, privacy issues and security. To address some of these risks, boards and companies should ensure that their organizations' data and security protocols are AI-ready. Several criteria must be met:

• Data must be ethically governed. Companies' data must align with their organization's guiding principles. The different groups inside the organization must also be aligned on the outcome objectives, responsibilities, risks and opportunities around the company's data and analytics.
• Data must be secure. Companies must protect their data to ensure that intruders don't get access to it and that their data doesn't go into someone else's training model.
• Data must be free of bias to the greatest extent possible. Companies should gather data from diverse sources, not from a narrow set of people of the same age, gender, race or backgrounds. Additionally, companies must ensure that their algorithms do not inadvertently perpetuate bias.
• AI-ready data must mirror real-world conditions. For example, robots in a warehouse need more than data; they also need to be taught the laws of physics so they can move around safely.
• AI-ready data must be accurate. In some cases, companies may need people to double-check data for inaccuracy.

It's important to understand that all these attributes build on one another. The more ethically governed, secure, free of bias and enriched a company's data is, the more accurate its AI outcomes will be."

More CEOs are getting forced out for ethics violations; Washington Post, May 15, 2017

Jena McGregor, Washington Post; More CEOs are getting forced out for ethics violations

"If it seems like more CEOs are getting cast aside amid ethical blunders or corporate scandals, they are. According to a new report on CEO succession from Strategy&, PwC’s strategy consulting business, the percentage of CEOs getting pushed out for questionable behavior — lapses including environmental disasters,  insider trading, résumé fraud, accounting scandals and sexual misconduct — is up over the past five years."