Now that attention within the AI revolution has one again firmly turned toward the cost-benefit equation (i..e., ROI) of tokens (see "From Singularity To Tokenomics: The AI Narrative Just Hit A Serious Snag") in particular, and the trillions behind the AI spending rollout in general, and we say once again because every few months we get some iteration of the following report from Goldman published almost two years ago today…

… we have more bad news: according to a global survey by Bain, cost savings from automation are broadly falling short of projections. Which means that those expecting big savings from their investments in artificial intelligence, which is most companies, will be disappointed.

The missed targets "should be making executives uncomfortable," since many of them are approving increased spending for artificial intelligence on the basis of expected savings, the consulting firm said in a report shared exclusively with Bloomberg News. The problem is there are little actual savings to speak of. 

The survey, completed in April, was based on responses from executives at 951 companies with more than $100 million in revenue, across nine sectors: retail, technology, advanced manufacturing, healthcare, consumer products, energy, financial services, telecom/media/entertainment and insurance.

It found that among companies measuring their AI cost savings, the largest share (40%) realized reductions of 10% or less. Predictably, most had been expecting to see far more meaningful improvement, especially since they spent far more than that on the new technology.

Here's the part that Bain found the most troubling: 44% of large companies that are funding their next wave of AI spending are basing those investments on the last round of savings – savings that haven't yet materialized. 

"The prior wave underdelivered. The savings pool is smaller than assumed," Bain warned. "And the investment case for the current wave was sized against projections rather than actuals." Kinda like the bubble in AI forward earnings: based on projections – which as any intern can tell you can flip on a dime – rather than actuals.

"Self-funding the next wave from past returns sounds like discipline. In reality, it is a circular bet with a structural leak," the firm cautioned, and concluded that "The technology worked. The value didn't arrive."

Whether driven by hope or FOMO or a blend of both, the AI boom is exposing divides between promise and reality. An MIT research report last year showed that 95% of corporate AI pilots fall flat and concluded that the "primary factor keeping organizations on the wrong side of the GenAI Divide is the learning gap, tools that don't learn, integrate poorly, or match workflows."