Enterprises in shaky spot amid calls for an AI slowdown

Shaky ground for enterprises

With all the calls for the federal government to act, enterprises find themselves in an uncertain position, adding even more unpredictability to a technology that is already unstable in some ways.

"Enterprises are having to choose AI platforms, vendors, skills, architectures and operating models while knowing that the underlying technology may change before those investments fully mature," said Kashyap Kompella, RPA2AI Research founder. "The showdown debate adds several new uncertainties at once."

Those fears, doubts and open questions include whether frontier development will continue at its current torrid pace or slow, open models become restricted, and some important AI capabilities remain privately controlled.

However, some of the fears at this point could be exactly what OpenAI and Anthropic want, because enterprises are realizing that despite the impressive performance of frontier models, they're more expensive than open models and that enterprises can do more with less with smaller and open-weight and fully open source AI models, said David Nicholson, an analyst at Futurum Group.

"Every day that goes by, fewer and fewer workloads legitimately need what the leading edge of frontier models can deliver," Nicholson said, noting that Anthropic and OpenAI are nearing highly anticipated and lucrative IPOs.

"There is no question that the leading edge of frontier models is amazing, but when you start pricing the cost of what you're paying for and looking at the task at hand, there are more economically efficient ways to do what OpenAI and Anthropic are both offering to the market," he continued.

Preserving the lead in the AI race

With OpenAI and Anthropic under increasing price pressure from developers of mostly open models, the appeals for federal AI regulation appear less about doing what is good for society and more about preserving their lead in the AI race.

"In the interest of preserving their duopoly in this space, they are willing to let the government regulate them," Nicholson said, "What they're asking for is for the federal government to step in and protect them from Chinese competition."

The recent advancements by Chinese AI vendors such as Alibaba, Moonshot AI and Z.ai, among others, mean that frontier model makers have realized that open models are nearly as good as the models they release, but available at far lower cost.

"They are under siege by a lot of the emergence of all these open weight models," Lian Jye Su, an analyst at Omdia, a division of Informa TechTarget, said. "It is a business risk that they are facing at the verge of the IPO."

He added that Chinese vendors have also argued that the call for regulation is unique to the U.S., since China is already enacting some regulations. For instance, China recently introduced rules to keep minors from forming relationships with AI chatbots.

"Maybe it's for the IPO, maybe it's in [Anthropic's] interest to slow things down, but it's still a very important thing because the U.S. fundamentally doesn't have that AI governance regulation as compared to China," Su said. He added that Anthropic also sees a risk from open source because open source -- a decentralized and highly public technology framework -- entails less governance.

Hedging against uncertainty

For enterprises, though, doubt about whether regulation will extend to open source AI technology and geopolitical tensions involving Chinese models means they could cave in and use frontier models regardless of the cost, so that they can hedge themselves against the future possibility of regulation, Nicholson said.

"[Enterprises are] willing to pay for certainty," he said.

 While enterprises deal with uncertainty about the move toward regulation, the best approach remains proactive, Kompella said.

"Governance has to become an operating capability, not a checkbox exercise," he said. He added that enterprises can't treat AI governance as a policy document that they only look at periodically.

"That is inadequate for systems that can access data, write code, use tools, make decisions and act autonomously," Kompella added. He said that enterprises should prioritize early access and preview programs to get closer to frontier capabilities, particularly with regard to AI cybersecurity.

"Cyber preparedness becomes central," Kompella continued. "As agentic systems gain stronger offensive and defensive capabilities, security teams need to assume that AI will compress both attack and response cycles."

Esther Shittu is an Informa TechTarget news writer and podcast host covering artificial intelligence software and systems.