5 things for a CEO to consider before investing in AI
In September 2019, a Tech Nation report showed that investment in the UK’s artificial intelligence (AI) companies reached a record high. The first six months of 2019 saw more investment in the tech than the entirety of 2018. Will it be the same this year?
Here are five pointers for anyone who wants to get more from AI and doesnt know where to start.
1. Beware of the snake oil salesman
AI has become so ubiquitous that lots of people are unclear about what it really means. Leaving some buyers open to shadier traders who can rebrand their software as AI, bump up the price tag a bit and sell it as if it’s a shiny new toy.
Now, Im sure a vendor wouldnt do that but when evaluating an AI product, it is important to ask: does it learn and improve? True AI gets better as it crunches more data. It makes better decisions and provides better insights. If it doesnt learn, it might still be useful, but it’s not really AI. Ask to see evidence that it actually has the software to learn.
2. Is it beneficial?
The AI buzz is exciting. However, just because it’s trendy and exciting doesnt mean you actually need it. It does you no favours to sell people products that they don’t really need it will always backfire in the long term and it’s annoying that some companies do it.
When shown a fancy new tool, ask what the benefit will be. Will it save money or make money? Will it free staff for more important tasks? Will it give customers a better experience? The cost/benefit analysis is obvious to most chief executives, but Ive seen plenty of people get carried away by the desire for the latest tech.
3. Is it explainable?
AI can sometimes look a bit magical and who doesnt love a good magic trick? Any magician worth their salt will never reveal how the trick is done; they would get sawn in half if they did. The same is not true of an AI vendor: they should be sawn in half if they don’t reveal how it’s done (Not literally of course).
A survey of 5, 000 executives found that 60 per cent of them are worried about explaining how AI uses data to make decisions, because of the regulatory and compliance risks of not knowing.
This is an entirely reasonable concern. If AI is being used for important decisions and a regulator launches an investigation or a customer requests their data under GDPR, then companies need access to information that explains what happened. Our black box told us to do it? is unlikely to be a popular excuse. Make sure the vendor explains how it’s done.
4. Make sure you own the data
it’s a company’s data that is being fed into the AI, but the algorithm and the code belong to the vendor. The AI uses data to get smarter and, if not careful, the vendor will then be able to sell the AI to rivals, who get a smarter tool that they didnt pay to train. When signing up, make sure that the training data is protected and stays that way throughout the process.
5. If in doubt, call a doctor
As the Tech Nation report shows, AI is at the cutting edge of computing right now, so it’s understandable that a lot of people don’t understand how it works. That includes customers and, sometimes, even people who work for vendors. One trick for starting with new technology like this is to test it in a small area of business and evaluate its success before investing further.
However, because it’s hard to see inside the black box, even a trial might not reveal what you need to know. One option, in that case, is to speak to academics. Has the vendor allowed academics to independently evaluate their tech? If not, why not? That could be a red flag. Even if independent studies are not available, there are academics who can help ask the right questions.
There is a lot to consider when investing in AI perhaps more than with other IT tools. Hopefully, this list has helped clarify some of the questions that will make the process clearer.