Stanford HAI's ninth annual AI Index Report, spanning nine chapters across R&D, technical performance, responsible AI, economy, science, medicine, policy, education and public opinion. Its central finding: AI capability is not plateauing but accelerating — industry produced over 90% of notable frontier models in 2025, several of which meet or exceed human baselines on PhD-level science questions, multimodal reasoning and competition mathematics; performance on the SWE-bench Verified coding benchmark rose from 60% to near 100% in a single year; organisational adoption reached 88%, and four in five university students now use generative AI.

Stanford HAI's annual AI Index Report, published for the first time with an official Chinese translation. Highlights: scores on the demanding MMMU, GPQA and SWE-bench benchmarks rose 18.8, 48.9 and 67.3 percentage points respectively in one year; US private AI investment reached $109.1 billion in 2024 (about 12 times China's), with 78% of organisations using AI; the US produced 40 notable models to China's 15, yet Chinese models closed the MMLU-class performance gap to near parity; inference cost at GPT-3.5 level fell over 280-fold since November 2022; and US federal agencies introduced 59 AI-related regulations in 2024, more than double 2023.

Stanford HAI's seventh edition of the AI Index Report, providing comprehensive tracking of global AI development trends. The report analyzes nine dimensions: AI research and development, technical performance, responsible AI, economic impact, science and medicine applications, education, policy and governance, diversity, and public opinion. Key findings include the U.S. leading in top AI model production, generative AI investment surging to $25.2 billion, significant AI-driven labor productivity gains, and U.S. AI regulations rising from one in 2016 to 25 in 2023. Global public awareness of AI's societal impact has increased substantially, with rising concern levels alongside growing recognition of transformative potential.

Stanford HAI's annual AI Index Report, capturing the inflection around generative AI's breakout year: industry decisively overtook academia as the main producer of significant machine learning models (32 vs 3 in 2022); private AI investment fell year-on-year for the first time in a decade yet remained 18 times its 2013 level; AI-related laws passed across 127 surveyed countries grew from 1 in 2016 to 37 in 2022; and tracked AI misuse incidents rose 26-fold since 2012.

The 2022 AI Index Report from Stanford's Human-Centered AI Institute provides comprehensive benchmarking of global AI progress. Key findings include: private investment surged to $93.5 billion in 2021 (more than double 2020), US-China collaborations dominated cross-country AI research partnerships, large language models achieved record performance while exhibiting increased toxicity and bias, AI ethics research publications grew 5-fold since 2014, image classification training costs declined 63.6% since 2018, global AI legislation increased to 18 bills passed in 25 countries by 2021, and robotic arm prices fell 46.2% over five years. The report spans five chapters covering research and development, technical performance, AI ethics, economy and education, and policy and governance.

Stanford HAI's annual AI Index Report (the series skipped 2020, moving from the December 2019 edition to this March 2021 one). A record of the pandemic year: private AI investment grew 40% against the downturn to $67.9 billion in 2020, with drug discovery the most-funded area; China overtook the US in total AI journal citations for the first time, while the US kept its lead in conference-paper citations and significant model production. The report also documents the accelerating flow of AI talent into industry and persistent gaps in diversity data.

The 2019 AI Index Report from Stanford HAI is a comprehensive international AI benchmarking initiative covering nine dimensions including research and development, conferences, technical performance, economy, education, and autonomous systems. The report introduces the Global AI Vibrancy Tool, which benchmarks 28 countries across 34 indicators spanning research and development, economy, and inclusion. Developed with input from over 150 industry and academic experts, the report provides unbiased, rigorous data to help policymakers, researchers, and the public understand the global AI landscape.

The Stanford HAI 2018 AI Index Report is an independent initiative led by the AI Index Steering Committee, comprising experts from academia and industry. The report aggregates diverse metrics and data to provide unbiased, rigorous, and comprehensive insights for policymakers, researchers, journalists, executives, and the public to understand the AI field. The report is structured into four main sections: Volume of Activity (including conference attendance and VC investments), Technical Performance, Derivative Measures, and progress towards Human Performance.

The 2017 AI Index Report from Stanford HAI aggregates data on AI progress across volume of activity (conference attendance, VC investments), technical performance benchmarks, and sector-wide trends. The report introduces the AI Vibrancy Index to measure the liveliness of AI development across academia and industry, includes expert commentary, and tracks areas where AI systems approach or exceed human performance. It serves as a foundational resource for understanding AI development.