Companies are reportedly finding it increasingly difficult to forecast their AI spending.
That’s according to a report Monday (Oct. 5) by The Wall Street Journal (WSJ), which cites one recent study showing that just 11% of almost 400 surveyed businesses could accurately project their artificial intelligence (AI) costs.
The report notes that AI differs from standard software in that it “behaves more like a human worker,” taking actions and making decisions and mistakes, all on the clock.
Although more advanced models typically cost more per token, the WSJ said, they can sometimes carry out tasks more efficiently, which translates to lower costs.
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While more advanced AI models tend to cost more per token, they can sometimes perform tasks more efficiently, leading to lower overall costs. At the same time, asking a cheaper model to do something it isn’t designed to handle could lead to a token run-up, the report said.
This idea was tested earlier this year by researchers from Stanford University, Carnegie Mellon University, and the University of California, Berkeley, as well as Microsoft Research. They had models conduct more than 6,800 tasks in areas such as math, programming and science. In 32% of scenarios, lower-priced models actually cost more than their higher-priced counterparts.
“The practical takeaway is clear,” said Lingjiao Chen, one of the researchers. “Price alone should not be used to infer which model is actually cheaper.”
In related news, the September PYMNTS Intelligence report “AI at Work: Why Deeper Enterprise Use Produces Stronger Returns” found that the 60 U.S. companies surveyed about their AI usage deployed the technology in an average of 7 out of 8 business functions. These included payments, finance, product development and customer experience.
“Yet only 20% of the 437 deployments examined are embedded in a function’s regular work,” PYMNTS wrote last month. “The findings suggested an encouraging path to stronger returns for companies ready to put the technology to fuller use.”
The research also found that 62% of surveyed companies spent more than $10 million on new artificial intelligence tools in the last year. Companies with deeper deployment said they ran into more obstacles, such as gaps in skills and unclear responsibility for the technology.
“Earlier experience may help,” the report added. “Among firms that had embedded older forms of AI in at least two functions before 2022, 47% have now embedded newer AI in three or more.”
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