Ahead of the 2026 AI Impact Summit in New Delhi, the Center for Data Innovation and The Dialogue are convening an official pre-summit event, sponsored by Google, in Washington, D.C., on January 20, 2026.

Watch now for a panel discussion on how data and technology can create safer, healthier, and more productive workplaces, and the policies needed to encourage adoption while protecting workers.

Watch ITIF's Center for Data Innovation discussion on how the United States can build a durable AI alliance that creates strategic partnerships that are mutually beneficial and contains China’s growing technological influence in the Global South.

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.

Watch now for a panel discussion by ITIF's Center for Data Innovation on what the rise of agentic AI means for innovation, competition, and policy, how prepared the United States is to keep pace, and what policy shifts might be needed to ensure consumers and businesses can successfully develop and deploy AI agents.

Lawmakers risk misregulating grocery prices by targeting dynamic and algorithmic pricing tools, and should instead focus on enforcing existing laws against clearly defined deceptive practices.

Japan should revise its draft AI IP code to remove technically infeasible disclosure mandates and instead adopt workable, pro-innovation transparency standards aligned with international efforts like the Hiroshima AI Process to preserve U.S. alignment and avoid deterring AI investment.

While the U.S. has focused on securing AI systems themselves, it must urgently shift toward using AI defensively—through coordinated government, industry, and infrastructure efforts—to counter the growing threat of AI-powered cyberattacks on existing systems.

While false “Made in USA” claims are a real problem, the solution is not holding online marketplaces liable but strengthening data infrastructure and verification systems that enable regulators, consumers, and AI tools to more effectively identify and enforce legitimate claims.

China has surged ahead of the United States in adopting sidewalk delivery robots due to more proactive and coordinated policy experimentation, offering lessons for U.S. policymakers on how real-world pilots and clearer regulatory frameworks can accelerate deployment of autonomous delivery technology.

Agentic commerce—where AI agents autonomously shop and transact on users’ behalf—could deliver major efficiency gains, but outdated regulations and unresolved legal questions risk slowing adoption unless policymakers update rules built for human-driven transactions.

Center for Data Innovation Director Daniel Castro sent a letter to Maryland Senate Finance Committee Chair Pamela G. Beidle, Vice Chair Antonio L. Hayes, and members of the committee in opposition to Senate Bill 889.