Stanford Human-Centered Artificial Intelligence (HAI) is an interdisciplinary research institute at Stanford University focused on understanding and shaping the societal impacts of artificial intelligence. The institute conducts research on AI ethics, policy, economics, and human-centered design, while also producing influential reports that track global AI trends and development.

Stanford HAI serves as a hub for collaboration among researchers, policymakers, industry leaders, and civil society representatives. The institute's work spans multiple disciplines including computer science, sociology, economics, law, and business, reflecting a commitment to studying AI through a multifaceted lens rather than purely technical perspectives.

Stanford HAI is responsible for producing the annual AI Index, a comprehensive report that tracks trends in artificial intelligence development, deployment, and impact across the globe. The 2026 AI Index report provided critical insights into the state of the AI landscape¹⁾.

Key findings from recent reports include:

* Social and Psychological Divide: The index documents a growing gap between AI developers and the general public regarding AI safety, alignment, and societal implications. * Environmental Costs: Reports emphasize the substantial environmental impact of training frontier AI models, including energy consumption and resource requirements. * Geopolitical Competition: Recent analyses indicate that the United States' competitive lead in AI capability is diminishing relative to Chinese AI developments and capabilities. * Development-Adoption Gap: Research reveals a significant disparity between nations leading AI development and those achieving widespread AI adoption. While the U.S. leads in AI creation, it ranks 24th globally in adoption, trailing countries like Singapore and the UAE²⁾, suggesting that technological leadership does not automatically translate to societal integration.

The institute maintains research programs across several critical areas:

* AI governance and policy frameworks * Responsible AI development practices * Economic impacts of AI automation * Public understanding and trust in AI systems * Educational initiatives around AI literacy

• Stanford AI Index 2026
• System-Level AI / Ambient Intelligence
• Shanghai AI Lab
• Stanford University
• AI-Native Organization