Midterm results will raise AI costs and compliance questions for IT leaders

IT leaders need to quickly adapt IT strategies as AI and data centers will face more scrutiny following the US midterm elections, analysts said. Concerns around AI and…

IT leaders need to quickly adapt IT strategies as AI and data centers will face more scrutiny following the US midterm elections, analysts said. Concerns around AI and data centers helped Democrats sweep the US House and Senate. Tighter restrictions, more oversight and slower approvals could slow AI deployment and raise costs. An exit poll conducted by SSRS and shared by NBC News showed that 56% of voters considered AI and data centers a major factor in their vote.

The voter concerns revolve around AI data centers consuming electricity, water, and other resources, with the costs being passed on to consumers and local municipalities, said Jack Gold, principal analyst at J. Gold Associates. “There is not so much a backlash against the IT industry itself, but more against the thought that increased data centers will raise costs for normal consumers and do things to home values and land use,” Gold said.

Over the next two years, there will be more pressure to show who benefits, who pays, and who answers when something goes wrong, said Stephanie Walter, practice leader for the AI stack at HyperFRAME Research. IT leaders should keep deploying AI where it improves the work, while building the evidence to defend those decisions, Walter said. “A new Congress will not fix poor data, unreliable answers, or an application nobody needs,” Walter said.

“Do not assume AI services will always get cheaper just because technology usually does,” said David Linthicum, founder of Linthicum Research, in a LinkedIn post titled “The Midterms Put the AI Industry on Notice.” The election showed that AI isn’t just an enterprise issue anymore, but a kitchen table conversation. AI will face more resistance, scrutiny, and hearings, and “more demands to justify the resources it consumes,” Linthicum said. Building out AI infrastructure could get more expensive, and the costs will show up somewhere.

“They may show up in token pricing. They may show up in enterprise contracts. They may show up in limited availability. They may show up in stricter usage policies,” Linthicum said. Enterprises will need to rethink how they build AI systems, Linthicum said. CIOs could adopt smaller models, use tokens more efficiently, and make more careful decisions about what runs in the public cloud, he said.