> Despite $30–40 billion in enterprise investment into GenAI, this report uncovers a surprising
result in that 95% of organizations are getting zero return. The outcomes are so starkly
divided across both buyers (enterprises, mid-market, SMBs) and builders (startups, vendors,
consultancies) that we call it the GenAI Divide. Just 5% of integrated AI pilots are extracting
millions in value, while the vast majority remain stuck with no measurable P&L impact. This
divide does not seem to be driven by model quality or regulation, but seems to be
determined by approach.
I use my house all day and I'm sure I'm not the only one.
that didn't stop the housing bubble in the 2000s.
likewise, if I argue that Dutch "Tulip mania" [0] was a bubble, "but tulips are pretty" is not an effective counter-argument. tulips being pretty was a necessary precondition for the bubble to form.
the existence of a foo bubble does not mean that foo has zero value - it means that the real-world usefulness of foo has become untethered from market perceptions of its monetary value.
I used the internet every day in 2000. Bubbles happen with useful technologies not because we decide they aren't useful, but because we were over-sold on what they could do before they could do it.
A lot of AI investment right now is hinged on promises of "AGI" that are failing to materialize, and models themselves are seeing diminishing returns as we throw more hardware at them.
The issue isn't that AI has no value but that the amount of money invested in it is out of proportion to the value it's going to generate within a reasonable time frame. Useful new technologies are invented all the time. But not many of them will yield a return on a trillion dollar investment.
There was a lot of business value during the dotcom boom and we still had a crash. The question is how many AI companies have strong fundamentals and will survive, vs the ones that have weak fundamentals and will die if/when the investment money dries up.
The sad thing about bubbles based on overhyped but nevertheless useful tech is the collateral damage of the pop. Small promising companies that are simply too young to have good fundamentals will go under from the backlash created among investors and potential customers. It’s destruction that could’ve been avoided if we had a more measured and sober society that doesn’t need a new craze every 5 years.
There is definitely value but not sure if it is as much as the AI bosses are promising. I don’t know if it will crash or not but they are definitely overselling it. GPT-4o to 5 is so incremental compared to 3.5 and 4.
LLMs also cost what they cost because NVIDIA won't sell you a 5090 upgraded with 80GB RAM for $3000 instead of $2000 (which is overkill in the first place). Yo have to buy a H200 for $40000
If there is demand, someone will sell that eventually - while NVIDIA has a headstart, they "just" fab stuff on TSMC anyway. AMD and to a degree Intel are already starting to sell cards with more VRAM.
My take is the reckoning will come for the billion businesses that offer B2B AI solutions that don't offer any meaningful value. "Analyze customer intent and improve conversion with XYZ AI!" The tools of the AI revolution will continue to exist though development (read money) will presumably slow as businesses recalibrate and stop paying for the silver bullet solutions that they discovered don't work. Then the snake oil business people who built businesses around LLMs will move onto whatever BlockChain 2 Electric Boogaloo looks like.
I made this comment earlier, and its just easier to copy it:
>Theres 2 AI conversations on HN occurring simultaneously.
> Convo A: Is AI actually reasoning? does it have a world model? etc..
> Convo B: Is it good enough right now? (for X, Y, or Z workflow)
The internet reshaped the entire global economy, yet the dot com crash occurred all the same.
Convo A leads to questioning if the insane money being poured into AI make sense.
The fact that many people are finding utility, doesn't preclude things from being over valued and over hyped.
Crashes, rather, must come when there is an enormous, industry-wide mismatch between perceived value (e.g. assessed in terms of expected return on investment) and actual value in terms of real return on investment within the expected period.
Evidence is emerging that the former could be twenty times the latter, or more.
The value you perceive has been much, much more expensive than investors would like, I suspect.
Internet traffic kept growing throughout the dotcom bubble. That valuations got ahead of themselves didn't mean that there wasn't something real driving the hype.
Even if AI valuations have a sharp correction, there will still be a great need—and demand—for compute.
> Crashes come when there was no real business value.
Indeed. That's why we don't have trains or the internet anymore; once they had their big crashes we knew there was no business value, so they went away.
... I mean, what? You generally can't get a big bubble without _some_ business value, so bursting bubbles almost always have _something_ behind them (the crypto one may be the exception).
You fall into all or nothing logic. That's thinking failure.
If real business value is 10% of the price, there will be massive crash and years of slow advance.
Dot-com bust was like that. Internet clearly had value, but not as much and not as quickly as people thought.