Dive Brief:
- Token prices are leading businesses to adjust their AI deployment timelines amid a surge in compute costs, according to an EY report released this week. The company surveyed 500 U.S.-based decision-makers in SVP roles and above.
- More than 4 in 5 businesses investing in AI reported internal concerns over AI token usage and related costs of AI implementation. However, 37% of businesses are expanding the scope of their planned AI implementations despite the concerns, compared to just 15% who shifted to narrower deployments.
- “Companies are showing signs of reckoning with setting priorities rather than merely driving adoption,” said EY Global AI Consulting Leader Dan Diasio in the report. “Those priorities must be focused on doing different things, not the same things differently.”
Dive Insight:
After an era of large-scale AI deployment efforts, businesses are grappling with mounting AI expenses across compute, software and training. For some, the focus has landed on the age-old dilemma of buy vs. build.
Three-quarters of senior leaders with ongoing AI investments find off-the-shelf software solutions don’t align with their IT needs, and nearly 9 in 10 businesses have either fully deployed or are piloting programs to develop in-house AI, according to EY.
Vendors are getting wise to cost-consciousness among enterprise leaders. OpenAI said it slashed the cost of its Luna and Terra models earlier this week, while Oracle and AWS unveiled product changes last month aimed at helping leaders manage costs more effectively.
“This is a technology that moves the goal posts every six weeks, so it’s understandable that executives haven’t figured out the roadmap or the right narrative for change,” Diasio said in the report. “Organizations must be intentional about which initiatives they take on and driving them through financial value, or else they end up running in place.”
With costs in mind, visibility is also top of mind for leaders. More than two-thirds of companies lack accurate visibility into AI software use, according to Flexera data released in June. Roughly 3 in 5 flagged a year-over-year increase on AI overspend, Flexera found.
FinOps, a practice initially targeting cloud costs, has expanded its scope to include managing AI costs. The Tokenomics Foundation, an offshoot of the Linux Foundation unveiled last month, aims to help businesses get enterprisewide AI spending under control.
