But what I see is the two big costs for America:
1) Less money being invested into risky AI projects in general, in both public (via cash flows from operations) and private markets 2) The large tech firms who participated in large capex spend related to AI projects won't be trusted with their cash balances - aka having to return more cash and therefore less money for reinvestment
All the hype and fanfare that draws in investment at al comes with a cost - you gotta deliver. People have an asymmetric relationship between gains and losses.
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And so far there's no evidence that all this investment has generated more profit for the users of AI.
If you look around a bit, you will find evidence for both. Recent data finds pretty high success in GenAI adoption even as "formal ROI measurement" -- i.e. not based on "vibes" -- becomes common: https://knowledge.wharton.upenn.edu/special-report/2025-ai-a... (tl;dr: about 75% report positive RoI.)
The trustworthiness, salience and nuances of this report is worth discussing, but unfortunately reports like this gets no airtime in the HN and the media echo chamber.
Preliminary evidence, but given this weird, entirely unprecedented technology is about 3+ years old and people are still figuring it out (something that report calls out) this is significant.
I would love to see another report that isn't a year old with actual ROI figures...
All the middle managers are afraid to say anything though, so go go go.
It honestly just isn't that interesting. (Being most notable for people misunderstanding and misrepresenting the chart on page 46 of the report as being "ROI" rather than "ROI measurement")
In terms of ROI figures, it's really just a survey with the question "Based on internal conversations with colleagues and senior leadership, what has been the return on investment (ROI) from your organization's Gen AI initiatives to date?".
This doesn't mean much. It's not even dubiously-measured ROI data, it's not ROI data at all, it's just what the leadership thinks is true.
And that's a worrying thing to rely on, as it's well documented (and measured by the report's next question) that there's a significant discrepancy in how high level leadership and low-level leadership/ICs rate AI "ROI".
One of the main explanations of that discrepancy being Goodhart's law. A large amount of companies are simply demanding AI productivity as a "target" now, with accusations of "worker sabotage" being thrown around readily. That makes good economy-wide data on AI ROI very hard to get.