Data Innovation

Watch now for a timely discussion by ITIF's Center for Data Innovation and Public First surrounding new polling data exploring how U.S. public sentiment toward AI is evolving. The conversation unpacks where Americans see promise or peril, how their views have shifted over the past year, and what these perspectives mean for lawmakers, business leaders, and the future of AI policy.

The UK should reject misleading claims that AI training is theft and instead adopt a modern, permissive copyright framework that protects creativity while enabling the innovation needed to become a global AI leader.

Congress should act to preempt state laws that impose broad requirements on the development and use of AI.

By prioritising the digitisation and availability of data that reflects this diversity, countries and communities stand a better chance of shaping AI in their own image, rather than submitting to someone else’s.

With the right infrastructure and vision, the United States can become a global leader in AI-enabled diplomacy. The State Department should seize this moment—not just to experiment with AI and increase organizational efficiency, but to embed AI at the core of how it conducts diplomacy in the 21st century.

The magnitude of the total fines against U.S. companies is extraordinary. To put the amount in perspective, it is roughly the same as the GDP of Fiji. It could cover the cost of sending five rovers to explore Mars. It would be enough to build two new football stadiums in Washington, DC. It could even pay for every household in America to buy six dozen eggs.

The Office of Management and Budget (OMB) issued two memos aimed at accelerating AI adoption across the federal government. But that vision won’t materialize unless other parts of the administration stop pulling in opposite directions or failing to act altogether.

Watch now for the Center for Data Innovation's discussion on the potential consequences of the UK government’s proposed option and how creating a more permissive text and data mining exception would advance the UK’s goals of being competitive in AI without undermining the rights of creators.

To modernize enforcement, the Consumer Product Safety Commission (CPSC) should use AI to analyze real-time and historical data, allowing it to predict and address risks in e-commerce supply chains before harm occurs.

U.S. AI policy prioritizes training compute while overlooking inference—the compute needed to deploy models effectively. As AI progress shifts toward optimizing inference, policymakers must adapt by supporting global deployment, refining export controls, and promoting energy-efficient AI to maintain U.S. competitiveness.