This research is specifically NOT about tech companies. It is about the rest of the fortune 500.

If you are in software or IT at a non-tech company that is in the fortune 500, the impact of significantly better productivity may not be measurable in aggregate in the company's P&L.

In smaller companies I expect it could be more measurable because some of them really are using AI much more effectively across many functions. But we're finding it very hard to measure meaningful outcomes.

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abathologist 3 hours ago | parent [-]

But actually 40% of the S&P 500 are tech companies, and they are saying only the mag 7 are showing clear revenue increase. Would would suggest that even in most tech we are not seeming measurable revenue growth, right?

One plausible explanations that has occurred to me is this: While programmers etc. can produce way more code with LLMs, the declines in quality and coherence of the work, and a widening gap with a coherent strategy and aim for value means the increased activity is mostly not valuable. I suspect this may just be an intensification of https://en.wikipedia.org/wiki/Productivity_paradox#Little_pr...

	▲	jeremyjh 2 hours ago \| parent [-]
		The mag 7 are getting direct or nearly direct revenue from AI inference. New money is pouring into that - it is not zero sum. Everyone else is getting internal productivity lifts that are matched by competition, and when they are deploying inference features they are usually ones their customers didn’t ask for and don’t value, OR that they expect everyone to have and are not a differentiator. I think you are also correct that a lot of value is being wasted with projects that are developed impressively fast but that provide little value. It could be those are simply surplus personnel trying to add value or make people think they do.