alt Hacker NewsNo signs of AI payoff outside the tech sector
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I have worked in multiple companies where the internally developed software was central to the business success, yet it was handled in an extremely bad way, preventing it from using even a small percentage of its potential. The (good) developers were not the main problem there, but the management. The management did constantly override technical decisions and/or switched the main goals/vison around all the time, preventing the development from finishing anything. In several companies, they replaced the developers with ticket-crunshing code-monkeys that have no interest at all in the business at and who bring no innovation, ideas, or even feedback into their work. Some of that replacement was active, but most was by just making (work-)life miserable for anyone who cared what happened. In my case, one of these companies even offered me a big payment (one that I will probably never get anywhere else without switching to another country) for coming back, because I understand the business good enough to always fix the fires in the background that the management caused, but they still rejected any good ideas and made life worse instead of better for the people that dependent on the software. It's been almost five years since I left there, and I still have several friends in that company. One of them is one of the users of the software, another one is a developer who cares, but he could not switch because he is stuck there for several reasons. One of the main reasons being that he has medical issues that make most companies reject him by default. They keep me updated about the companies progress, or the lack of it. The latter guy told me this week, that the company made less progress in the last four years, than it did within a few weeks while the original dev team worked there. And he really wasn't exaggerating. Oh, the company has a big AI budget and they made pretty much every model available to all employees. They just can't use it for good ideas, because they will be garbled up by the management and turned around to be bad. As long as they don't replace the management with AI, this technology will not improve their business.
Well, of course not. If you borrow a trillion dollars to build a 1¢ aspirin machine to compete with $1 generic aspirin, you are strongly incentivized to sell your aspirin for 99¢. We don’t see productivity gains, because approximately all of the gain is captured as revenue for AI companies.
It’s weird that this has to be spelled out for so many engineers and economists, but to be very clear: OpenAI et al wants your token spend to go to one-minus-epsilon of what you previously spent on payroll, and wants your productivity to go to one-plus-epsilon of what it previously was. If you want 10x productivity, spend 9.9x more on tokens.
They are in the business of enclosure and rent extraction, and any innovation that comes out of their research and development - regardless of how real an innovation it is - will be completely contained and bent totally towards that business. Any leakage of the innovation that you experience as a productivity boost is literally felt as lost profits by them.
I don't see why a payoff would have appeared yet. Many (but certainly not all) software companies have increased their output without hiring more people. But having software with more features doesn't necessarily drive immediate productivity gains in the rest of the economy. It will take time for those benefits to percolate. We've only had access to models good enough to majorly accelerate code writing since early-2026. I feel like we're in the very beginnings of the first part of this wave.
For sake of comparison, consider e-commerce. As a proxy for "impact on the economy", we can use Amazon's revenue. They went public in 1997 and that year had revenue of $148M (just 0.14% of Walmart's revenue that year). By 2000, revenue was $2.76B (1.65% of Walmart). Bricks and mortar didn't start feeling anything until probably 2011, when Amazon crossed 11% of Walmart's revenue. And it wasn't until 2025 that Amazon finally surpassed Walmart.
But, if you worked in tech in the e-commerce business, things were already feeling pretty hot by 2007. And at that point in time, the e-commerce sector was still miniscule compared to traditional retail (~4%). Software is very exciting these days and the most fantastic things are happening. They will eventually percolate out to the rest of the economy. But it will take many years before everyone notices the difference.
"You can see the computer age everywhere but in the productivity statistics." -- 1987
One industry example.. We have been giving students computing devices for years with the cost of educating students going up year after year.. Yet scores keep dropping.. No productivity gains here.. I do not think these results are unique to the education sector.. There are probably alot of businesses where nothing much will change except slight efficiencies.. not enough to move the needle..
We can use a non-deterministic system because we have test suites that act as validation gates.
Other industries don't, so they have no way of knowing if the AI is bullshitting them outside of manual validation, which makes it more expensive and slower than doing it yourself.
"AI does not understand accountability, trust, culture, unwritten rules, ethical trade-offs or fairness, all of which shape reputational risk and ultimately drive revenue growth and profit margins."
For a sec I thought he was talking about private equity.
We're not seeing full automation for things that ought to be automatable now. Customer service chatbots still aren't very good. Salesforce ought to be taking over entire marketing operations, not just supporting sales but replacing it. The medical office side of insurance ought to be automatic now. The pick and place side of warehouse operations should be robotic. Shelf restocking in stores ought to be robotic. All of those things have been demoed, but didn't go to production.
It’d be nice to stop calling it The Magnificent 7. Perhaps The Circular 7, or The Shady 7, something more realistic about how they are treating the stock market. Yeah number go up, but the means to those ends are shady as all hell.
The reason the payoff isn't visible yet is because outside of software engineering, it isn't systematized nor integrated into workflows. But believe me, people are using it and increasing their free time. I was at an HOA meeting in Reno. The board president works for a major US cable provider doing "contract approvals and negotiations", whatever that means. This last year, he said he's cut his 8 hour days down to a few hours using Claude (pretty sure he is just using the web chat interface). Employees of the property management firm are using it too -- our representative at the meeting said it had been a lifesaver for her in recent months. We haven't seen the full benefit from their end but they are also in a state of constant turmoil as a company so it's a wash. A tennis partner of mine who is the regional (entire west coast) manager for an automotive company's extended warranty program has also been able to use it to cut down time-consuming documentation and the firm encourages it; but again, no direct integration into her workflow, she is just winging it with ChatGPT online.
When I tried to use CoPilot at my day job, I set up a prompt to process scans of checks and invoices (with the MICR account bar code line covered w/ a pen so that there was no PII), it would sort of work for 20 files at a time to write a .bat file command to rename the source image based on the content of the check and invoice --- this removed the need to open up scans in batches of 50, read the Invoice ID, save using that, then run a .bat file to rename them based on the balance of information in the database.
The thing is, the failure rate was quite high --- often only 15 (sometimes fewer) lines were returned, and after a while, Microsoft imposed a limit on uploading more files, even though I was deleting the conversations immediately and quitting CoPilot and re-starting (long sessions seemed to have a progressively worse failure rate).
Since then, access to CoPilot has been removed and we're waiting on a test program to finish. Kind of curious how many tokens this was using up (and if there's a model which could be run locally which would work well and quickly enough).
Paradigm shifts happen when old minds retire or die. Something like that, but for companies. If you’re starting a company now, you are _definitely_ hiring less people much later, and different profiles.
Even in the M7, I doubt AI is having much impact other than benefiting from AI spending. Its hard to point to any non-AI products in the M7 that have meaningfully improved since 2023.
The problem isn't that "AI doesn't understand..." this or that, as concluded by the article though. Its more a lack of creativity and incorrect reasoning about what AI can and cannot do. For one, whole role replacement is pure fiction and likely will never happen with LLMs. I expect most businesses will look very different in the next 10 years due to AI and it will not be smooth as the needed creativity will mostly happen in startups (and perhaps companies that can truly operate like startups) and diffuse out from there. I'd expect a lot of churn in the S&P493 and even the M7 most likely.
In video production, 3D modelling, editing etc, I think a lot of jobs are disappearing, with cost dropping. Not data backed, just from what I can see.
There's no payoff for tech either. AI has accelerated the accumulation of tech and cognitive debt that, once the technology is priced appropriately, will come due when it gets too expensive to continue to use.
I think most people in the tech sector and especially driving the AI hype have absolutely no clue how difficult it is to implement change in complex organisations. There are a bunch of technical reasons but half the reasons are not even technical - social, legal, etc. You have to shift the practices of humans and they have incredible inertia. Like decade level change response period. And during the change period they are less productive. Expect a decade type period before "productivity" impact manifests and even then it won't really be measurable directly because people will be doing different things.
There are three kinds of lies: lies, damned lies, and statistics.
I'm pretty sure most of the growth comes from companies laying off useless COVID-epoch engineers. If you lose the dead weight, you climb up without ever gaining more profit. And IT companies hired the most during COVID — the rollback is logical and it has nothing to deal with AI.
But this theory is harder to grasp than the sweet "growth is coming soon". Personally, I don't see any signs of long-term recovery after 2022, the US gov. debt growth is unsustainable, and the global market falls apart i.e. GDP growth while real markets collapsing will just collapse the currency.
I am in a tech role that straddles traditional business. Yes, LLMs are very adept at software development and of course we are early adopters, but the amount of other things that can be automated or at least significantly augmented hasn't scratched the surface.
At the start of this all, execs were clamoring for "AI" and at that time the models were superficially impressive but fell short. Now I think they are all underestimating the amount of improvement in the last year. There's loads of work that can be automated
I wonder if this is going to be something like the Solow Paradox, from Econ Nobel Laureate Robert Solow: https://www.brookings.edu/articles/the-solow-productivity-pa...
>You can see the computer age everywhere but in the productivity statistics. Robert Solow (1987)
We’re heading into corporate budget season. Company after company is slashing their AI budget and the head cut wagons are circling around all the various “AI lab” teams that every company invested in two years ago with zero ROI to show for it. All while massive debt piles up to build data centers despite little evidence any of this is coming close to returning the ROI needed to justify any of it.
2027 is going to be very interesting. Buckle up.
I dont even think theres a payoff in the software dev.... seems to be great to spin something up quick as a POC, then maintaining it requires people immediately who struggle with reading the amount of code it produces.
I think what people fail to appreciate, is that past a certain size, organizations and the people within them get so tightly wrapped up in working a certain way that it becomes nearly impossible to fix without rebuilding the whole thing from the ground up.
If you want to see if AI is paying off, look at new startups that build AI-native versus those that don't, controlling for the type of industry/product. This is a difficult causal inference comparison to make, but it's the one that I find most meaningful and interesting.
The problem is that very few people exist in both worlds, so most don't know how to use AI to streamline their workflows. They waste time repeatedly asking AI the same questions instead of having it write scripts to automate their repetitive tasks
I think we are still in a value discovery phase, as the token cost of one shotting someone's job is not cost effective, you have to constantly pay for tokens. Distilling someones role and breaking it up into AI responses and have AI build the deterministic workflow is where the efficiency is. It should be an upfront cost and then stable efficiency but I don't think many industries are setup to even begin this transformation. Someone else mentioned it's kind of like electricity, in itself productivity doesn't change, it's systems adopting it that compete and scale versus non adopting competition.
'a.i' is unlike software before - where it was build then deploy with lack of customization except of a few high ticket items such as SAP, Workday etc.
for 'A.I' to work for the rest of industry outside of software - you need high touch customization.
I think you could say the same thing of tech and the economy prior to AI.
No Signs of Tech Payoff Outside the Tech Sector. Manufacturing, basic science, education, etc languished while Big Tech reaped record profits and achieved stock heights for the last 15 years.
The problem with this analysis is twofold.
1. Even before AI, the U.S. economy was growing because of a handful of tech companies. The rest of the companies were collapsing.
2. If revenue per worker is stagnant despite AI investment, we don’t know what the revenue per worker would be without AI investment.
3. There’s no reason to believe AI should improve revenue. AI doesn’t just make companies more efficient. It makes their customers more capable of replacing their products. This continues all the way down to the individual. I might have thought about buying a calories tracking app in the past, but now, I can just use one of my AI Chat apps to do that for me.
AI might be reducing overall demand for services and therefore naturally contracting the exchange based economic system.
No signs of AI payoff outside the tech sector...yet. I think it's partially because our harnesses are generally much, much better. And engineers seem to be more deft at figuring out where AI provides real benefit and where it needs a watchful eye.
I'm seeing non-engineers use AI to send more emails, have more meetings, create more documents, and create more dashboards. So much of the busy work that happens in corporate environments was never that valuable in the first place. A firehose of busy work doesn't move any needles that matter.
I find it totally unsurprising and uninteresting that the tool makers themselves are the first to adopt the new tool they made.
this is literally the textbook historical process across every industry ever.
A winner of the Nobel Prize in Economics, Paul Krugman wrote in 1998, “The growth of the Internet will slow drastically, as the flaw in ‘Metcalfe’s law’—which states that the number of potential connections in a network is proportional to the square of the number of participants—becomes apparent: most people have nothing to say to each other! By 2005, it will become clear that the Internet’s impact on the economy has been no greater than the fax machine’s.”
This kind of seems to me like exactly what a reasonable person would expect, based on the nature of the technology and the dynamics of the market bubble: getting plausible-looking-text-generators to do text munging on web apps and servers doesn't seem likely to increase base productivity, but the companies who can collect on the hype will make a killing.
Anecdotally this is not true. At $JOB I'm responsible for running the accounting function of a small US public company. With tools like OMP and shortcut my team has been able to significantly reduce the time it takes to prepare internal and public reporting documents. Not only are we getting more done within tighter deadlines, I have also observed a dramatic increase in the quality of the work product (not least in the form of fewer audit findings).
Maybe it takes a while to show up on the S&P 493's bottom line, but our token spend has had one of the best ROI as far as I'm concerned.
This is the wrong read. Industries outside of tech are weaker in tech, duh. But, they are currently experimenting with the technology, and it’s also less good at non coding tasks, but getting better.
Also adoption is less pervasive.
But wait a few years and you will see a big payoff.
> the AI story will be decided in the S&P 493, not the Mag 7
Maybe? But aren’t they the Mag 7 for a reason? Don’t they control a substantial part of GDP? Don’t they have a significant impact on the global economy that the s&p 493 may not - especially with large scale adoption of these tools.
Not saying that this means AI spending at current rates will be profitable or not crash - but only that there may only be 7-10 big companies at the end of all of this and the S&P 493 will be irrelevant (it’s one potential scenario in my book at any rate)
I would say the driving industry will get up-ended, but we'll see. It may just be workers get paid less because they only babysit the truck during very complicated times.
Robots still seem far off. Its just like war, air superiority might make the war winnable but its the boots on the ground that are needed to actually take the territory.
> AI may be a great calculator, but in business, intelligence is mostly judgment. Judgment depends on context, and the answer varies with which human or which model you ask. Perhaps most importantly, AI does not understand accountability, trust, culture, unwritten rules, ethical trade-offs or fairness, all of which shape reputational risk and ultimately drive revenue growth and profit margins.
All of this is true, but the reality is that LLM agents free up time for people to make judgement by taking care of the grunt work, which means each person can do more. That increased efficiency can mean higher revenues in growth industries and higher profits (through reduced labor force) in stable or declining industries.
I thought Meta Muse, OpenAI's Dot are solving consumer problems. Isn't it? For me most of Google searches are powered by Gemini & I interact with Gemini with follow up questions - completely non-tech.
This is not just "Outside the Tech Sector", but "outside the magnificent 7"
"Tech sector" is supposed to be much bigger than just 7 companies, no matter how big those 7 are.
This looks to me more like just a huge centralization of wealth.
Article is spot on!
The only issue is that the benefits would be more enmeshed with other gains in other industries.,
Heck, even in Software Development, the real benefits are not with mass labor elimination resulting in cost savings but with increasing available throughput. Technology if used to the fullest potential should be able to expand the proverbial pie., which is where the gains are!
That is not to say people won't try to save cost by eliminating labor due to AI., which is super shortsighted and misses the forest for the trees, but the overarching goal should be to increase the quality and quantity of deliverables, as demanded by the market.
> the AI story will be decided in the S&P 493, not the Mag 7, and so far, there is no evidence that revenue growth or margins are improving outside the tech sector.
Lots of theories seeking to explain this reality, but that's all they are: theories. Maybe some will be proven right. Maybe all will be proven wrong.
As of right now, the economic reality lags far behind the hype. But down the road... I wouldn't place a bet either way.
There's a lot more to business in America than the corporate S&P. If you think AI isn't paying off for businesses, then you probably aren't a consultant right now. I have small/mid-size clients who, in pre-AI times, would have never been able to afford the work they're currently scoping out for me. Now I can quote them cheaper rates to build more custom solutions that they didn't even imagine was possible, and they are loving it.
This is a use case issue.
Right now, the most effective use case for AI is coding agents. Software development is a profit center for the tech sector, so it's not surprising that they're seeing big gains. In Corporate America, software development is part of IT which is a cost center, and the software landscape is 30+ years of bandaid-ed legacy systems, maintained by offshore contractors who submitted the lowest cost bid, so attempts to gain productivity via AI have not been as successful.
Where Corporate America has seen gains from AI in my experience is with customer support chatbots, but the customer service function overall in Corporate America is an unmitigated disaster, so the gains are hard to measure.
Beyond these two use cases, most people in Corporate America are just using ChatGPT to create slop and copy/pasting it wherever, and then goofing off in their newly freed spare time.
We need to see new AI use cases in Operations, Finance, Marketing, etc. that can handle business processes end to end before the productivity gains start showing up in the financials.
"Perhaps most importantly, AI does not understand accountability, trust, culture, unwritten rules, ethical trade-offs or fairness, all of which shape reputational risk and ultimately drive revenue growth and profit margins" - This is perhaps the most consequential sentence in the entire article, and yet was almost mentioned as an after-thought.
Are people on here still arguing that these tools are not a good ROI for SW engineering? IF someone has a good argument for it I would love to hear it
This is not surprising. AI in its current form is more obviously useful at generating software than it is at assisting with other kinds of knowledge work. Software can be automatically validated. Validation loops are what let these systems iterate toward acceptable solutions. If you want AI to produce a document for humans, you need to carefully review and revise the output. In that case there's little to be gained, as reviewing plausible but subtly incorrect information sentence by sentence is in some ways harder than authoring it yourself (a quote from someone who worked in like city planning). Depending on the company/industry, some of the non-tech sector workloads still involve phone calls, parcels, faxes, etc -- things AI can't really do.
Yes there are technical solutions to such problems; I'm sure there's probably a startup to make phone calls that's hooked into your company's knowledgebase, multi-LLM workflows for document review, etc. But non-tech companies aren't adopting those. Tech companies came for the software generation and stayed for the general knowledge worker productivity. Since 2023 they made the investments to procure services, change culture, and generally re-tool. Software companies are also uniquely positioned to deal with the limitations of AI in-house, like by building custom glue components to link systems, building controls to mitigate risk, etc.
So basically the tech sector leverages AI more than other sectors. At a company level, non-tech has less investment, less training, less integration of AI with business processes. At an individual level this looks like workers having fewer tools, not knowing how to use the tools they do have, not knowing even what the tools' capabilities are, and incorporating them into their work only superficially if at all.
Someone asked me for help using AI at their job (which is tech adjacent). They were trying to create a process document using ChatGPT. Their selected model was GPT Luna Light (!), and they were copying and pasting data between ChatGPT and SharePoint. There _was_ a SharePoint integration but it lacked write access. The model was not aligning the doc images. Their prompts were not specific. It was a bad experience. Their conclusion was that AI was stupid and not worth the trouble.
So even though the non-tech sector can't take advantage of AI to the same degree that the tech sector can, they're utilizing it even less than they could be.
When IBM PC compatibles first became widely available, most economic reports I saw said that there was no economic impact from computers becoming widely available in offices. Word processors, spreadsheets, and email didnt have any productivity improvements... and I think we know better.
It's too early and we are probably not measuring the right things.
At a fundamental level LLMs reshape how we gather, shape, process and interact with information. Information is that which allows you to make a predictions with a probability better than chance. This will slowly change any industry where decisions are being made. So, it will touch all industries. And if we let it, all of life eventually. Better decisions, better survival.
The tech sector is the most software-defined and virtual of all sectors, it's natural that they are first to change. Other industries need to make capital investments to adapt to change.
You can see a similar history with electrification. A few industries went quickly, but then it took like a decade of little growth before the true benefits showed up. As an example, take a factory that was built around hyrdo-power like a grain mill. You can't just take an electric motor and drop it in in place of the water wheel. It doesn't fit, the wheel is outside, there isn't room between the mill and the wall, etc. Only when you completely rebuild a new mill building designed around the features and limitations of the electric motor do you see the major benefits.
Same thing here; it will be new factories and new companies that are designed from the ground up around AI and its benefits and limitations that really move the needle.