High growth scenario and medium growth scenario (Graph 2). I feel like an idiot asking - aren't we missing some, or at least one, scenario? Is "medium growth" for the next 4 years really the worst people can think of?
Essentially yes? The stock market operates entirely on the assumption that the lines will keep going up. As soon as they flatten the whole thing collapses onto itself.
The source article says (in a way that I can understand might be a bit non-obvious) that it's analyzing the AI buildout from the perspective of the people who are participating in it. Someone who believes there'll be less than "medium growth" would probably not be buying hyperscaler bonds right now regardless of their precise estimate. They discuss the tail risks if the whole investment thesis is wrong at the end.
Can't you see how much money is being pumped into this lunacy? Of course it's going to succeed. Graphs for failire are such a bummer too and are bad for the economy...
if growth doesn't materialize, then the infrastructure build out plays out exactly like the dot com bubble. the biggest difference this time around is the earnings. if those fall, the rest crubmles.
Usefulness aside, I see little evidence AI is making money (profit, not revenue) for any firm whose profit doesn't come from the AI itself or the infrastructure, including supply chain. I'd love to hear a counterexample. One such example would be of a hypothetical company that does translations for payment, and with AI they now are making more profit because they use AI to do the translation rather than pay a translator.
Duolingo is such a company you would expect AI to help a lot. Surely AI could allow it to cut costs substantially. And yet, in the past year its stock is down 70% and in Q1 2026 profit has not seemed to increase compared to Q4 2025. In fact, other than Q3 of last year which had some tax shenanigans, their profit is relatively flat. Not a great look given that AI is highly disruptive to their product.
---
AI is actually insidious. Suppose you're in a competitive industry like Costco making 3% (net profit) margin. Suppose the average costco employee makes 60K. Then you come in and think it would be great to have an AI agent lets every employee ask questions of inventory to help customers. Surely if employees could use AI that could somehow make more money for Costco. Hypothetically let's say this ends up costing about the same as the basic subscription in terms of tokens. $20/employee/month Can't be that bad right?
$240 ÷ 0.03 = $8,000 (in other words, generate over 10% of their own salary in marginal additional net profit every year). Is Costco really going to generate 8K more per employee? Nope. And yet, firms like Costco who choose AI effectively just lower their own profit margins.
I want to add context for Duolingo because I think it's confounded by cultural conversation. Duolingo in some Q1 earnings call stated it was going to go AI-native. They were going to switch from contractors to AI. This led to a huge PR crisis, especially on TikTok, where they used to have a big online presence and GenZ influence. I'm not sure if they ever recovered the image they had after that.
They tried, and they got pushback from their consumer base.
Your Costco example makes a lot of sense to me. Right now at my company we are spending hundreds and thousands per employee, but it's not like everyone has an idea that is meant to be integrated into product. So everyone's just making more vaporware.
I do think this is the year the numbers and projections will start coming down to the ground. We can already see this with the fact that the leaders at the frontier labs have stopped talking about AGI and have started talking about token costs and just direct comparisons. It's no longer pie in the sky.
This study finds increased sales and value per customer from GenAI integration at a large Chinese online retailer (all the way back in 2023-24!) The customer Q&A scenario is one of those covered, except the customer talks directly to the LLM rather than an employee with a subscription:
> We quantify the short-term impact of Generative Artificial Intelligence (GenAI) on sales performance through a series of large-scale randomized field experiments involving millions of users and products at a leading cross-border online retail platform. Over 2023-2024, the platform integrated GenAI into seven business workflows spanning customer service, consumer-product matching, advertising, and seller services. We find that GenAI adoption increases sales in most workflows, with effects ranging from no detectable impact to 16.3%, depending on GenAI's marginal contribution relative to baseline firm practices. Across the four GenAI applications with positive sales effects, the implied annual incremental value is roughly $5 per consumer−an economically meaningful impact given the retailer's scale and the early stage of GenAI adoption. The gains operate primarily through higher conversion rates rather than larger cart values, consistent with GenAI improving the shopping experience by reducing search, information, communication, and personalization frictions. Importantly, these effects are not associated with worse post-purchase outcomes, as product return rates and customer ratings do not deteriorate. Finally, we document substantial demand-side heterogeneity, with larger gains for less experienced consumers. Our findings provide novel, large-scale causal evidence on how GenAI shapes sales productivity in online retail, highlighting both its immediate value and broader potential.
Impact on profitability itself is hard to determine due to caveats listed in the paper (which are important to read!) but offhand I would guess that incemental $5 margin per customer is much more than what their prompts cost.
Translator services usually get paid because they offer an accreditation or certification that the humans doing the translation are trained and are not randos / computers. I could imagine these services becoming marginally more efficient but no dramatically improving profits.
I'm not an MBA over here, but this math seems wrong. If they are spending $240 in increased costs, then they only have to make about $247 in additional revenue from that spend to preserve a 3% margin. That seems much more reasonable if it increases the probability that customers find the product they are looking for and have a good experience.
The risk here is that either AI commoditizes the software "why ask duolingo to ask chatgpt when I can do so directly?" or simply adds cost to an existing service "why does every costco employee now cost 10% more?"
So far, there hasn't been a clear win for "software wrapping an existing LLM" - if the AI is good enough, then the users can go directly to the source.
I agree with your main observations, but the Costco example is a bit contrived. I expect companies to eventually figure out suitable applications for AI, and I doubt a flat subscription per seat will be one of them. Personally, I feel the main issue is that the tooling + systems needed to deploy AI successfully have only recently started to mature.
AI has been making a ton for advertisers for decades. Think Facebook ads, Google search ads, etc.
That's a different and older kind of AI than chatbots, but it's not fundamentally different, but AI is the engine that makes their ad targeting so effective, and why they're some of the most profitable large companies on the planet.
Speaking of financing: how is the Anthropic IPO going, what is the timeline? They filed over a month ago, no news since. (I would have expected some spectacular news headlines that would be designed to fuel public interest in the impending IPO, but can't detect anything of substance)
just recalled: some significant open source projects are being rewritten in Rust, with the help of Claude. I don't know if these efforts will be successful in the long run, but in some way these news headlines may be creating a media dynamic as part of the IPO preparations?
AFAICT, the last we heard of any AI company IPO was that OpenAI got spooked by the market response to SpaceX and is considering punting to 2027 (https://www.the-independent.com/tech/openai-ipo-date-valuati...). My money is on Anthropic similarly punting, especially if SpaceX manages to cross the very very short distance remaining to drop below the IPO price.
Public utilities tend to pass on all their costs to their customers. If the data centers crumble, that just means the remaining customers (business and residential) each will have to pick up a larger share of the debt payments for the buildout.
Thinking out loud, is productivity the ultimate macro benefit of AI? Should we expect macro AI investment to be a leading indicator of macro productivity gains?
For example, did macro investment in factory automation predict future productivity gains?
I've seen other reports that suggest the level of investment for eclipses the internet buid out in 2000 and the railroad boom more than a century earlier. I wonder if they use different ways of landing on these wildly different assessments
Yes. In inflation adjusted dollars spending on AI dwarfs previous "megaprojects". But as a fraction of GDP it's fairly modest -- comparable to the Apollo Project.
It's a sign of how much the economy has grown that under "1% of GDP for a few years" now is far bigger than "over 10% of GDP for a few decades" was in the late 1800s.
BIS released a larger report in June that identified AI financing/sustainability as one of the biggest risks for the global economy:
https://www.bis.org/publ/arpdf/ar2026e.htm
Thread: https://news.ycombinator.com/item?id=48912577
pre-echos of "too big to fail"
High growth scenario and medium growth scenario (Graph 2). I feel like an idiot asking - aren't we missing some, or at least one, scenario? Is "medium growth" for the next 4 years really the worst people can think of?
Financial news tends to be written for people who can fill in a lot of blanks themselves.
Essentially yes? The stock market operates entirely on the assumption that the lines will keep going up. As soon as they flatten the whole thing collapses onto itself.
> Is "medium growth" for the next 4 years really the worst people can think of?
At this point anything less than "medium growth" will crash the economy. We'll have bigger problems if that happens (think 2000 or 2008)
Hmm. Perhaps too similar to pre-GFC when the ratings agencies' models never accounted for scenarios where home prices went down at the national level.
The source article says (in a way that I can understand might be a bit non-obvious) that it's analyzing the AI buildout from the perspective of the people who are participating in it. Someone who believes there'll be less than "medium growth" would probably not be buying hyperscaler bonds right now regardless of their precise estimate. They discuss the tail risks if the whole investment thesis is wrong at the end.
Can't you see how much money is being pumped into this lunacy? Of course it's going to succeed. Graphs for failire are such a bummer too and are bad for the economy...
if growth doesn't materialize, then the infrastructure build out plays out exactly like the dot com bubble. the biggest difference this time around is the earnings. if those fall, the rest crubmles.
Usefulness aside, I see little evidence AI is making money (profit, not revenue) for any firm whose profit doesn't come from the AI itself or the infrastructure, including supply chain. I'd love to hear a counterexample. One such example would be of a hypothetical company that does translations for payment, and with AI they now are making more profit because they use AI to do the translation rather than pay a translator.
Duolingo is such a company you would expect AI to help a lot. Surely AI could allow it to cut costs substantially. And yet, in the past year its stock is down 70% and in Q1 2026 profit has not seemed to increase compared to Q4 2025. In fact, other than Q3 of last year which had some tax shenanigans, their profit is relatively flat. Not a great look given that AI is highly disruptive to their product.
---
AI is actually insidious. Suppose you're in a competitive industry like Costco making 3% (net profit) margin. Suppose the average costco employee makes 60K. Then you come in and think it would be great to have an AI agent lets every employee ask questions of inventory to help customers. Surely if employees could use AI that could somehow make more money for Costco. Hypothetically let's say this ends up costing about the same as the basic subscription in terms of tokens. $20/employee/month Can't be that bad right?
$240 ÷ 0.03 = $8,000 (in other words, generate over 10% of their own salary in marginal additional net profit every year). Is Costco really going to generate 8K more per employee? Nope. And yet, firms like Costco who choose AI effectively just lower their own profit margins.
The issue is Duolingo is rubbish, what the app does isn’t that hard to replicate and there are already competitors that have a better product.
So if AI is real then that‘s the cherry on top: people can now make an alternative to your ineffective messy app even easier.
For those kind of SaaS products with no moat LLMs could actually be a problem and definitely aren’t a good thing
I think this is a great point.
I want to add context for Duolingo because I think it's confounded by cultural conversation. Duolingo in some Q1 earnings call stated it was going to go AI-native. They were going to switch from contractors to AI. This led to a huge PR crisis, especially on TikTok, where they used to have a big online presence and GenZ influence. I'm not sure if they ever recovered the image they had after that.
They tried, and they got pushback from their consumer base.
Your Costco example makes a lot of sense to me. Right now at my company we are spending hundreds and thousands per employee, but it's not like everyone has an idea that is meant to be integrated into product. So everyone's just making more vaporware.
I do think this is the year the numbers and projections will start coming down to the ground. We can already see this with the fact that the leaders at the frontier labs have stopped talking about AGI and have started talking about token costs and just direct comparisons. It's no longer pie in the sky.
This study finds increased sales and value per customer from GenAI integration at a large Chinese online retailer (all the way back in 2023-24!) The customer Q&A scenario is one of those covered, except the customer talks directly to the LLM rather than an employee with a subscription:
https://arxiv.org/abs/2510.12049
> We quantify the short-term impact of Generative Artificial Intelligence (GenAI) on sales performance through a series of large-scale randomized field experiments involving millions of users and products at a leading cross-border online retail platform. Over 2023-2024, the platform integrated GenAI into seven business workflows spanning customer service, consumer-product matching, advertising, and seller services. We find that GenAI adoption increases sales in most workflows, with effects ranging from no detectable impact to 16.3%, depending on GenAI's marginal contribution relative to baseline firm practices. Across the four GenAI applications with positive sales effects, the implied annual incremental value is roughly $5 per consumer−an economically meaningful impact given the retailer's scale and the early stage of GenAI adoption. The gains operate primarily through higher conversion rates rather than larger cart values, consistent with GenAI improving the shopping experience by reducing search, information, communication, and personalization frictions. Importantly, these effects are not associated with worse post-purchase outcomes, as product return rates and customer ratings do not deteriorate. Finally, we document substantial demand-side heterogeneity, with larger gains for less experienced consumers. Our findings provide novel, large-scale causal evidence on how GenAI shapes sales productivity in online retail, highlighting both its immediate value and broader potential.
Impact on profitability itself is hard to determine due to caveats listed in the paper (which are important to read!) but offhand I would guess that incemental $5 margin per customer is much more than what their prompts cost.
Translator services usually get paid because they offer an accreditation or certification that the humans doing the translation are trained and are not randos / computers. I could imagine these services becoming marginally more efficient but no dramatically improving profits.
I'm not an MBA over here, but this math seems wrong. If they are spending $240 in increased costs, then they only have to make about $247 in additional revenue from that spend to preserve a 3% margin. That seems much more reasonable if it increases the probability that customers find the product they are looking for and have a good experience.
The risk here is that either AI commoditizes the software "why ask duolingo to ask chatgpt when I can do so directly?" or simply adds cost to an existing service "why does every costco employee now cost 10% more?"
So far, there hasn't been a clear win for "software wrapping an existing LLM" - if the AI is good enough, then the users can go directly to the source.
I agree with your main observations, but the Costco example is a bit contrived. I expect companies to eventually figure out suitable applications for AI, and I doubt a flat subscription per seat will be one of them. Personally, I feel the main issue is that the tooling + systems needed to deploy AI successfully have only recently started to mature.
AI has been making a ton for advertisers for decades. Think Facebook ads, Google search ads, etc.
That's a different and older kind of AI than chatbots, but it's not fundamentally different, but AI is the engine that makes their ad targeting so effective, and why they're some of the most profitable large companies on the planet.
Speaking of financing: how is the Anthropic IPO going, what is the timeline? They filed over a month ago, no news since. (I would have expected some spectacular news headlines that would be designed to fuel public interest in the impending IPO, but can't detect anything of substance)
just recalled: some significant open source projects are being rewritten in Rust, with the help of Claude. I don't know if these efforts will be successful in the long run, but in some way these news headlines may be creating a media dynamic as part of the IPO preparations?
[1] https://news.ycombinator.com/item?id=48870966 pgrust passes 100% of the Postgres regression tests
[2] https://news.ycombinator.com/item?id=48837877 Rewriting Bun in Rust
[3] https://news.ycombinator.com/item?id=48789325 My AI-built PHP engine in Rust passes 17% of PHP-src tests, renders WordPress (ekinertac.com)
they're probably waiting to see how market reacts to fable5 and gpt 5.6
AFAICT, the last we heard of any AI company IPO was that OpenAI got spooked by the market response to SpaceX and is considering punting to 2027 (https://www.the-independent.com/tech/openai-ipo-date-valuati...). My money is on Anthropic similarly punting, especially if SpaceX manages to cross the very very short distance remaining to drop below the IPO price.
At least if the datacenters usage crashes, we'll have cheap power from all the infra that got built.
Public utilities tend to pass on all their costs to their customers. If the data centers crumble, that just means the remaining customers (business and residential) each will have to pick up a larger share of the debt payments for the buildout.
No, we won't - there's significant capex on all that infra that will have to be paid down, and we won't have datacenters to help pay for it.
(January 2026)
Thinking out loud, is productivity the ultimate macro benefit of AI? Should we expect macro AI investment to be a leading indicator of macro productivity gains?
For example, did macro investment in factory automation predict future productivity gains?
I'm not sure the current administration is fully driven by macroeconomic arguments.
I've seen other reports that suggest the level of investment for eclipses the internet buid out in 2000 and the railroad boom more than a century earlier. I wonder if they use different ways of landing on these wildly different assessments
Yes. In inflation adjusted dollars spending on AI dwarfs previous "megaprojects". But as a fraction of GDP it's fairly modest -- comparable to the Apollo Project.
It's a sign of how much the economy has grown that under "1% of GDP for a few years" now is far bigger than "over 10% of GDP for a few decades" was in the late 1800s.
Manhattan Project: $36B, 5 years
▫ Apollo Program: $257B, 14 years
▫ Interstate Highway System: $620B, 37 years
▫ AI data centers: $930B, 6 years and still accelerating
From: https://substack.com/@rubendominguez/note/c-244929068
this time its free printed fiat debt tho, not fully comparable. If market crashes, they will print even few times more again
I’d rather see capital invested rather than being hoarded on a corporate balance sheet with minimal utility.
Good to see GDP growing.
Is it being "invested" or is it being set on fire? Would you rather see capital be set on fire or hoarded?
We don't have to spend it on hardware with such short use-life to spend down those dragon hoards...
The amount of money we are talking about could have given the entire US high speed commuter rail.