AI: The ROI Runway Could Be Long Outside the Tech Sector

HardCodedBias

The premise is flawed. "The first chart below shows that so far there are no signs of profit margins rising outside the tech sector. This is ultimately what we are waiting for, because the value of AI companies today rests entirely on the promise that margins in the S&P 493 will eventually climb." This is absolutely not necessary. The bull case is that AI will bring great efficiencies. The surplus profits from those efficiencies could easily be competed away by firms who have adopted AI. Those firms who do not adopt AI will have their margis crushed.

hyperpape

Maybe there's an argument that a lack of rising profit margins in non-tech companies is a bad sign for AI, but this article doesn't make it. Why can't we have a red-queen's race where non-tech companies are implementing AI, but it's not increasing the total profits of those sectors, just meeting rising customer demands/fighting over the share of existing profits? (Never mind that if you look at that chart, profit margins aren't static to begin with, so you can't isolate AI impact from normal fluctuation). Now, on the first order point, I agree that non-tech companies seem to be taking longer to see results from AI, even if the argument was bad. I work on SaaS for the logistics space, and I feel like prior to the end of 2025, almost all the discussion about AI for logistics was vaporware, starting this year, companies are actually trying to deploy agents, and we'll start finding out what the ROI is later this year or next.

rooftopzen

Article is authored by a private credit firm who assigned absurd valuations to AI infra (see below as an even super recent example) - what is their intention by writing this (is it due to the AI fear narratives around software investments they also hold that drive ppl to withdraw their holdings in Apollo?) From last month: https://peinsights.substack.com/p/apollo-and-blackstone-clos...

sublinear

I don't understand why anyone insists that this needs more time. None of what we've seen in the past few years is new tech. It's more money and hardware thrown at the problem than ever before for diminishing returns. The market has clearly spoken. Knowing what you're doing is much more valuable than just the doing. That still requires humans. This AI winter has already begun.

rnagulapalle

The slower adoption in non-tech sectors isn't just cultural lag - the integration surface is genuinely harder. Legacy ERP systems, compliance review cycles for what data the model can touch, and change management overhead all front-load costs before any efficiency shows up in margins. I've seen this in payment/API systems: the actual model integration takes weeks, but getting legal and security sign-off on the data pipeline takes months. Non-tech companies face the same pattern but with less internal tooling to manage it. The margin signal might also be appearing at the wrong level. Gains in these sectors often show up first as headcount flatness or throughput improvements before they hit EBITDA. Measuring at the P&L level on a 2-year horizon is probably too early and too coarse - the operational metrics are moving, the accounting just hasn't caught up yet.

Animats

> If token costs converge toward zero for most AI use cases... In the real world, token costs seem to be going up, as early stage pricing at a loss gives way to pricing that generates revenue. Compute costs might go down a little over the next five years, but there's nothing coming along in hardware that leads to huge reductions in price. NVidia says don't expect better price/performance before 2030. The models keep getting bigger, and people put loops around them which iterate, burning tokens. Where is this cost reduction coming from?

kazinator

There is no reason to believe the ROI runway is not long inside the tech sector either. I mean, you cannot base that on claims made by the AI sub-sector of the tech sector; of course they are going to claim nothing other than that eating their dogfood is great ROI with a short runway.

rybosworld

One thing I can't square: if the cost to build an application goes to zero, we should see a proliferation of apps, especially from the AI labs. The fact that we aren't seeing an app explosion (I think) is evidence that building applications people will pay for is significantly more complex than just prompting claude/codex/etc

Legend2440

If you need immediate ROI (say, because you just invested a trillion dollars into datacenters) you may be out of luck. And I don't think this is unusual. It took decades for previous technologies to be fully integrated into existing businesses. In the 80s you could see the IT revolution everywhere... except the productivity statistics, which didn't catch up until the 90s. LLMs are still very new and have significant limitations (like prompt injection and high token costs) that are very likely solveable but will take time.

sharadov

Microsoft, Amazon are all building forward deployment engineering teams - to increase AI adoption. It will take time, but it will happen.

StackOptimist

Everyone's arguing the macro (do the margins show up), but the reason non-tech ROI is slow is pretty concrete once you've been close to one of these projects: most of what I've seen bolts a chatbot onto the existing system and stops there, and a chatbot on top of rigid software inherits all the rigidity plus a new way to be wrong. The value shows up only after the boring part: wiring the model to the real data with real access control, and moving anything that has to be exact or repeatable out of the model and into deterministic tools it calls. That's an integration-and-permissions project, not an "adopt AI" project. It's slow, it's unglamorous, nobody demos it, so pilots skip straight to the chatbot and then report thin ROI. Tech companies see returns faster partly because their data and tooling are already reachable by the thing. So I'd read the flat margins as "the actual work hasn't been done yet," not "there's no value there." The runway being long and the technology being real aren't in tension. The gap is that the useful version looks like plumbing, and plumbing doesn't get funded on the same timeline as a demo.