Stanford University's Institute for Human-Centered Artificial Intelligence (HAI) has released its eighth annual AI Index, providing a data-driven overview of the global artificial intelligence landscape as of May 2025.
The 2025 AI Index from Stanford University's Institute for Human-Centered Artificial Intelligence cuts through the confusion with a 400+ page report stuffed with graphs and data on R&D, technical performance, responsible AI, economic impacts, science and medicine, policy, education, and public opinion.
Last year, 40 notable models came from the United States, while China had 15 and Europe had 3 (incidentally, all from France). Almost all of those 2024 models came from industry rather than academia or government. As for the decline in notable models released from 2023 to 2024, the index suggests it may be due to the increasing complexity of the technology and the ever-rising costs of training.
Industry is racing ahead in AI development, with nearly 90% of notable AI models in 2024 coming from industry, up from 60% in 2023, while academia remains the top source of highly cited research. The AI Index doesn't have precise data on training costs because many leading AI companies have stopped releasing information about their training runs. However, researchers partnered with Epoch AI to estimate costs based on details about training duration, hardware type and quantity. The most expensive model they could estimate was Google's Gemini 1.0 Ultra, with a breathtaking cost of about US $192 million.
While the U.S. maintains its lead in quantity, Chinese models have rapidly closed the quality gap: performance differences on major benchmarks such as MMLU and HumanEval shrank from double digits in 2023 to near parity in 2024. China also continues to lead in AI publications and patents.
AI is becoming more efficient, affordable, and accessible. Driven by increasingly capable small models, the inference cost for a system performing at the level of GPT-3.5 dropped over 280-fold between November 2022 and October 2024. At the hardware level, costs have declined by 30% annually, while energy efficiency has improved by 40% each year. Open-weight models are also closing the gap with closed models, reducing the performance difference from 8% to just 1.7% on some benchmarks in a single year. Together, these trends are rapidly lowering the barriers to advanced AI.
Businesses are increasingly adopting AI technologies. In 2024, the proportion of survey respondents reporting AI use by their organizations jumped to 78% from 55% in 2023. Similarly, the number of respondents who reported using generative AI in at least one business function more than doubled—from 33% in 2023 to 71% last year. However, according to one index tracking AI harm, the AI Incidents Database, the number of AI-related incidents rose to 233 in 2024—a record high and a 56.4% increase over 2023. Among the incidents reported were deepfake intimate images and chatbots allegedly implicated in a teenager's suicide.