As enterprises struggle to manage their AI strategies, the US AI regulatory environment is sending a wide range of contradictory signals. OpenAI’s Wednesday announcement that it will now release GPT-5.6 Sol, along with Terra and Luna, on Thursday highlights the confusion.
Initially, the US government said that it was asking OpenAI to saying simply: “GPT-5.6 Sol, along with Terra and Luna, will launch publicly this Thursday. We’re expanding preview access globally now.” No details were released about the extent of the expansion.
Then the White House issued a statement, a copy of which it emailed to InfoWorld, saying that the US government “did not give OpenAI a ‘green light,’ approval or clearance to release its models. No such permission is required or granted. The Administration does not provide approvals for private companies to release AI models – decisions on timing and scope of releases rest entirely with the companies.”
The statement then quoted from the .
The ‘worst of both worlds’
, principal analyst at Moor Insights & Strategy, agreed with Carhart and described the overall back-and-forth as “a bit of pageantry. OpenAI needs its model to look as powerful, potentially dangerous, as Anthropic’s so it can be a contender to be at the absolute frontier. It also helps to burnish OpenAI’s PR efforts to look more responsible than it has in the past.”
Furthermore, he added, “tech CEOs are acutely aware that flattery towards this administration could keep regulators or the threat of regulation at bay.”
Criteria not clear
, director of AI standards and governance at AI agent vendor Zenity, shared the frustration that little to no actionable compliance data is being released.
“Nobody outside a closed room can tell you what standard [the model] passed because it was never written down. For two weeks, [US government officials] kept a model out of defenders’ hands that’s better at guarding your network than breaking into anyone else’s,” Lambros said. “Call that a security review if it helps you sleep better. But it reads to me like a bouncer working a velvet rope nobody hired him to run, waving people through today because he’s in a better mood than he was a couple of weeks ago.”
This unpredictability is likely to have impacts on AI strategy far beyond traditional compliance concerns, Lambros said.
“We’ve built way too much operational reliance on these models to hang it on a review with no rulebook,” he said, pointing out that hospitals, pipelines, banks and water utilities are relying on frontier AI whose availability “can swing from ‘on’ to ‘off’ to ‘on’ with no notice, no appeal, and no published standard behind any of it.”
“You can’t run critical infrastructure on a tool that runs fine Friday and is offline by Monday because an approval process nobody can see reached a verdict nobody can predict,” Lambros said. “That is a supply chain risk with a government hand on the switch, and almost nobody has priced it into a continuity plan.”
To protect themselves, companies need to adjust their expectations. “Treat model availability like any single point of failure you don’t own by standing up a fallback you’ve tested, getting a continuity clause in your contract, and drilling for the blackout, because ‘the government backed off this time’ is not a plan,” he advised.
This article originally appeared on InfoWorld.
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