How much governance can I leave to AI?

How much governance can I leave to AI? Once you realise its potential, it’s natural that you might ask this question. Leading a company is still a hugely rewarding career, but there are multiple responsibilities. Investors, consumers, and regulators expect more reporting, transparency, and integrity, which increases the pressure on you. Enter AI, the innovation that can automate tasks we wouldn’t have thought possible ten years ago. It’s only natural that corporate leaders might see this innovation and think, ‘bingo’, problem solved, but don’t jump that far ahead just yet. Yes, AI can help significantly with corporate governance, but we need to draw lines now between things it can easily help with things it could conditionally help with, and things it should never help with. It’s all new territory, so we need to be careful. How much governance can I leave to AI: an overview If you’ve used generative AI like ChatGPT in the last few years, you’ve probably been equally amazed and disappointed. Sometimes, it can perform complex writing tasks with just a few prompts; other times, it can’t seem to understand the difference between US and UK spelling. Still, it has quickly become clear that AI will soon be indispensable in all sectors, including corporate governance. Its particular strengths are in areas requiring data analysis, compliance tracking, and risk assessment. However, while its capabilities expand, AI is not a perfect substitute for human judgment, ethics, and strategic insight, and it likely won’t be in our lifetime. The amount of governance you can delegate to AI depends on the nature of the task, the risks involved, and the level of transparency AI provides. Routine and data-intensive tasks are ideal for automation, but decisions requiring ethical reasoning or nuanced judgment should remain firmly in human hands. What corporate governance tasks can AI do? The rule of thumb is that you should focus on repetitive, data-intensive tasks that require consistent accuracy. These include: Compliance monitoring: Properly-trained AI models can scan vast amounts of regulatory data, flagging potential violations and ensuring ongoing compliance with relevant laws. Generating reports: By aggregating and analysing data from multiple sources, AI can produce comprehensive reports quickly and accurately. Risk assessment: Predictive analytics allow AI to identify patterns and potential risks, offering actionable insights for risk mitigation. Data processing and analysis: Tasks like summarising large datasets or identifying trends are highly efficient when performed by AI. You’ll see that many of these tasks concern processing and analysing, turning mundane stuff into projects that could be completed in minutes. This frees up time for governance teams to focus on higher-level responsibilities, enhancing overall productivity. What corporate governance tasks should AI never do? Some responsibilities are too nuanced and require human judgment, making them unsuitable for AI. These include: Strategic decision-making: A human must make every strategic decision. While it’s still sci-fi territory to imagine a board letting a robot make a final call, it is more likely that a board would act on a suggested action plan generated by an AI, accepting it without question. Never do this. Ethical decision-making: Decisions with moral implications, such as addressing corporate social responsibility, require empathy and ethical reasoning. These are much less about data and much more about human nature and principles. AIs should never be involved here. Stakeholder communication. Stakeholders may be happy to hear that a company is using AI, but stakeholders will be furious if they realise AI is their primary line of communication. That’s a step too far. Stakeholders must communicate with human beings at all times. Cultural and leadership assessments: Evaluating leadership effectiveness or shaping organisational culture cannot rely solely on algorithms. Many of these points deal with areas that go a lot deeper than data and deal instead with human interaction and principles of respect. Corporate governance tasks could AI conditionally do? Certain tasks can leverage AI under specific conditions, and most of those conditions come back to adequate human oversight. Drafting governance policies: AI can use data-driven results to suggest changes in corporate strategy or policies. However, these should only ever be suggestions. The final decision rests with the human beings who use the AI. Auditing: AI can conduct preliminary reviews and highlight financial anomalies or risk. The condition is that human auditors must be present to check the work and sign off on its quality, making any changes to conclusions as necessary. Board performance evaluation: As evaluations can be time-consuming, AI could help with data collection for practical metrics like attendance and participation. However, the final assessment of a board member's performance should always require human interpretation. Trend analysis and forecasting: AI can predict market or regulatory trends, but strategic decisions based on these predictions should involve human input, and the humans involved must have a thorough knowledge of the figures being used; otherwise, the data becomes meaningless. Where conditions exist around AI, it usually means you need a person who understands the process and who can look over the AI’s shoulder and say, with confidence, that the work is sound. Conclusion AI transforms corporate governance, particularly in automating repetitive tasks and enhancing data-driven decision-making. However, its limitations make it unsuitable for responsibilities requiring ethical judgment, strategic thinking, or human interaction. A balanced approach that leverages AI’s strengths while maintaining human oversight is key to ensuring effective and responsible governance. Organisations can harness its potential while safeguarding their integrity and values. How much governance can I leave to AI - The Corporate Governance Institute

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