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I guess this is trend now because it's a contrarian / attention grabbing headline. See: - "Thousands of CEOs just admitted AI had no impact on employment or p

I guess this is trend now because it's a contrarian / attention grabbing headline. See: - "Thousands of CEOs just admitted AI had no impact on employment or productivity..." https://fortune.com/2026/02/17/ai-productivity-paradox-ceo-study-robert-solow-information-technology-age/ https://fortune.com/2026/02/17/ai-productivity-paradox-ceo-s... - “Over 80% of companies report no productivity gains from AI…” https://www.tomshardware.com/tech-industry/artificial-intelligence/over-80-percent-of-companies-report-no-productivity-gains-from-ai-so-far-despite-billions-in-investment-survey-suggests-6-000-executives-also-reveal-1-3-of-leaders-use-ai-but-only-for-90-minutes-a-week?utm_source=chatgpt.com https://www.tomshardware.com/tech-industry/artificial-intell... But fundamentally, large shifts like this are like steering a super tanker, the effects take time to percolate through economies as large and diversified as the US. This is the Solow paradox / productivity paradox https://en.wikipedia.org/wiki/Productivity_paradox https://en.wikipedia.org/wiki/Productivity_paradox > The term can refer to the more general disconnect between powerful computer technologies and weak productivity growth

ej88 7mo ago
Even the source article in the first link, https://www.nber.org/papers/w34836 https://www.nber.org/papers/w34836 the same firms "predict sizable impacts" over the next three years late 2025 was an inflection point for a lot of companies
XenophileJKO 7mo ago
I keep seeing the "Productivity Paradox" highlighted over an over again. I think one thing people are missing with this specific technology is that unlike many of the comparisons (computers, internet, broadband, etc), AI in particular doesn't have a high requirement at the consumer side. Everyone already has everything they need to use it. There will be a period like we are in now where dramatic capability gain (like recent coding gains) take a while for people to adapt to, however, I think the change will be much faster. Even the speed of uptake in coding tools over the last 3 months has been faster than I predicted. I think we'll see other shifts like this in different sectors where it changes almost over a series of a few months.
- afavour 7mo ago
  > AI in particular doesn't have a high requirement at the consumer side. Everyone already has everything they need to use it. That isn’t actually true though, right now everyone has a hard dependency on a cloud service. That is currently sold to them at deep discount by companies that are losing billions. When the market eventually corrects it’ll be interesting to see how much AI ends up costing. At the very least it will be comparable to the broadband internet connection you mentioned. Possibly a whole lot more.
  - slg 7mo ago
    >That isn’t actually true though, right now everyone has a hard dependency on a cloud service. That is currently sold to them at deep discount by companies that are losing billions. Isn't that a huge red flag? If customers are being given this product at a discount and it still isn't showing a positive ROI for them, what makes people think it will improve once we're charged full price?
    - weevil 7mo ago
      I think most people just assume it's magic, and are too awestruck by the hype to think critically. Financially this feels similar to Uber's business plan in the 2010s; undercut the market with unsound pricing propped up by venture capital (PE was literally subsidising taxi fares; they admitted this and their intention to readjust, but no one seemed to care) then stop manipulating the market and allow fares to even out at (gasp) what it cost to get a cab before Uber. The difference here is that the LLM market is human productivity; enormous subsidies are afforded to Anthropic, OpenAI etc. in the form of VC or compute credit, but eventually those debts will be called in, the free-to-use aspect will vanish because it's simply not profitable, and we'll be left with several premium products that only a few people will actually pay for, and even then that may not be enough to cover their costs. That's when the bubble will burst.
      - great_psy 7mo ago
        Actually I think there’s another option. There’s the scenario where LLMs get more efficient in size, and to get 2026 SOTA performance you will be able to get it from consumer grade laptop. Sure with a 1000B parameter you will get better performance but the average person will have it write some python script, not derive new physics equations. So in a sense the demand for LLM intelligence with reach a plateau (arguably we are there today for avg person) so there will not be any subsidy required, because the avg person will not need the latest and greatest. There’s not the same demand pattern for something like uber.
slongfield 7mo ago
This isn't new. "The Productivity Paradox" is what they called it when people were skeptical that computer would end up finding a place in the office. There are articles from the 90s complaining about how much people are spending on buying computers for no real impact on productivity https://dl.acm.org/doi/10.1145/163298.163309 https://dl.acm.org/doi/10.1145/163298.163309
surgical_fire 7mo ago
How to reconcile this with all the narratives of how powerful AI is, how it can perform right now at the same level of engineers and so on? Once confronted with reality we have a "productivity paradox"?
Lalabadie 7mo ago
I would argue that the leadership and financial support behind AI (in its current form) does not have the patience or level-headedness to treat it as a long-term change, and is very much trying an all-or-nothing approach to making a long shift happen in a few years instead, or burn through nation-level budgets trying. To my eyes, the problem is not the productivity gain arriving slowly, but the immediate draining of funding from virtually all other areas of innovation.
- camillomiller 7mo ago
  This. They created an innovation black hole and we will all pay the long-term consequences of it
  - palmotea 7mo ago
    > This. They created an innovation black hole and we will all pay the long-term consequences of it But they may get rich soon, which is all that really matters to them.
camillomiller 7mo ago
All of the technologies mentioned eventually made things better. In order to work, gen AI requires a general acceptance of widely spread mostly mediocre outcomes. I don’t see how the comparison stands.
edgyquant 7mo ago
Seems like it’s an ever shifting goalpost when we are told that tons of layoffs etc are already happening due to the tech and yet when quantified it’s debatable if there’s been any gains at all
dodu_ 7mo ago
I'll take it over seemingly endless deluge of FUD-slop from the past 4 years that claims you better get ready for the AI takeover coming for all the jobs in just-long-enough of a timeline that nobody will remember to hold the author accountable when their prediction is woefully incorrect, where the "advice" in the article is conveniently to pay for more AI tools.

ej88 7mo ago

Even the source article in the first link, https://www.nber.org/papers/w34836 https://www.nber.org/papers/w34836 the same firms "predict sizable impacts" over the next three years late 2025 was an inflection point for a lot of companies

XenophileJKO 7mo ago

I keep seeing the "Productivity Paradox" highlighted over an over again. I think one thing people are missing with this specific technology is that unlike many of the comparisons (computers, internet, broadband, etc), AI in particular doesn't have a high requirement at the consumer side. Everyone already has everything they need to use it. There will be a period like we are in now where dramatic capability gain (like recent coding gains) take a while for people to adapt to, however, I think the change will be much faster. Even the speed of uptake in coding tools over the last 3 months has been faster than I predicted. I think we'll see other shifts like this in different sectors where it changes almost over a series of a few months.

afavour 7mo ago
> AI in particular doesn't have a high requirement at the consumer side. Everyone already has everything they need to use it. That isn’t actually true though, right now everyone has a hard dependency on a cloud service. That is currently sold to them at deep discount by companies that are losing billions. When the market eventually corrects it’ll be interesting to see how much AI ends up costing. At the very least it will be comparable to the broadband internet connection you mentioned. Possibly a whole lot more.
- slg 7mo ago
  >That isn’t actually true though, right now everyone has a hard dependency on a cloud service. That is currently sold to them at deep discount by companies that are losing billions. Isn't that a huge red flag? If customers are being given this product at a discount and it still isn't showing a positive ROI for them, what makes people think it will improve once we're charged full price?
  - weevil 7mo ago
    I think most people just assume it's magic, and are too awestruck by the hype to think critically. Financially this feels similar to Uber's business plan in the 2010s; undercut the market with unsound pricing propped up by venture capital (PE was literally subsidising taxi fares; they admitted this and their intention to readjust, but no one seemed to care) then stop manipulating the market and allow fares to even out at (gasp) what it cost to get a cab before Uber. The difference here is that the LLM market is human productivity; enormous subsidies are afforded to Anthropic, OpenAI etc. in the form of VC or compute credit, but eventually those debts will be called in, the free-to-use aspect will vanish because it's simply not profitable, and we'll be left with several premium products that only a few people will actually pay for, and even then that may not be enough to cover their costs. That's when the bubble will burst.
    - great_psy 7mo ago
      Actually I think there’s another option. There’s the scenario where LLMs get more efficient in size, and to get 2026 SOTA performance you will be able to get it from consumer grade laptop. Sure with a 1000B parameter you will get better performance but the average person will have it write some python script, not derive new physics equations. So in a sense the demand for LLM intelligence with reach a plateau (arguably we are there today for avg person) so there will not be any subsidy required, because the avg person will not need the latest and greatest. There’s not the same demand pattern for something like uber.

slongfield 7mo ago

This isn't new. "The Productivity Paradox" is what they called it when people were skeptical that computer would end up finding a place in the office. There are articles from the 90s complaining about how much people are spending on buying computers for no real impact on productivity https://dl.acm.org/doi/10.1145/163298.163309 https://dl.acm.org/doi/10.1145/163298.163309

surgical_fire 7mo ago

How to reconcile this with all the narratives of how powerful AI is, how it can perform right now at the same level of engineers and so on? Once confronted with reality we have a "productivity paradox"?

Lalabadie 7mo ago

I would argue that the leadership and financial support behind AI (in its current form) does not have the patience or level-headedness to treat it as a long-term change, and is very much trying an all-or-nothing approach to making a long shift happen in a few years instead, or burn through nation-level budgets trying. To my eyes, the problem is not the productivity gain arriving slowly, but the immediate draining of funding from virtually all other areas of innovation.

camillomiller 7mo ago
This. They created an innovation black hole and we will all pay the long-term consequences of it
- palmotea 7mo ago
  > This. They created an innovation black hole and we will all pay the long-term consequences of it But they may get rich soon, which is all that really matters to them.

camillomiller 7mo ago

All of the technologies mentioned eventually made things better. In order to work, gen AI requires a general acceptance of widely spread mostly mediocre outcomes. I don’t see how the comparison stands.

edgyquant 7mo ago

Seems like it’s an ever shifting goalpost when we are told that tons of layoffs etc are already happening due to the tech and yet when quantified it’s debatable if there’s been any gains at all

dodu_ 7mo ago

I'll take it over seemingly endless deluge of FUD-slop from the past 4 years that claims you better get ready for the AI takeover coming for all the jobs in just-long-enough of a timeline that nobody will remember to hold the author accountable when their prediction is woefully incorrect, where the "advice" in the article is conveniently to pay for more AI tools.