Hype AI vs pragmatic AI

In the current AI boom, like with many technological revolutions in the past, there are two distinct reasons people talk about the new technology.

First, there are benefits that the new technology, once it's assimilated into society, will bring. It may improve people's lives, commercial productivity, and more. Of course, while technology itself is neutral, it can lead to both good and bad outcomes (like nuclear energy and weapons of mass destruction, or the climate after-effects of the industrial revolution and fossil fuel use).

Technology also takes time to disseminate through industry. The internet started in the '70s, was popular in academia in the '90s, but mass adoption and commercial use arrived only in the 2010s. The iPhone launched in 2007, and smartphone use reached 50% of the world population in 2023. Computers in general also took their time: while the first personal computers appeared in the '70s, a Nobel laureate once quipped in the '90s, "You can see the computer age everywhere but in the productivity statistics." William Gibson put it more succinctly: "The future is already here, it's just not evenly distributed."

This delay between a technology becoming known and being properly integrated into industry and society can easily lead to hype bubbles like the dot-com bubble. While the internet proved transformative, and some companies became massive successes (Google, Amazon), many flopped by being too early, executing poorly, or getting caught by bad timing.

Another curious thing happened during the dot-com bubble: many companies with no internet-related business started adding ".com" to their names in an attempt to surf the hype. The same thing happened with the crypto boom, where a flood of projects "adopted" blockchain (or at least the name) to seem more relevant.

The same is happening today with AI. The technology is real. A lot of companies are working on it and evaluating how to integrate it into their products or processes. Many people use ChatGPT and other tools daily for a wide variety of tasks.

At the same time, there's an enormous amount of hype. Some of it comes from a poor understanding of the technology: not everyone can be an AI expert. But a lot of it is companies adopting AI in name only to ride the hype wave. We're being bombarded with claims about the imminent arrival of "Artificial General Intelligence" (AGI) or even "Artificial Superintelligence" (ASI). AI companies tell us to "stop hiring humans" or announce plans to lay off hundreds or thousands of employees as they're replaced by AI agents.

This is AI being used for marketing, not productivity. It doesn’t even require the tech itself—the story is what sells, and the more controversial or hyped, the better. I call this "hype AI."

This contrasts with individuals and organizations exploring AI in a more measured, rational, curious-but-cautious way. They understand the technology is in early stages, has limitations and drawbacks, and that the best use cases are still emerging. They're not rushing to upend operations or fire people, but they do want to take advantage of the new tech where it makes sense. I call this "pragmatic AI."

Currently, we have way more hype AI than pragmatic AI. Witness Klarna walking back its replacing 700 employees with AI, Duolingo backpedaling on contractors, and the general sense that the tech isn’t living up to expectations, as covered by The Economist in Welcome to the AI trough of disillusionment.

The bubble may pop or deflate less dramatically while the technology stays and improves. Riding the hype train might bring short-term marketing wins, but to really take advantage of this new tech, choose the pragmatic approach.