Wherever one turns, one is deafened by talk of artificial intelligence (AI) and how it will influence pharma, medtech and other life sciences industries.

Some of this discussion is useful, as when it reveals the opportunities to make drug discovery faster and cheaper. Much of it is nothing more than frenzied speculation, with consultants, in particular, encouraging their clients’ FOMO (fear of missing out). At this embryonic stage of the technology, any prediction of the future is, as Niels Bohr famously said, ‘difficult and speculative’. But there is one thing we can be pretty sure of and that can guide how we surf the tsunami of AI innovation. Stay with me for few minutes while I share how a Darwinian views the times we’re living in.

Heraclitus was right when he said the only constant is change. In my research, I talk about the ‘six great shifts’ shaping our industry, one of which is a fundamental change in how we create and use information. There’s more to the information shift than AI, but it is a part of this transformation in our industry’s sociological and technological environment. And, from a Darwinian point of view, change creates new selection pressures to which some firms will adapt better than others. While Darwin never said that ‘it is not the strongest that survives, but the most adaptable’, it is still true. So, despite all the possible and unpredictable futures that AI creates, we can predict that some firms will gain from AI, some will suffer pain from it and the difference between them will be how well they adapt. This isn’t exactly an earth-moving conclusion, I accept. But it is the jumping-off point for some interesting thoughts about AI.

AI isn’t an ordinary technology. It is, in the words of Erik Brynjolfsson, a general purpose technology (GPT), one with the potential to transform the economy. Richard Lipsey and Kenneth Carlaw think that there have been 24 such technologies in the past, ranging from electricity to the factory system. What makes GPTs interesting and different from other, narrower, technologies is that it isn’t their basic technology that matters, it’s their applications. For example, electricity didn’t change the world but artificial lighting and electric motors did. Factories didn’t transform society but cheap, mass-produced goods define modern economies. So we have 24 case studies that can teach us about why some firms will gain from AI and others will enter a world of pain, as Sobchak says in ‘The Big Lebowski’.

Those 24 historical case studies teach us that AI will have innumerable applications. So many, in fact, that firms could spend every penny they have on AI and still not have enough to buy everything. Those cases also teach us that some AI applications will create value and some will be money pits. Spare a moment to remember Thomas Parker, who built the first production electric car in 1884, only to see his choice of application embarrassed by the internal combustion engine. Together, those two lessons partly answer our question about which firms will gain from AI and which will not. It isn’t the richest firms that will survive, it will be the ones that make the best choices from the myriad, countless AI investments available to them.

If you accept the lessons from earlier GPTs, you might now be asking what AI applications should a firm invest in?. That’s the wrong question. A better one is: “What applications should my firm invest in?”, because the answer is not the same for every firm. AI applications will create value when they align with and enhance your strategy and won’t if they don’t. Different firms’ strategies create value with different parts of their value chain and for different target markets. Investment in AI applications that amplify a firm’s strategy will pay off, while those that conflict with or are unsupportive of strategy will become painful money pits.

AI will change our industry and some firms will adapt better than others. From the infinite AI investment possibilities, the best firms will choose those that amplify their competitive strategies, while other firms will be distracted by the hype. The difference between them will be the ability to think strategically about AI, something I’ve written about elsewhere in a longer article.