As the Accenture call shows, it's making even some of the most AI-bullish organizations question their usage, because measuring the spend and the return on that investment is proving all but impossible.
As Kwak said in the leaked audio, "Leadership, especially at the CFO, COO, and CIO level, are still asking the question of whether they’re getting value from what we’re spending on in the context of AI.”
Although large language models are proving to be extremely useful in niche cases, their effectiveness at a broader range of tasks is more nebulous. Especially when it comes to financing it. When managers and executives look at AI budgeting and a return on that investment, it's hard to square away the numbers.
When you can't know how many tokens a task will take to complete, or whether the task will be completed effectively on the first, second, or third attempt; when you can't completely control the length of the output, or know whether that output will be wrong, or a lie, or just a random hallucination, how do you measure return on the investment in that tool?
"We’re hitting this inflection point where AI is becoming material to the cost structure; spend is becoming very unpredictable," Accenture's Kwak said during the meeting. Although the overall bill of AI costs is visible, he suggested, finding the specific value attributed to that token spend was not.
This seems to have created a culture of task hierarchy within Accenture, where some tasks are deemed more worthy of AI token use than others. When Kwak positioned himself to show some slides during the meeting, Accenture's client group lead, Stuary Henderson, joked that he hoped Kwak didn't use AI to convert a PDF into images and then markdown files.
“I’m learning that’s one of the big token chewers," he said. “Turning PDFs into markdown: is that right?”
Kwak agreed that Accenture data did show some tasks being completed using AI that didn't really need it, and were using unnecessary tokens because of it. Much of that problem, he suggested, was down to non-technical staff overusing it.
“We’re seeing from some of the data internally at least that it’s actually not our engineers that are driving the token consumption. It’s a lot of the non-engineers that are doing some of those behaviors."
Now that Accenture has encouraged heavy AI adoption among its clients, it finds itself in the bizarre position of having to discourage it or at least encourage more studious use of it. It now sees its next opportunity as a way to advise clients on how to "think about token economics."
It's working on a tool called "Token IQ" to help advise clients, according to the call, but hasn't made any announcement so far.
What's clear from the Accenture leak and actions of some of the major tech companies, which have previously been so bullish on AI use, is that the finances of mass AI adoption at the per-token scale don't line up. Without a clear way to measure the return on AI investment, we may find even the most tokenmaxxing companies look to restrict access and spend through the rest of 2026 as they re-address AI strategy.
Jon Martindale is a contributing writer for Tom's Hardware. For the past 20 years, he's been writing about PC components, emerging technologies, and the latest software advances. His deep and broad journalistic experience gives him unique insights into the most exciting technology trends of today and tomorrow. ","collapsible":{"enabled":true,"maxHeight":250,"readMoreText":"Read more","readLessText":"Read less"}}), "https://slice.vanilla.futurecdn.net/13-4-24/js/authorBio.js"); } else { console.error('%c FTE ','background: #9306F9; color: #ffffff','no lazy slice hydration function available'); } Jon Martindale Freelance Writer Jon Martindale is a contributing writer for Tom's Hardware. For the past 20 years, he's been writing about PC components, emerging technologies, and the latest software advances. His deep and broad journalistic experience gives him unique insights into the most exciting technology trends of today and tomorrow.
Key considerations
- Investor positioning can change fast
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Reference reading
- https://www.tomshardware.com/tech-industry/artificial-intelligence/SPONSORED_LINK_URL
- https://www.tomshardware.com/tech-industry/artificial-intelligence/the-ai-tokenmaxxing-party-is-crashing-over-spiraling-costs-leaked-consulting-firm-audio-suggests-no-one-is-sure-how-to-measure-ai-effectiveness#main
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