95% of Companies See 'Zero Return' on $30B Generative AI Spend

Here is the report: https://mlq.ai/media/quarterly_decks/v0.1_State_of_AI_in_Bus...

The story there is very different than what's in the article.

Some infos:

- 50% of the budgets (the one that fails) went to marketing and sales

- the authors still see that AI would offer automation equaling $2.3 trillion in labor value affecting 39 million positions

- top barriers for failure is Unwillingness to adopt new tools, Lack of executive sponsorship

Lots of people here are jumping to conclusions. AI does not work. I don't think that's what the report says.

> AI would offer automation equaling $2.3 trillion in labor value affecting 39 million positions

But

>Current automation potential: 2.27% of U.S. labor value

Given the US GDP right now is 27 trillion, I'm not sure if this is really mathing out in my head. Wwe're going to potentially optimize 61 billion dollars of US labor value while displacing some 15% of the American labor force, and return back 2.3 trillion in value? Who's purchasing all this (clearly not the workforce)? Meanwhile, investments in AI as of 2025 is already hitting half of that.

Granted, GDP is an odd indicator to measure on for this situation. But I'm unsure how else we measure "labor value" here.

I’m not sure how you got that 2.2% of 18.5 trillion in GDP attributed to labor is 61 billion, so I’d agree that math doesn’t seem accurate.

Additionally, you seemed to have pulled the cherry-picked quote and compared with the “current” impact and ignored the immediately following text on latent automation exposure (partially extracted for quote) that explains how it could have a greater impact that results in their 2.3t/39m estimate numbers. Seems odd to find those numbers in the report but not read the rest of the same section.

>I’m not sure how you got that 2.2% of 18.5 trillion in GDP attributed to labor is 61 billion

The number I googled for 2024 US GDP was 29.18 trillion, so thats part of it. I'm flexibke enough to adjust that if wrong.

>Additionally, you seemed to have pulled the cherry-picked quote and compared with the “current” impact and ignored the immediately following text on latent automation exposure

There's no time scale presented in that section thst I can find for the "latent" exposure, so its not very useful as presented. That's why I compared it to now.

Over 5 years; I'm not sure but it can be realistic. Over 20 years, If the US GDP doesn't absolutely tank, that's not necessary as impressive a number as it sounds. You see my confusion here?

>that explains how it could have a greater impact that results in their 2.3t/39m estimate numbers.

Maybe I need to read more of the article, but I need a lot more numbers to be convinced of a 40x efficiency boost (predicted returns divided by current gdp value times their 2.2% labor value) for anything. Even the 20x number if I used your gpd number is a hefty claim.

>Or presented a better metric than my formula above on interpreting "impact". I'm open to a better model here than my napkin math.