AI is not a Business Strategy

There is a question Martin Kay likes to ask a room, and he asked it at AI for Good Wellington: who here remembers the dot-com boom? Then blockchain. Then web 2.0, software as a service, cloud computing. Each one arrived as the technology that would change everything, and in its own way each one did. AI is simply the latest. Kay was careful not to dismiss any of them, his own included. The pattern he wanted the room to notice was not about the technology. It was about how people respond to it.

Every time one of these waves breaks, he observed, the same thing happens. The hype train pulls in, and every pitch is suddenly rewritten to sit on board. He has lived it from both sides, as a founder raising capital and as a mentor to startups. When blockchain was the word of the moment, founders were pressed to find a place for it in the deck whether or not the business needed it. Companies that were never really about a given technology started insisting that they were, reshaping their own story to match the moment rather than their customers.

Then the tide goes out. Kay borrowed the familiar line about who is left wearing swimming trunks. The dot-com era was the clean example: a rush of companies bolted the suffix onto their names without a business model or a clear value proposition underneath. The ones that survived and grew were the ones that knew what they were for. Those who hitched themselves to whatever was fashionable, because next year it would be something else, often did not last.

From there his argument was straightforward, and deliberately so. Start with knowing yourself. What is your business actually for? How does it create value for customers? Where is your advantage? He pointed out that he had not yet mentioned AI at all, and that was the point. A company that calls itself an AI business still has to answer what it sells, who its customer is, and what that customer wants. Some businesses genuinely sell AI, and that is fine. For most, the more useful question is whether AI can be an enabler that helps them deliver better outcomes than their competition. The advice, he noted, would be the same in a talk that had nothing to do with AI. Focus on delivering value to your customers better than the alternative. It is just good business sense.

That sets up the line that gave the talk its title. AI strategy follows business strategy. It is not the tail that wags the dog. Strategy comes first, and the AI work supports the goals of the business. Kay walked through the textbook framing to make it concrete. Most strategy reduces to one of two broad paths. Cost leadership, where the advantage is being among the lowest-cost or most efficient providers, and where AI might improve operating efficiency, trim expenses, or let a team manage relationships it previously could not. Differentiation, the more interesting side, where the advantage is innovation, speed to market, better customer relationships, sharper sales and marketing. The room, he suspected, was already full of ideas for applying AI to either. The discipline is to begin with the strategy and then ask how AI serves it, rather than the other way around.

His other reminder was about sequence, and he made it against the grain of his own slides, which he admitted had the order wrong. People, then process, then technology. A business starts with people. People design and run processes, and the processes are what the business actually does. Technology comes in to automate and support those processes. The common mistake is to start at the technology end, reaching for a system before understanding the work. Automate a poor process, he warned, and you simply make a bad outcome arrive faster. People still matter most in an AI-heavy world, because they are the ones monitoring what the AI does and keeping the processes honest, which means continuing to invest in training them.

That led to where he landed on the anxiety underneath all of this. There is a lot of narrative about AI replacing roles, and Kay does not like to think that way. He would rather treat AI as a force multiplier. Make a team of ten people fifty per cent more productive and you have a choice: cut headcount to hold output flat, or keep the ten and do half as much again. His preference was clear.

The takeaways he left were plain ones, and stronger for it. AI is not your business strategy; it is a technology to put to work, so do not confuse the two. Focus on the right things, which always means delivering more value to customers than your competitors do. And align your AI strategy to follow your business strategy, because that is where the technology pays off. It is common sense, which is exactly why it is so easy to lose in the noise.