The forecasts that put automation of AI research in 2027 are closer to one voice than several: they trace to a single outside estimate of acceleration at Anthropic whose main evidence was redacted, and against the labs' own accounts and independent tests the chance that either lab can automate all r

In November 2026 several prominent forecasts moved toward 2027 at once: a forecasting group shifted its dates for a superhuman AI researcher from 2028 or later to 2027, an Anthropic co-founder said he now thinks 2027 more likely than 2028 for a model able to improve itself, and other forecasters shortened their timelines. Read together these look like converging independent judgments.

The record shows they are not independent. The assessment of whether Anthropic or OpenAI will have AI able to do all frontier research work except agenda-setting by the end of 2027¹ traces the shift to one input: an outside evaluator's estimate that Anthropic is improving its models at about twice its earlier rate, most of it attributed to AI. Most of the evidence behind that estimate was redacted by the lab, the forecasters who moved furthest call their analysis preliminary, and the insider forecast comes from a co-founder of the lab that was assessed. The argument from forecasts of stronger milestones² therefore stands or falls with the reliability of what is in effect a single line of evidence.

The evidence on the other side comes from separate hands with different incentives and agrees on the same weakness. OpenAI's own September 2026 account claims an automated research intern for well-defined tasks of a few days, reports that agents need significant human steering as tasks lengthen, and sets March 2028 as its goal for an automated researcher. Anthropic reports that no measured part of its research is fully autonomous. In the one direct open-ended test, the original authors rejected every AI-written paper. The argument from the present gap in open-ended research³ is the main reason the forecast is judged more likely false than true.

The result is not a verdict that progress is stalling. The same record judges a stall in progress toward automating AI research in the next few years⁴ doubtful, at about one in five, and puts the date of the superhuman-researcher milestone⁵ at a median near 2030 with about one chance in ten by mid-2027. The stricter forecast that a frontier model will autonomously train its successor by the end of 2027⁶ stands at about one in eight. The assessment names what would move the figure during 2027: expert-accepted AI-written papers in a repeat of the open-ended test, either lab reporting multi-week projects completed by AI within a human-set direction, OpenAI moving its 2028 goal earlier, or an outside evaluator finding autonomous contributions dominant at either lab.