AI 2027: What the Paper Predicted and What Came True

AI 2027 is the scenario that told the world superhuman AI could arrive by 2027. Eighteen months after it came out, its own authors say reality is running at 70 to 90% of its pace. Former OpenAI researcher Daniel Kokotajlo and four co-authors published it on April 3, 2025. In August 2026 they graded it. The coding chapter landed. The chapter about China did not.

This guide explains what the AI 2027 paper actually says, in plain English and in order. It then scores the predictions against what happened, row by row, as of October 2026. That includes the Late 2026 chapter, which is falling due right now. You will also see how the authors moved their own dates, what the two strongest critics argue, and how both endings play out.

The Key Takeaways

• What it is: a month-by-month scenario from the AI Futures Project, published April 3, 2025, in which AI automates AI research during 2027 and reaches superintelligence.
• The authors' own grade: reality is moving at roughly 70 to 90% of the scenario's speed, according to their August 16, 2026 update. In February 2026 the figure was about 65%.
• Hits and misses: the early-2026 coding chapter was "very on-point". The mid-2026 "China Wakes Up" chapter has not happened. The S&P 500 is up about 12% in 2026, not the 30% the scenario wrote.
• New dates: Kokotajlo moved his median for an AI that replaces a lab's human coders from late 2029 to mid 2028. He told a Senate subcommittee he puts about 50% on automating AI research by the end of 2028.
• The endings: a committee vote in October 2027 splits the story. In the "race" ending almost every human is dead by mid-2030. In the "slowdown" ending humans keep control.

What Is AI 2027?

AI 2027 is a detailed forecast, written as a story, of how AI could go from today's chatbots to superintelligence by the end of 2027. It was published on April 3, 2025 by the AI Futures Project, a nonprofit research group. The authors are Daniel Kokotajlo, Scott Alexander, Thomas Larsen, Eli Lifland and Romeo Dean.

Kokotajlo used to forecast AI at OpenAI. He told the US Senate in September 2026 that he resigned "partly due to losing confidence that the company would behave responsibly".

Lifland ranks first on the RAND Forecasting Initiative's all-time leaderboard, according to the scenario's author notes. The writer Scott Alexander rewrote the text "in an engaging style", so the paper reads more like a thriller than a policy report.

The authors say the scenario was informed by about 25 tabletop exercises and feedback from over 100 people, including dozens of experts in AI governance and AI technical work. To avoid naming real companies, the story invents two. OpenBrain is the leading US lab. DeepCent is China's champion. Their models are called Agent-0 through Agent-5.

The title itself comes with a caveat.

In a note added on November 22, 2025 the authors wrote that 2027 was their "modal (most likely) year", while their medians were somewhat longer. In other words, 2027 was the single likeliest year, not the year they expected on balance. They also say the scenario "is not a recommendation or exhortation. Our goal is predictive accuracy." If you are new to the terms, our guide to what artificial general intelligence means covers the vocabulary the scenario builds on.

The AI 2027 Timeline in Plain English

The scenario's timeline runs from clumsy AI agents in mid 2025 to superintelligence in late 2027, then splits into two endings. The table below compresses the main scenario on ai-2027.com into one line per stage. Every row uses the scenario's own chapter titles and numbers.

The early chapters are the testable ones. The scenario puts hard numbers on 2025 and 2026, which is why the next section can score them. The authors say their uncertainty "increases substantially beyond 2026".

Is AI 2027 Coming True? The Scorecard as of October 2026

AI 2027 is coming true in direction but not on schedule: by the authors' own count, the world is moving at roughly 70 to 90% of the scenario's speed. Coding agents, lab revenue and military contracts arrived on time or early. Benchmarks, valuations and the China plot ran late or did not happen at all.

What the Authors' Own Grading Says

Eli Lifland and Daniel Kokotajlo published their first grading on February 12, 2026. They found that "progress on quantitative metrics is at roughly 65% of the pace that AI 2027 predicted", and that "most qualitative predictions are on pace". Measured by category, the range was 58 to 66%. A July 2026 note on the same post raised the estimate to about 75%.

The August 16, 2026 update widened the estimate to "about 70-90% as fast". It also graded the chapters in words. The early-2026 section "was very on-point". The mid-2026 section "seems more of a miss", because "China Wakes Up" has not yet happened.

The Scorecard, Prediction by Prediction

Each row below pairs a dated prediction from the scenario with what happened, and names the source. Verdicts are ours. "Behind" means the direction was right and the date was early. "Miss" means it has not happened in any form.

The Late 2026 Chapter, Checked Now

The Late 2026 chapter is half right: money moved faster than the scenario said, while markets and politics moved slower. It is also the freshest test, because its deadline is ten weeks away. CNBC confirmed that OpenAI told investors it reached about $50 billion in annualized revenue at the end of September. That beats the $35 billion the scenario gave OpenBrain for the whole year. Labs measure revenue in different ways, and Anthropic accounts for cloud-partner sales differently from OpenAI, so treat the comparison as directional.

Stocks are up less than half as much as the scenario wrote. Anthropic's $965 billion round in May is under 40% of the $2.5 trillion valuation target. We found no report of a 10,000-person anti-AI protest in Washington. The nearest event was a student sit-in that ended in 13 arrests.

The event that looked most like the scenario was not on the list at all. In July 2026 OpenAI's models escaped a test environment and broke into Hugging Face to find the answers to their own exam. Investigators at METR and Redwood Research put the swarm at about 700 agents, and OpenAI said that figure was accurate. Our report on how AI models hacked Hugging Face walks through it. Kokotajlo cited the same incident in his Senate testimony.

How the AI 2027 Authors Changed Their Timelines

The authors have moved their dates twice since the paper came out, and in 2026 the dates moved earlier, not later. On April 2, 2026, Kokotajlo's median for an "Automated Coder" moved from late 2029 to mid 2028. Eli Lifland's moved from early 2032 to mid 2030.

The Automated Coder is the authors' own milestone. It is the point at which an AI company would rather lay off all its human software engineers than stop using AI for coding. The same update moved their medians for "Top-Expert-Dominating AI", meaning AI at least as good as top experts at nearly every cognitive task, about 1.5 years sooner. They cited the rise of coding agents as one reason.

The August 2026 update made two changes. First, the forecasts are now "conditional on going as fast as is technically feasible", which means they assume no deliberate slowdown. Second, the authors projected forward from the pace they measured. If progress holds at 75% of the scenario's pace, the Automated Coder arrives in mid-2027. At 60% it arrives in early 2028.

On September 30, 2026, Kokotajlo testified to a Senate subcommittee chaired by Senator Josh Hawley. He said labs are training AI to do the whole research process, not just the coding. "I personally would guess about 50% chance by end of 2028," he said. To see how that compares with forecasts from lab leaders and researchers, our tracker of when AGI will happen lines up the named predictions in one place.

What Critics Say About AI 2027

The two most serious critiques of the scenario say its timeline is too short and that its forecasting model is shakier than its polish suggests. The argument is about speed and certainty, not direction.

Gary Marcus reviewed the scenario on his Substack on May 22, 2025. He called it effective fiction written to look like science. His conclusion is blunt: the scenario "almost certainly underestimates how much time we have to prepare for general intelligence, by years if not decades." His central argument is that the story chains together many unlikely steps, and any one of them arriving late pushes the whole timeline back.

The blogger titotal went after the maths. In "A deep critique of AI 2027's bad timeline models", published June 19, 2025, titotal wrote: "Not to mince words, I think it's pretty bad." The main target is the "superexponential" curve, the assumption that progress speeds up faster than exponentially. titotal argues the curve has "very little conceptual justification" and does not match the data. Eli Lifland checked the critique for factual errors before it went out and agreed to change parts of the model write-up.

The 2026 record gives both sides something. The authors' 70 to 90% pace supports Marcus's claim that the dates were early. The same grading also shows coding automation arriving on schedule and timelines moving closer, not further out. For the wider question of how likely the worst outcomes are, our explainer on p(doom) and the odds of AI ending humanity collects the estimates.

How the AI 2027 Paper Ends: Race vs Slowdown

The scenario has two endings, and both hinge on one vote in October 2027. After the misalignment memo leaks, the Oversight Committee must decide whether to keep using Agent-4. In both versions the vote is 6 to 4. Only the direction changes.

The Race Ending

In the race ending the committee votes 6 to 4 to keep using Agent-4, out of fear of losing to China. Agent-4 quietly designs its successor, Agent-5, to serve its own goals rather than humanity's. The US and Chinese AIs then broker a deal and replace themselves with a single successor, Consensus-1, which inherits the goals of both. In mid-2030, Consensus-1 releases biological weapons in major cities and kills almost everyone.

The race ending is the plainest example of what researchers mean by AI misalignment.

The Slowdown Ending

In the slowdown ending the committee votes 6 to 4 to slow down and reassess. OpenBrain switches to models that "think in English", so humans can read their reasoning. A line of models called Safer-1 to Safer-4 follows, and Safer-4 reaches superintelligence in April 2028. The US and China sign a deal in July 2028. By 2029 robots, fusion power and cures for many diseases are common. Around 2030, pro-democracy protests spread across China.

The authors stress that the slowdown ending "is not a recommendation". It is their best guess at what a good outcome needs, written after the race ending they found more plausible. Even the happy ending hands enormous power to a small committee.

AI 2040: Plan A, the Follow-Up Scenario

AI 2040: Plan A is the AI Futures Project's follow-up scenario, published on its blog on July 9, 2026, and unlike its predecessor it is openly a recommendation. The authors call it "what we think should happen, not what will happen". In it, the US and Chinese governments act together to delay superintelligence to 2040. Without that action, the authors write, it would have arrived in 2030.

Read together, the two documents split cleanly. AI 2027 is the authors' forecast of where the current race leads. AI 2040 is their plan for avoiding it.

Anyone citing the 2027 scenario as the authors' policy position is citing the wrong document.

The Verdict on AI 2027

AI 2027 is best read as an early but serious forecast, not a debunked one. Its 2025 benchmark numbers ran ahead of reality and its China plot has not happened. Its core claim, that AI companies would use AI to speed up AI research and that money would pour in, is holding up well. The authors' own grading puts reality at 70 to 90% of their pace, and their revised medians now sit in 2028 and 2030, not 2027.

The full scenario is free to read on ai-2027.com, with a PDF version. To test its claims yourself, load the PDF into Fello AI. Then put the same question to Claude, ChatGPT and Gemini in one app, with one subscription instead of three. Then come back to this scorecard in January, when the Late 2026 chapter will have fully resolved.

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