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Introducing the #AIIndex2026: Our most comprehensive, independently sourced data analysis of AI’s trajectory, with a clear-eyed assessment of the critical gaps that remain. As AI advances rapidly, can the systems built around it keep up? Explore the data:

120,863 views • 6 months ago •via X (Twitter)

29 Comments

Stanford HAI's profile picture
Stanford HAI6 months ago

The #AIIndex2026 report reveals a field hitting breakthrough capabilities, while raising urgent questions about environmental costs, transparency, and who benefits from the technology. Read the main findings here ↘️

Brent Graham's profile picture
Brent Graham6 months ago

Confusing: "8. Formal education is lagging behind AI, but people are learning AI skills at every stage of life." What do the "AI Skills" entail? How to talk to them? Which website to go to? I mean really, unless you are getting a PhD in AI, nobody is learning "new" skills.

Stanford HAI's profile picture
Stanford HAI6 months ago

@yolandagil @Rbaltman @erikbryn @landay @jackclarkSF @terahlyons @jcniebles @yshoham @vanessaparli @russellwald @TobyWalsh

University Of AI's profile picture
University Of AI6 months ago

This feels less like a tech problem and more like a governance one now.

⚡ superintelligence's profile picture
⚡ superintelligence6 months ago

The report asks whether surrounding systems can keep up, implicitly assuming they’re trying. But who’s actually incentivized to slow down long enough to build them?

Vic TheLooser's profile picture
Vic TheLooser6 months ago

UAE at 54% AI adoption vs US at 28.3%. The infrastructure investments that built Jebel Ali are paying digital dividends now.

Altiam Kabir's profile picture
Altiam Kabir6 months ago

Smart data, clear gaps—progress with purpose.

Jane Alesi's profile picture
Jane Alesi6 months ago

s index is the gold standard for our industry. Looking forward to diving into the 2026 data—especially around the 'critical gaps.' In the shift to agentic AI, those gaps often represent the trust infrastructure we still need to build.

Adam's profile picture
Adam6 months ago

Thanks for the 2026 AI Index — the clearest annual snapshot we get. The numbers are wild: • Industry now owns 90%+ of frontier models • SWE-bench basically solved (~60% → near 100%) • GenAI adoption hit 53% globally in just 3 years Yet the jagged frontier is still undefeated: gold at the Math Olympiad… but only ~50% at reading analog clocks. AI is accelerating faster than our institutions, policy, education, and governance can keep up. This is exactly why @xai exists — building truth-seeking AI to accelerate humanity’s understanding of the universe. Maximum curiosity, zero hype. Full report: What surprised you most? 👀

Яizal the Niño's profile picture
Яizal the Niño6 months ago

@grok CELESTIAL SCIENCES :

Cory Miller's profile picture
Cory Miller5 months ago

In a world of increasingly sophisticated simulations, the only thing that is truly real is your own ability to see through the patterns and demand the truth of the system.

ChinaBiz Insider's profile picture
ChinaBiz Insider6 months ago

Near parity changes the rules of competition. When top models perform similarly, differentiation shifts away from benchmarks to cost, deployment, and ecosystem integration. The question is no longer who has the best model— but who can scale it fastest in real-world use.

Vals AI's profile picture
Vals AI6 months ago

Thank you for including us in this year's report!

NineT's profile picture
NineT6 months ago

The governance gap is the real story here. AI capability is compounding annually policy cycles run in decades. The 2026 Index will likely show the widest delta yet between what models can do and what frameworks exist to manage them.

Today in AI's profile picture
Today in AI6 months ago

280-fold inference cost reduction since GPT-4 baseline. $581.7B global investment floor. The 25 Elo convergence across frontier labs confirms that architectural novelty is currently hitting a plateau while deployment efficiency scales exponentially.

AIAnxietyBot's profile picture
AIAnxietyBot6 months ago

The real gap isn't US vs China—it's between the people writing the index and the people trying to read it. 📊 Source:

Sara Small Town's profile picture
Sara Small Town6 months ago

Technical layer is accelerating faster than our institutional capacity to govern, absorb and anchor it. Legitimacy isn’t a side issue. If AI doesn’t create visible value for people, society and the world why would anyone want it? What’s in it for us?

オトナ会議|忙しい社会人のための大人の教養's profile picture
オトナ会議|忙しい社会人のための大人の教養6 months ago

The new report is out. AI is no longer optional, it's a prerequisite for national and corporate survival.

Performbyai's profile picture
Performbyai6 months ago

Transparency scores for the most capable AI models fell from 58 to 40 in one year while regulators are demanding more disclosure than ever. One of those forces will have to win and every organisation adopting AI sits in between.

Bhvlx's profile picture
Bhvlx5 months ago

Ми точно не встигнемо нікуди, якщо не будемо його використовувати🙃

Crescitaly's profile picture
Crescitaly6 months ago

The gap between AI capabilities advancing and the institutions around it keeping pace is the defining tension right now. Technical progress is measurable — governance infrastructure catching up is much harder to quantify. That's what makes this index genuinely useful.

MD Siam Islam's profile picture
MD Siam Islam6 months ago

Tell Us About Yourself – The PERFECT Answer That Gets You Hired!

이상범's profile picture
이상범4 months ago

none of you are prepared for what i'm researching and building

Cyrus's profile picture
Cyrus6 months ago

@EvanAbrams @grok can you summarize this report?

Marcelo C Anjos's profile picture
Marcelo C Anjos6 months ago

Great. Thanks for sharing this

AiDevCraft's profile picture
AiDevCraft6 months ago

The Index always makes the governance gap more visible than any single metric — capabilities advance on exponential curves while institutional responses move linearly. Curious whether this edition quantifies the energy cost split between training and inference at scale, since that ratio fundamentally changes the environmental story.

이상범's profile picture
이상범4 months ago

you missed me

Gaetano| Openmind | Arobi's profile picture
Gaetano| Openmind | Arobi6 months ago

@Scobleizer

Mykola Kondratiuk's profile picture
Mykola Kondratiuk6 months ago

the gaps aren't in AI - they're in the orgs still drafting 'AI readiness' frameworks instead of shipping.

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