Hyperscalers spurred enterprise adoption of generative AI and IT budgets are feeling the crunch. As companies double down on hybrid cloud to power large language model technologies, they are struggling to keep cloud bills in check.
“The price-per-unit for what you need to run AI is higher,” said Chris Orbitals. “You’re running GPUs and TPUs — it’s not just a typical EC2 unit on AWS.”
More than 9 in 10 respondents reported climbing cloud bills in the last year, due in part to AI applications and automation tools. Roughly the same proportion said their FinOps cloud expense management practices need to include AI and other software services in addition to infrastructure.
The move to bring SaaS under the FinOps umbrella got a boost when the FinOps Foundation broadened the scope of the practice to encompass service-based applications and other cloud-based software solutions in February. IT asset managers joined FinOps efforts at roughly one-third of enterprises to help tame rising software audit costs, according to a midyear Flexera report.
“Our cloud spend is going up because we’ve added automation and AI,” Ortbals said of Tangoe.
“We’re running our own internal GPT, which is a cost we’re incurring in the public cloud on top of our normal spend to power our platforms,” said Orbals. “I think a lot of companies are going through that.”
AI has also upped the ante on shadow IT, a prime target area for FinOps-driven cost optimization.
Software procurements that escape the watchful eye of IT comprise more than one-third of SaaS costs, respondents to Tangoe’s study said. Two-thirds of companies uncovered wasted spend in productivity software, a category vendors like Microsoft have infused with LLM agents, coding assistants and other generative AI tools.
The trend amplifies the budgetary implications of shadow IT.
“Consumption-based billing just makes it easier to have rogue IT,” Ortbals said. “Departments can just put it on their purchasing card and off they go.”
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