5 AI tips every C-suite leader should follow

graph of UK business adoption of AI

Foreseeing and keeping up with changes in business risk is always at the top of business leaders’ minds but, when we are dealing with opportunities and threats outside our sphere of expertise, fear of damaging the business by not spotting a new threat can keep us awake at night.

At a presentation I gave last week, I asked the audience how far down the line they were with artificial intelligence (AI) in their businesses. Most said they were not confident in making decisions about investing in AI. Only 5% had deployed AI with a further 5% at the pilot stage. A massive 58% reported they were in the early stages of considering AI and 29% had not yet started looking at it. Take a look at the graph below and you’ll see that these rates are lower than the rates reported by the UK Government in its new study of AI adoption in UK businesses.

Graph showing UK government statistics on UK business adoption of AI

The audience last week had fewer large businesses and more SMEs than the Government study which may be the reason for the lag. I find in conversations even with large businesses that very few Board members are confident about not missing out on the advantages of AI and they all worry – rightly – about falling into one of the many pitfalls of AI that can damage a business severely.

So if you want to move from the AI hesitant majority to dealing with AI confidently, here are five tips that every C-suite leader should follow:

  1. Know your data
    To get started with AI and make progress, the Board need to truly understand the data they have and what data they could acquire. Regulations around data are tightening all the time (rightly so) and Boards should have zero tolerance for any use of data for the wrong purposes. The reputational and financial risks of getting this wrong should be at the top of leaders’ minds.
  2. Solve real business problems
    Most businesses start small with AI, perhaps testing out a machine learning algorithm to see whether it can predict, personalise or automate in a useful way. It’s too easy to leave it to a small team to think up AI use cases (especially if this avoids the Board having to declare they don’t know how to direct this aspect of the company’s activities). The Board need to have discussions with a wide range of stakeholders to talk about what AI could do before narrowing down the use cases that solve real business problems.
  3. Ask if AI is the right tool
    AI isn’t always the right tool for the job but it’s easy to get carried away with its shiny newness and try to badge everything as solvable by AI. Spend time getting to know alternative solutions and make sure your team know that they can come back to you with non-AI solutions too.
  4. Think about ethics and governance from the start
    Again and again leaders tell me they’ll get round to thinking about ethics and governance later. But there are two key reasons why this is wrong-headed. First not thinking about AI and data governance and ethics increases the risk of making a mistake that will damage your reputation and could have financial penalties too. Second if you don’t have strong governance practices from the outset, regulation will force this on you soon enough so do you really want to have to unpick successful parts of your business to try to inject better standards later on?
  5. Don’t get tangled in the war for talent
    Wage inflation across the economy is spiralling up and, with demand for data and AI specialists far outstripping supply, their pay is sky-rocketing. It makes no sense to enter this war for talent so the solution is to find people internally who have a leaning towards data and logic and train them yourself. Make sure you also train your Board members to increase their confidence so they are ready and willing to invest in your AI future.

If you have questions, want more detail or advice on anything in this article, contact sue.turner@aigovernance.co.uk or call 07858 908046.

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