The question is no longer whether companies should start using AI, but where they should begin. AI is changing every industry, role and product. That means every board needs to ensure that its company has a clear strategy and priorities for where AI can genuinely make a difference.

But here is what I believe is important to keep in mind: AI is not the strategy. The strategy is your business strategy – the services you provide and the value you create for your customers. That should remain the board’s long-term focus. What needs to change is the role AI plays in delivering that strategy.

It applies to every company – but in different ways

There is no industry, role or product where AI is not changing how customers behave, how competitors deliver their services or how value is created. All companies can benefit from AI, and they need to adapt to it to remain competitive.

For smaller companies, AI can provide superpowers, enabling them to do and offer things that were simply not possible before. For larger companies, it can help them rethink business models, improve efficiency and respond to competitive moves their peers are already making. The scale differs; the relevance does not.

The board’s role – asking the right questions

The board’s role is not to understand the technical aspects of AI or the details of every project the company is running. Its role is to ensure that management has a clear plan for how AI will help the company achieve its goals.

That means asking: Where will AI make a difference for us? Which use cases and pilot projects are currently under way? How is management measuring whether AI is creating value? The answers will help the company determine what to scale, which risks are increasing and where the real opportunities lie.

There is no industry, role or product where AI is not changing how customers behave, how competitors deliver their services or how value is created.

Three pieces of advice

1. Start with the business problem – not the technology
What specific challenge facing your customers or your company are you trying to solve? AI does not solve anything on its own. It can help address the particular challenges to which it is applied. Always start with the problem, not the tool.

2. Establish clear principles for data, accountability and use
Once you start applying AI, you need clear principles governing which data is used, who is accountable and which guidelines employees should follow. It is equally important to agree on where the company is comfortable using AI – and where it should not yet be used. Without this framework, adoption becomes fragmented and risks become more difficult to identify.

3. Measure the impact before scaling
Many AI projects begin as small pilots – promising, but not yet proven. They should be scaled only once you know that they create real value. From the outset, be clear about how that value will be measured. Track the results and make sure the solution delivers a meaningful impact before committing to scaling it.

 

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