[2606.15708] Artificial Intelligence Index Report 2026

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Computer Science > Artificial Intelligence

arXiv:2606.15708 (cs)

[Submitted on 14 Apr 2026]

Title:Artificial Intelligence Index Report 2026

Authors:Sha Sajadieh, Loredana Fattorini, Raymond Perrault, Yolanda Gil, Vanessa Parli, Lapo Santarlasci, Juan Pava, Nestor Maslej, Russ Altman, Erik Brynjolfsson, Carla Brodley, Jack Clark, Virginia Dignum, Vipin Kumar, James Landay, Terah Lyons, James Manyika, Juan Carlos Niebles, Yoav Shoham, Elham Tabassi, Russell Wald, Toby Walsh, Dan Weld<br>View a PDF of the paper titled Artificial Intelligence Index Report 2026, by Sha Sajadieh and 22 other authors

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Abstract:Welcome to the ninth edition of the AI Index report. As AI continues to advance rapidly, the question becomes whether the systems built around it can keep up. Governance frameworks, evaluation methods, education systems, and the data infrastructure needed to track AI's impact are struggling to match the pace of the technology itself. That gap between what AI can do and how prepared we are to manage it runs through every chapter of this year's report. New in this edition, the report tracks how AI is being tested more ambitiously across reasoning, safety, and real-world task execution, and why those measurements are increasingly difficult to rely on. It also features new estimates of generative AI's economic value alongside emerging evidence of its labor market effects, an analytical framework on AI sovereignty, and a science chapter developed in collaboration with Schmidt Sciences. For the first time, the report features standalone chapters on AI in science and AI in medicine, reflecting AI's growing impact across these two domains.

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Artificial Intelligence (cs.AI)

Cite as:<br>arXiv:2606.15708 [cs.AI]

(or<br>arXiv:2606.15708v1 [cs.AI] for this version)

https://doi.org/10.48550/arXiv.2606.15708

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Submission history<br>From: Loredana Fattorini [view email]<br>[v1]<br>Tue, 14 Apr 2026 02:22:23 UTC (37,792 KB)

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