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SUPREME AI AGI

Prediction · On the road to AGI

The next large survey of AI researchers will put the 50% date for AI outperforming humans at every task earlier than 2047.

Near termMedium confidenceOpen

Why we think so

Between two surveys a year apart, the estimate moved 13 years earlier. Since then, olympiad maths, long tasks and the ARC-AGI-3 generalisation test have all fallen faster than expected.

What would prove us wrong

A comparable survey giving 2047 or later.

Horizon
Near term. Within about 3 years of the date the prediction was made.
Confidence
Medium confidence
Status
Open. Not yet decided either way.
Made
21 October 2026
Research programs
Measuring progress to AGI

The evidence it rests on

Public results from teams around the world. Read the sources and judge for yourself.

  • · AI Impacts, University of Bonn and University of Oxford (arXiv, later JAIR)

    Survey of 2,778 AI researchers on when AI will beat humans at every task

    Researchers who publish at top AI venues gave a 50% chance that unaided machines outperform humans at every possible task by 2047, 13 years earlier than the same survey a year before.

    What it means for AGI: expert expectations have been moving earlier, fast.

    Source: arxiv.org(opens external site)

  • · ARC Prize Foundation (testing OpenAI's model)

    GPT-6 Astra scores 99.9% on ARC-AGI-3, with a caveat

    ARC Prize verified 62.7% with its standard harness and 99.9% with a harness that keeps the model's reasoning state between steps; in one setting it used fewer actions than the median person on 96% of levels. ARC Prize states it is not claiming this is AGI.

    What it means for AGI: the gap on learning new tasks closed within six months of the test's launch. The jump from 62.7% to 99.9% came from how the system keeps memory, not from a new model, which supports the view that AGI is a system, not one model. The run cost about $18,800, far more than a person would.

    Source: arcprize.org(opens external site)

  • · Stanford Institute for Human-Centered AI

    AI Index 2026: capabilities jump, but unevenly

    Agent success on Terminal-Bench rose from 20% to 77.3% in a year, and agents solved 93% of cybersecurity tasks, yet robots succeeded at only 12% of real household tasks. AI data-centre power capacity reached 29.6 GW, and four in five US students use AI for schoolwork.

    What it means for AGI: digital abilities are racing ahead while physical abilities and governance lag.

    Source: hai.stanford.edu(opens external site)

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