ΑΙhub.org
 

2026 AI Index Report released


by
15 April 2026



share this:

Image from AI Index Report. Reproduced under CC BY-ND 4.0 licence.

The ninth edition of the Artificial Intelligence Index Report was published on 13 April 2026. Released on a yearly basis, the aim of the document is to provide readers with accurate, rigorously validated, and globally-sourced data to give insights into the progress of AI and its potential impact on society.

Hear from some of the people behind the report:

The 2026 AI Index Report comprises nine chapters, covering: research and development, technical performance, responsible AI, economy, science, medicine, education, policy and governance, and public opinion.

The report authors have highlighted 10 key takeaways, and these are as follows:

  1. AI capability is accelerating and reaching more people than ever. Model performance continues to improve against benchmarks, and 80% of university students now use generative AI.
  2. The USA-China AI model performance gap has effectively closed. The USA still produces more top-tier AI models and higher-impact patents, while China leads in publication volume, citations, patent output, and industrial robot installations. South Korea has the most AI patents per capita.
  3. The USA hosts the most AI data centres, with the majority of their chips fabricated by one Taiwanese foundry. With 5,427 data centres, the USA hosts 10 times more than any other country, and also consumes the most energy.
  4. AI models can win a gold medal at the International Mathematical Olympiad but cannot reliably tell time. Gemini Deep Think earned a gold medal at IMO, yet the top model reads analogue clocks correctly just 50.1% of the time.
  5. Responsible AI is not keeping pace with AI capability. Recent research has found that improving one responsible AI dimension, such as safety, can degrade another, such as accuracy.
  6. The USA leads in AI investment, but its ability to attract global talent is declining. The number of AI researchers and developers moving to the USA has dropped 89% since 2017, with an 80% decline in the last year alone.
  7. AI adoption is spreading at historic speed. Generative AI reached 53% population adoption within three years, faster than the PC or the internet, though the pace varies by country and correlates strongly with GDP per capita.
  8. Formal education is lagging behind AI, but people are learning AI skills at every stage of life. Over 80% of USA high school and college students now use AI for school-related tasks, but only half of middle and high schools have AI policies in place, and just 6% of teachers say those policies are clear.
  9. AI sovereignty is becoming a defining feature of national policy. National AI strategies are expanding, and state-backed investments in AI supercomputing are rising in parallel.
  10. AI experts and the public have very different perspectives on the technology’s future. 73% of experts expect a positive impact of AI on jobs, compared with just 23% of the public.

Useful links



tags:


AIhub is dedicated to free high-quality information about AI.
AIhub is dedicated to free high-quality information about AI.

            AUAI is supported by:



Subscribe to AIhub newsletter on substack



Related posts :

How much can fair budget-division rules resist manipulation?

The authors write about their award-winning IJCAI-ECAI paper: "Approximate Strategyproofness in Approval-based Budget Division".

AI dives into a sea of data, from plankton to pollution

  16 Sep 2026
“Faster and cheaper monitoring means problems like plankton decline, litter accumulation, oil spills and coral degradation can be picked up and acted on sooner."

Interview with Yash Saxena: how is external knowledge used in AI systems?

  15 Sep 2026
What happens to information from external sources as it moves through an AI system?

When AI art has no author: Study finds generated images often can’t be traced to training data

  14 Sep 2026
A new method for surgically removing training examples from a model reveals that as datasets grow, the link between what a model learns and what it produces dissolves.

AI in nature conservation: powerful tool or dangerous shortcut?

  11 Sep 2026
AI provides opportunity for future biodiversity conservation but introduces risks .

Improving the process for large-scale recommender systems: an interview with Haruka Kiyohara

  10 Sep 2026
Credit-assigned policy gradient for early stage retrieval in two-stage ranking.

The Machine Ethics podcast: Data Collective with E.M. Lewis-Jong

Ben chats to E.M. Lewis-Jong about the promise of AI and making human connection easier, speech recognition and supporting linguistic diversity, making useful technologies that have a purpose, and more.

AI for ethology: an interview with Isla Duporge

  08 Sep 2026
Deep learning is becoming a powerful tool for understanding animal behaviour and tracking populations.



AUAI is supported by:







Subscribe to AIhub newsletter on substack




 















©2026.05 - Association for the Understanding of Artificial Intelligence