On the effects of using AI to replace knowledge workers, from lawyer and typographer Matthew Butterick:
How might this work? The economy is increasingly driven by intangible assets. Knowledge workers provide those assets. If a company lays off its knowledge workers in favor of adopting some vendor’s AI, at first it gets the same productivity at much lower cost. So much win.
But in doing so, the company commoditizes its own output. If your company can automate its output via AI, others can too. Your existing competitors, certainly. But also upstarts who don’t have your cost footprint. Whatever intangible assets AI can generate will be produced in excess, leading to a deflationary market for that asset. A company’s knowledge workers may be its greatest expense. But they also contribute to its competitive moat.
Feel free to take his argument about legal services and see how hard you feel you have to stretch to apply it to healthcare:
Consider large law firms, aka Big Law. Currently certain legal-AI startups license LLMs from Big AI and repackage them for Big Law at high prices. These startups claim to add other special sauce. OK, sure. Where’s the economic equilibrium? If legal-AI startups prove that money can be made selling AI to Big Law—won’t Big AI just sell to Big Law directly, and cut out the startups? Or if legal-AI startups prove that AI can effectively provide legal services—won’t legal-AI startups just sell to clients directly, and cut out Big Law? Won’t members of Big Law that adopt AI have to lay off a lot of equity partners, because adoption of AI will shrink profit margins? Won’t the members of Big Law refusing AI have to consolidate to preserve their margins? Or just cave to AI? (The tendency of competitors to adopt similar practices is called institutional isomorphism.) So it goes. Most states prevent nonlawyers from sharing in legal fees, so law firms will probably remain a distinct set of entities. But one plausible equilibrium is that legal-AI startups disappear (quickly), and members of Big Law consolidate (relatively quickly) until there are only a handful left, all contracting directly with Big AI.
Along these lines, I expect that to succeed financially, Big AI will likely need to demolish a significant number of existing tech companies and grab their revenue for itself. By the process described above: Big AI essentially uses its tech customers as an R&D facility. Big AI licenses models to these companies. Tech companies compete to adapt their businesses to AI. Once a concept is proven, Big AI directly takes over that market. The labor-replacement story will grow into a company-replacement story. Many of those tech companies—and their shareholders in the public markets—may also find that AI is a poisoned chalice.
The possible deflationary component to AI deserves much more attention. When companies raise and spend oodles of money to address a specific market, the assumption is that those big companies and the AI companies will reap the economic profits. But even if that were to happen, those profits may disappear quickly if the once scarce cognitive good is repriced accordingly.
Perhaps that will lead the entire planet to enjoy a widespread post-scarcity techno-utopia thanks to Jevon’s Paradox once we can deploy at scale the cognitive resources that used to be the exclusive domain of the human brain, but I’d argue the law of supply/demand is, broadly, real.