Why CEOs need to get involved with artificial intelligence
Tuomas Syrjänen, co-founder AI Renewal at Futurice, explains why CEOs need to ‘get down and dirty’ with artificial intelligence
Artificial intelligence is more than just hype now, the technology has already found its way into multiple areas of our lives. It’s in the digital ads we view online every day. It’s in our health apps and in our digital playlists. It’s changing how we interact with brands and how we interact with each other.
The technology is also increasingly powering our businesses. AI’s ability to enable new ways of competing – including transforming business models, together with understanding possible risks and ethical issues – mean that embracing this new technology should be part of every future-facing CEO’s job spec.
Unfortunately, this isn’t always the case, with many leaders still seeing it as something to be delegated to CTOs. That approach is no longer fit for purpose. CEOs prepared to get down and dirty with AI give their companies the best chance of staying relevant in a world where business decisions are increasingly automated, and data driven.
Here are four steps that CEOs can take to get more involved in AI:
Do you know the difference between AI and machine learning? How about deep learning? Try regression and classification for size. Getting to grips with the basics of AI ensures CEOs understand the risks and opportunities this new technology presents as well as equipping them to be part of the conversation about AI and how it can affect their business.
It won’t mean having to learn how to write Python code. But it does require business leaders to gain an understanding of how different algorithms support what is possible as well as what the pitfalls and the trade-offs are. Developing this technical understanding enables business people to envision and innovate solutions to their business problems and empowers them to challenge their technical teams in a constructive way.
If a CEO isn’t on first name terms with their data scientists and technologists, then they may have a problem. One of the biggest challenges in converting AI visions into reality is bridging the knowledge gap between business people and data scientists. Business leaders tend to understand the commercial landscape, but not how AI can be applied to solve existing problems or to create new opportunities.
