The purpose of boards has remained largely unchanged. Boards have and continue to exist as oversight bodies to:

• Ensure fair practices

• Protect shareholders

• Prevent malfeasance

What is changing is the means: Artificial Intelligence (AI) now provides a better platform to do the work boards have always done.

For as long as boards have existed, they have operated at a structural disadvantage. Directors answer for a company they do not run, and most of what they learn reaches them through a single channel: the management team they are meant to oversee. Few teams set out to mislead, but the board package is assembled by management, the framing is theirs, and it is often of significant length to read prior to a meeting.

AI will not make the decisions but rather leave those who do better prepared and more capable of doing so... in essence, AI should be used to inform, not decide.

In practice this presents a small concern that the board is seeing the company in the way that management has chosen to present it. This now matters more than it once did. A director's remit has stretched from a focus on financial performance, audit, legal and compliance to include cybersecurity, geopolitical risk, climate financial risk, supply chain integrity, human capital, regulatory divergence, and reputational risk, all under a level of public scrutiny and personal liability that an earlier generation of directors never faced.

Today, AI is helping to provide much needed utility and support. Technology and AI can now be used as a medium of oversight in its own right. Applied thoughtfully, it allows directors to comprehend more relevant information that is given to them, frame sharper questions, and spend time on judgment rather than on reading and retention.

Essentially, AI can be leveraged today to support board efforts, rather than just being a governance concern.

Closing the information gap

The clearest advantage is the board package. AI can help work through a package that may be several hundred pages in length and quickly distil each section, point to what deserves attention, and note what is absent. It can also propose pointed questions against each agenda item, so directors are ready to obtain answers to the questions they need.

It also supports independence. Rather than relying solely on management's account, a director can ask AI to compare the company's disclosures against peers, test the numbers against outside market data, and read the board's own back catalogue of materials for trend analysis. PwC reports that 35% of directors have now incorporated AI and GenAI in their oversight work to track trends, benchmark peers, evaluate performance and pressure-test strategy. The benefit is a board that arrives with an informed viewpoint of its own.

Focused preparation, targeted questions

AI can also support administrative efforts through drafting meeting minutes, carrying action items from past meetings, logging attendance, and keeping a record of which commitments were made and met. With less time lost to administrative work, directors can focus on the items that really matter. The same means can also examine a company's own performance measures against outside data, letting a board pressure-test a capital-allocation choice before the vote rather than explain it afterward.

A mirror for the board itself

Boards have never found it easy to judge their own performance objectively. Using agendas, committee charters, and skills matrices, set against a wide body of peer disclosures and governance codes, AI can show directors where their time actually goes and how that compares with good practice elsewhere. The result is evidence behind the decisions most closely tied to long-term performance: a) how a board evaluates itself, b) its capacity and composition; and c) its current and future capabilities.

Director and management evaluation

Today directors are assessed manually, but AI is helping to change this. A director's entire career of decision making, including voting decisions, attendance, committee contributions and much more, can increasingly be reviewed, analysed and scored by AI.

These AI-generated scorecards can also be extended to management. Through AI, CEO and management decision-making can increasingly be assessed on a more continuous basis and benchmarked against peers. With this, continuous rather than quarterly assessment can be conducted.

Compensation and succession planning, which are today shaped heavily by judgment and relationships, are also able to be informed by a far more comprehensive AI analysis.

The Evidence is in the Numbers

MIT's Center for Information Systems Research reported that companies whose boards have digital and AI expertise sit 10.9 percentage points above their industry's average return on equity, while those without it sit 3.8 percentage points below.

Despite the adoption of AI remaining slow with McKinsey reporting that only 39% of Fortune 100 companies disclosed a form of board oversight of AI and Deloitte's global survey of directors finding that 66% say their boards have 'limited to no knowledge or experience' with AI, there is a clear opportunity here to increase board effectiveness.

The trade-offs are real

It is important to note that there are considerations and governance efforts that need to be accounted for when using AI for board efforts:

• AI outputs should always go through a human-review before a board evaluates it

• Board materials are often sensitive so company- approved tools and standardised systems must be used

• As directors' prompts and AI outputs can become part of the discoverable record, there should be agreed retention rules

The boards that are ahead of the game will follow an agreed framework that defines how and when the board will use AI tools and phase their adoption over time.

Used with balanced judgment, AI is a useful addition to the boardroom.

In the final analysis, AI will not make the decisions but rather leave those who do better prepared and more capable of doing so. That, in the end, is what board effectiveness has always meant.