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Anthropic’s August 2026 surveys found that 39% of US adults and 91% of Anthropic staff expected AI to be able to make a Nobel-level discovery by 2030. That 52-percentage-point difference captures a sharp gap in expectations—not evidence that AI will make such a discovery. The report also found wider differences in views about AI’s pace of improvement, workplace adoption, time savings, and ability to automate people’s jobs.
What does the 39% versus 91% figure mean?
It is the share of respondents who expected AI to be able to make a Nobel-level discovery by 2030: 39% of surveyed US adults and 91% of surveyed Anthropic staff. Anthropic published the comparison in its October 16, 2026 report, The AI expectations gap.
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The figures measure expectations, not scientific capability. They do not show that AI has made, or will make, a Nobel-level discovery by the deadline. Nor are they a direct measure of respondents’ confidence that the outcome is certain: the headline result is the proportion who said they expected AI to be able to do it.
The 39% figure comes from the August US adult survey. In a separate September follow-up, 44% of US adults expected such a discovery by 2030. Anthropic’s report uses the August results for its main comparisons, so the two percentages should not be presented as if they came from the same survey wave.
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How were the two groups surveyed?
The US adult survey was fielded online by Morning Consult from August 11 to 23, 2026, and reached 10,980 adults. Anthropic says responses were weighted to be nationally representative. Its internal staff poll ran August 9 to 12 and received 1,334 responses from across the company; those responses were unweighted.
The comparison has important limits. The public sample consisted of opt-in online panelists, not a probability sample of every US adult. Anthropic cautions that the survey excludes people without internet access and that demographic weighting may not remove all differences between panelists and the population. The staff poll, meanwhile, represents employees of one AI company—not AI researchers or technology workers in general. Staff build and use frontier AI, while the other sample represents a broad adult public.
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The timeframes also differ slightly: US adults were asked questions about either 2027 or 2030, and the report presents 2030 results unless it says otherwise. Staff were asked about 2030. The results are useful as a snapshot of contrasting expectations, but the sample and question design mean they should not be treated as a perfectly matched experiment.
Where else did Anthropic staff and the public disagree?
The report describes the groups as broadly aligned on what AI can do today, but more divided over how fast it will improve, how widely it will be adopted, and how much time it will save. Its authors—Szymon Sacher, Tess Cotter, Charles I. Jones, Anton Korinek, and Peter McCrory—write: “US adults and Anthropic staff largely agree about what AI can do today. However, they disagree about how quickly it will improve, how widely it will be used, and how large the productivity gains measured by time saved will be.”
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- Scientific work in the near term: About 9 in 10 Anthropic staff and 38% of US adults expected AI to be able to design, conduct, and publish scientific studies by the next year.
- Time saved on suitable tasks: Among US adults who use AI at work, 26% said a suitable task takes a quarter of the time or less with AI. The equivalent share among Anthropic staff was 59%.
- Share of current work AI could do: Staff expected AI to be able to do 75% of their current work hours by 2030 on average. Employed US respondents gave an average of 28%. At the higher end, 5% of US workers expected AI to do at least 80% of their work.
These measures describe different things. Expectations about scientific capability are not the same as estimates of time saved on selected tasks, and neither directly establishes how much work will actually be automated. The gaps are better understood as several distinct differences in outlook than as a single score of which group is “more optimistic.”
What did respondents expect about jobs and economic growth?
Respondents who expected AI to do more of their own work also tended to expect higher unemployment. Anthropic says this relationship was similar in the staff and public groups. The report’s authors summarize the pattern: “Those who expect AI to do more of their own work in the years ahead expect higher unemployment as well.” This is an association between survey answers, not evidence that expectations themselves cause unemployment.
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The report also translates respondents’ answers into estimated GDP growth through an economic model. The median US adult’s answers implied 5.4% growth in 2030, while the median staff member’s answers implied 17.1%. These are model-implied outcomes based on survey responses—not observed growth, a standalone forecast, or a guarantee of future economic performance. The figures depend on the model and assumptions used to convert expectations into an economic estimate.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.How should you read the headline finding?
Keep three qualifications in view. First, 39% and 91% are respondents’ expectations for 2030, not proof of an AI capability. Second, the groups are different kinds of samples: a weighted opt-in adult panel and an unweighted poll of one company’s employees. Third, the report’s other results cover separate questions about scientific work, task-level time savings, automation of respondents’ own jobs, unemployment, and model-implied economic outcomes.
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Read together, the findings show that Anthropic staff surveyed in August 2026 anticipated a faster and broader advance in AI than the US adults surveyed did. They do not establish which expectations will prove correct.
Frequently Asked Questions
Did the report say AI will win a Nobel Prize by 2030?
No. The survey asked whether respondents expected AI to be able to make a Nobel-level discovery by 2030. That is not the same as predicting a Nobel Prize award, and the result does not establish that such a discovery will occur.
Why does one report give 39% and another figure give 44%?
The 39% result is from Anthropic’s August 2026 US adult survey; 44% is from a follow-up survey fielded in September. They are results from separate survey waves, not competing calculations of the same set of responses.
Can the GDP numbers be treated as economic forecasts?
No. The 5.4% and 17.1% figures are outputs from an economic model applied to the median respondents’ answers. They are not measured GDP growth or independent forecasts of what the US economy will achieve.
Does the survey show that AI will cause unemployment?
It reports that people who expected AI to handle more of their own work also tended to expect higher unemployment. A relationship between survey responses does not by itself show that AI will cause a particular employment outcome.

