43% of American workers have used AI at work, they are mostly doing it in informal ways, solving their own work problems. Scaling AI across the enterprise is ha

43% of American workers have used AI at work, they are mostly doing it in informal ways, solving their own work problems. Scaling AI across the enterprise is hard A lot of firms starting into this business are "betting the farm" on "scaling AI across the enterprise" In my experience LLMs are incredibly useful from a simple text interface (I only work with text, mainly computer code). I am still reeling from how disruptive they are, in that context. But IMO there is not a lot of money to be made for start ups in that context (I expect there is not enough to justify the high valuations of outfits like Open AI). There should be a name for the curse - revolutionary technology that makes many people vastly more productive, but there is no real way to capture that value. Unless "Scaling AI across the enterprise" can succeed. I have my doubts. I am sure there will be niches, and in a decade or so, with hindsight, it will be clear what they are. But there is no reliable way to tell now The "Bitter Lesson" seems like a distraction to me. The fundamental problem is related: this technology is generally useful, much more than it is specifically useful. The "killer app" is a browser window open to https://chat.deepseek.com https://chat.deepseek.com. There is not much beyond that. Not nothing, just not much. But so long as you have not bet your farm on "scaling AI across the enterprise" nor been fired by someone else who is trying, we should be very happy. We are in a "steam engine" moment. Nothing will ever be the same. And if Open AI and the like all go belly up and demote a swathe of billionaires to be normally rich, that is the cherry on the top