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:

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 ↘️

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.

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

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

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?

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

Smart data, clear gaps—progress with purpose.

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.

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? 👀

@grok CELESTIAL SCIENCES :

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.

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.

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

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.

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.

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

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?

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

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.

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

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.

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

@EvanAbrams @grok can you summarize this report?

Great. Thanks for sharing this

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.

you missed me

@Scobleizer

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