In August 2025, I reflected on the state of AI policy in the United States vs the European Union and the widening gap between the two approaches. At the time, the core difference was clear: Europe was focused on codifying guardrails through regulation, while the United States was prioritizing speed through industrial policy and market-driven adoption. At the time, the debate was framed as values versus velocity.
As 2025 came to a close, it was unmistakable that the year was focused on execution, not new principles. Europe moved from writing rules to enforcing them while the United States moved from signaling to deploying AI at speed. And U.S. courts, not legislatures, ended up defining the most consequential rules on copyright and AI training data – rules that companies are now aligning to globally, regardless of where their models are built or deployed. As 2026 begins, uncertainty has not disappeared, but it has shifted from abstract questions of intent to concrete questions of responsibility.
The U.S. Path: Speed Became Policy
In the United States, the release of Winning the AI Race: America’s AI Action Plan in July marked a transition from rhetoric to action. Infrastructure, procurement, and deregulation quickly became the dominant levers. Expedited permitting for data centers and semiconductor facilities, relaxed regulatory thresholds, and directives encouraging federal AI adoption signaled a deliberate choice: competitiveness first, guardrails later.
Ethical principles did not vanish, but they were clearly deprioritized in favor of acceleration. The implicit bet was that speed would outpace regulation. That bet has paid off operationally, but it has also shifted the burden of responsibility squarely onto companies. Scrutiny did not disappear in the U.S.; it migrated to courts, contract negotiations, procurement requirements, and public trust, where failures are punished after the fact rather than prevented upfront.
The EU Path: Guardrails Are Now Being Tested
Europe’s story in 2025 looked very different. The EU AI Act moved from legislative ambition to enforcement reality. Obligations phased in, oversight bodies were stood up, and companies began grappling with system classification, documentation requirements, and audit readiness. What once felt abstract is now operational.
The EU approach continues to favor predictability and precaution, even at the cost of flexibility. Importantly, this has not slowed global AI adoption. Instead, it has reframed how companies talk about risk, transparency, and accountability. Even U.S.-based firms are increasingly borrowing EU-style governance internally, not because they are legally required to but because they need a defensible operating model in a fragmented regulatory environment.
The False Choice Has Collapsed
One of the clearest lessons of 2025 is that the perceived choice between U.S. speed and EU compliance no longer exists. Companies cannot optimize exclusively for one regime without being exposed in the other. They are now expected to move quickly and demonstrate control, often simultaneously.
Complicating this further, U.S. courts have emerged as de facto standard-setters on issues like copyright and training data, shaping baseline expectations that global companies are increasingly aligning to, regardless of where they operate.
Governance has therefore become the connective tissue between these systems. It is no longer a philosophical exercise or a compliance checkbox, but the mechanism that allows organizations to operate across jurisdictions, withstand legal scrutiny, and maintain credibility while scaling rapidly.
What 2025 Made Clear for Leaders and Boards
For leadership teams and boards, 2025 underscored that AI governance is not about ethics statements. It is about operational design. Infrastructure decisions, data provenance, model accountability, and incident response planning now sit alongside financial and cyber risk as board-level concerns.
Legal exposure is increasingly shaped by courts and contracts rather than comprehensive legislation, and trust, credibility, and license to operate have emerged as strategic assets. Companies that treated governance as a downstream consideration are now paying for that choice.
Looking Ahead to 2026
As 2026 unfolds, several forces will continue to shape the landscape: enforcement actions under the EU AI Act, further U.S. court rulings on copyright and training data, growing pressure for opt-out tools and dataset transparency, and persistent infrastructure constraints around power, chips, and permitting. Political dynamics also introduce the risk of policy whiplash, particularly in the U.S.
The takeaway is not alarm, but realism. The debate is no longer about whether AI will be regulated or accelerated. It is about whether organizations are prepared to operate credibly in an environment that demands both.
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