President Trump’s latest executive order on artificial intelligence signals a shift in federal posture: lighter-touch oversight, a renewed emphasis on innovation, and a preference for centralized federal direction over a fragmented state-by-state approach. But beyond the rhetoric, the practical implications for organizations deploying AI are more restrained and far less disruptive than they may initially appear.

For foundational model developers, Trump’s AI executive order reshapes expectations around federal oversight and accountability. For most AI deployers, it has a much less profound impact, reinforcing the need to govern how AI is used within existing legal and regulatory frameworks, rather than how it is built. In short, for AI deployers, the fundamentals of governance remain largely intact.

A Familiar Federal Playbook

At its core, Trump’s AI executive order reflects themes that have appeared repeatedly in prior federal AI initiatives, including earlier Trump-era directives:

• Continuity with prior federal guidance. The order aligns with earlier federal efforts such as OMB Memorandum M-25-21, reinforcing expectations around AI inventories, risk assessment, transparency, designated oversight, and training, while reframing them through a pro-innovation lens rather than prescriptive control.
• Leverage AI for national benefit. The order emphasizes AI as a driver of economic growth, efficiency, and global competitiveness.
• Encourage adoption, not restraint. The focus is on accelerating responsible use rather than imposing new restrictions.
• Central coordination. The order calls for federal leadership through committees and coordinated oversight mechanisms.
• Rely on existing law. Rather than creating new AI-specific prohibitions, the order points back to existing legal frameworks tied to civil rights, labor, and consumer protection laws.

The message is not the absence of governance, but a reframing of governance as an enabler of scale.

What This Really Means for AI Governance

Despite the emphasis on deregulation, core governance expectations remain unchanged:

• Discrimination remains illegal. Title VII and other civil rights laws continue to apply fully to AI-driven decision-making.
• AI inventories still matter. Organizations are expected to know where AI is used, how it functions, and what risks it introduces.
• Documentation enables scale. Inventorying and assessing AI use cases is essential not only for compliance but to safely expand adoption.
• AI consent litigation is already active. Lawsuits tied to consent, transparency, and notice, particularly around automated decision-making, biometric data, and AI-powered interactions, are already working their way through the courts. Regardless of shifts in federal policy, these claims are grounded in existing privacy, wiretap, and consumer protection laws, making consent management and disclosure an ongoing risk area for organizations deploying AI.

In practice, governance remains the mechanism that allows organizations to deploy AI with confidence, particularly as scrutiny increases.

The Legal Reality: Expect Court Challenges

Trump’s AI executive order has reach that is likely to face meaningful legal scrutiny.

Under the U.S. Constitution, states generally retain authority to regulate in areas that Congress has not expressly preempted, and AI remains firmly within that category. Executive orders, unlike statutes passed by Congress, do not have the legal force necessary to override state legislative action.

That limitation was highlighted by Florida Governor Ron DeSantis, who publicly stated that an executive order cannot preempt state law, noting that only Congress could theoretically do so through legislation. His comments are especially notable given Florida’s own recent proposals introducing AI-related measures, signaling that state-level AI policymaking will continue regardless of federal executive guidance.

As a result, several questions are likely to be tested in court:

• Whether the federal government can limit state AI regulation absent congressional action
• How far executive authority can extend in shaping national AI policy
• Where the line lies between federal coordination and state sovereignty

The practical takeaway is clear: state AI laws are unlikely to disappear simply because of a federal executive order, and legal uncertainty will persist.

State Laws: Uneven Terrain

From a governance perspective, the state landscape remains fragmented.

AI Regulations Unlikely to be Challenged

• Texas Responsible AI Governance Act
  A business-friendly framework emphasizing:
  • Compliance with existing anti-discrimination laws
  • Privacy, consent, and transparency obligations
  • Risk assessments for AI use cases
  • Appropriate notice requirements

These provisions closely align with widely accepted AI governance best practices.

AI Regulations Likely to be Challenged

• California’s AI transparency and deepfake regulations (squarely in the target of Trump’s AI executive order)
• Colorado’s algorithmic discrimination rules
• New York’s personalized pricing disclosure requirements

These laws may face challenges on the grounds of overreach, leaving their long-term enforceability uncertain.

Potential Challenge Unclear

• California’s CCPA/CPRA ADMT rulemaking
• Florida’s evolving AI proposals

For now, their trajectory remains unsettled.

Does This Change AI Governance?

For most organizations deploying AI, the answer is only marginally.

The core expectations remain consistent:

• Follow existing anti-discrimination and consumer protection laws
• Comply with privacy and transparency requirements
• Assess, document, and monitor AI risks
• Maintain visibility into AI use across the organization

Foundational model developers may experience greater impact as federal policy evolves. But for most enterprises and public-sector entities, the same governance fundamentals continue to apply.

One Certainty: More Uncertainty

If there is one clear outcome of Trump’s AI executive order, it is increased uncertainty, especially around the balance of federal and state authority.

That uncertainty does not reduce the need for governance. If anything, it reinforces it. Organizations that can clearly document their AI use, demonstrate compliance with existing laws, and show thoughtful risk management will be best positioned regardless of how the courts ultimately resolve these questions.

In an unsettled regulatory environment, proactive and defensible AI governance remains the strongest foundation for scale. For information on how Truyo is helping organizations build defensible AI governance programs, collect compliant consent, assess AI models, and more, click here or reach out to hello@truyo.com for a complimentary AI governance program evaluation.