The future of firms in an AI world

Whatever we think about them, we can all agree on one thing: computers are brilliant. They can process vast amounts of data. They can do so at an astonishing speed. (How long would it take you to work out the cube root of 36,264,691? Ages – if at all. Yet within a split second, a computer gives you the answer – 331.) And computers are becoming ever smarter. It is now decades since they showed their ability to do humdrum calculations such as finding a cube root. Now they can plan the quickest route to drive from A to B, avoiding traffic jams, and tell us our arrival time. They can predict pretty accurately how many cartons of milk a shop is likely to sell in two days’ time. They can recognise faces. They can steer a car through heavy traffic.

This exponential growth in computing power will not stop. Robots will become increasingly deft at performing tasks we currently see as the unique preserve of humans. They will become more and more skilled in interrogating patterns of behaviour by individuals and organisations and then suggesting better ways that tasks can be accomplished. Artificial intelligence (AI) will surround us even more than it does today. Within a couple of decades, the tech evangelists maintain, it will be able to replicate everything the human is capable of.

A computer will be able to hold a genuinely stimulating conversation. It will be able to devise and perform a seriously funny comedy routine. It will be able to choose the right clothes for your day ahead, iron them and lay them out ready for when you step out of the shower. It will be able to make you feel loved.

Well, maybe. But let’s be clear about what AI can and cannot do. Its “intelligence” is essentially an ability to process and build upon what has gone before. Certainly, computers already have a capacity for “deep learning” – spotting patterns, interpreting them and coming up with something new. (In the board game Go, for example, computers have already shown they can devise genuinely new strategies.)

Call that creativity if you like, but it is creativity that is confined within a narrow set of boundaries: it is about drawing an inference from past experience.

So how does all this relate to the future of work, the future of organisations and the future of the way those organisations are managed? It is already commonplace for accounts to be drawn up with only the smallest human intervention: AI does the basics. AI can scour thousands of documents to find relevant precedents in putting together a legal case. Increasingly, such work and a myriad of other tasks will be executed by AI: the humans who hitherto earned a living doing these things will be redundant.

Those performing more creative, less mechanistic tasks at what we can loosely call the top end of the employment scale should escape this cull of their jobs. Those who work in areas such as providing care for the sick and elderly or serving in restaurants should also continue to see demand for their skills: empathy still counts for something. Hence, as the well-worn argument goes, the increasing application of AI will lead to a hollowing-out of the middle in the jobs market, while those at the top and bottom should see their roles change but endure.

But what does the increasing application of AI imply for companies? Certainly, for a company to survive, it will have no option but to adopt labour-saving, cost-cutting technologies. It will have to strive to match the operational efficiency of its competitors, who will all be doing the same thing. And of course, it will also need fewer employees. But all this does no more than get a company onto the starting grid.

To win the race, it needs to make decisions about which customers to target and what new products or services might be devised to attract them. Here, AI’s limitations are revealed. Decisions such as these require intuition, imagination – and, crucially, an ability to pull together items of information from many different sources. Lateral thinking involves far more than computing power, however vast. No computer ever dreamed up a cool new brand.

Compare venerable British high street institution John Lewis and Amazon, for example. John Lewis is a retailer. So is Amazon. John Lewis will use computing power for routine tasks such as invoicing and stock control: it tries to achieve operational efficiency. But given Amazon’s vast resources, John Lewis will never be able to do more than play catch-up in terms of delivering a given product at a lower cost. In terms of sheer efficiency, it cannot beat Amazon.

So, what to do? The crucial point is that John Lewis and Amazon are not mirror images of one another. Amazon delivers goods to your door after you have ordered them online; the whole process has virtually no human involvement.