Federal AI Strategy Raises Compliance Stakes for Banks and Big Tech 

The move was the subject of an analysis from the Steptoe legal firm. “Toward A National AI Framework: The Federal Strategy To Override State Regulation,” frames the order as more than rhetoric. It describes a federal strategy that pairs policy direction with enforcement posture, including the creation of an “AI Litigation Task Force” and instructions for agencies to evaluate and challenge state laws deemed inconsistent with federal priorities.

Steptoe also emphasizes the limits of executive authority. “Despite its sweeping language, the Order cannot, on its own, preempt state law,” the analysis says. That tension sets up a messy period in which federal agencies push for uniformity while states defend their statutes and the courts referee the boundaries of preemption.

For financial services firms, the practical takeaway is not a single new rulebook, but a faster-moving supervisory environment with higher expectations around governance, disclosure and controls. The analysis argues that the order “reinforces a principles-based supervisory approach while increasing expectations for accurate AI-related disclosures and governance.”

That approach matters because it tends to expand the scope of examination risk. A principles-based regime often relies on existing duties and anti-fraud authorities, then tests whether a firm’s AI systems, vendor stack and oversight processes are “reasonable” in context.

The analysis points to the Securities and Exchange Commission as an early signal of how this could land. The SEC Investor Advisory Committee recommended AI disclosure guidance “based on materiality.” That, along with the agency’s retreat from certain prescriptive proposals, supports a pivot toward familiar frameworks such as fiduciary duties, Regulation Best Interest, supervision and recordkeeping. For banks and market intermediaries, that is less about checking the box on a novel AI statute and more about ensuring models are governed like other high-impact systems that can affect customers, markets and financial reporting.

Related: Governing AI Through Standards: Europe’s Race Against Time

The Steptoe analysis also highlights how coordination and scrutiny could intensify across agencies. It cites the SEC Division of Examinations’ fiscal 2026 priorities, including assessing firm AI policies and the accuracy of registrant claims about AI, and it notes that the SEC’s AI Task Force plans to use AI tools to improve efficiency and accuracy. In practice, that combination can raise the stakes for marketing language, investor communications and internal documentation. It can also increase the downside of overstating capabilities, understating risks, or failing to demonstrate how systems are monitored and corrected.

The order’s promise of reduced reliance on state-focused compliance programs may also be less of a near-term relief than it appears. The analysis advises firms to rethink the “build to the strictest state” approach, but not to abandon it. It recommends separating core investor-protection controls from jurisdiction-specific requirements, given uncertainty about preemption and the durability of state regimes. That is a practical roadmap for financial institutions trying to manage AI across lines of business while state laws, federal guidance and litigation theories remain in flux.

For companies building and deploying AI across the economy, the message is straightforward. Expect more federal activity, faster policy evolution, and a compliance environment that rewards documented governance over aspirational claims.