The AI expectations gap
A survey of US adults and Anthropic staff in August 2026 shows that while both groups agree on current AI capabilities, staff expect faster progress, wider adoption, and greater productivity gains. Staff predict AI will automate 75% of their own work by 2030, compared with 28% for the general workforce. The public cites customer preference, privacy, and reliability as main adoption barriers.
The Core Development
Szymon Sacher, Tess Cotter, Charles I. Jones, Anton Korinek, Peter McCrory
How will AI reshape the economy in the years ahead? AI capabilities are advancing rapidly, and the possibility that future AI models may be able to build their own successors (recursive self-improvement) could further accelerate the rate of progress. How quickly this might materialize and to what extent is unclear. Forecasts vary widely and are fiercely debated.
What is the core source of disagreement about AI's future impact on the economy? Is it principally due to differences in beliefs about how quickly AI capabilities will improve? Or does it reflect disagreement about how quickly and in what form those capabilities translate to real-world adoption? Which views on the future path of AI are consistent with rapid economic growth?
Strategic Perspective & Ecosystem Impact
This note presents new survey evidence on these questions. In August 2026, we surveyed two groups: a sample of US adults that was nationally representative and Anthropic staff. 1 The questions covered, among other things, AI’s capabilities, how widely it will be used, how much time it saves, how autonomous it will be, and how difficult it will be for a displaced worker to find a job in a different occupation. 2 Anthropic staff build and use frontier AI every day. The second survey therefore shows how people closest to the technology anticipate its future, both in capabilities and in broader economic impact.
We report the following main findings. First, the two groups largely agree about what AI can do today but disagree about the pace of future progress. Anthropic staff expect capabilities to advance faster, AI to be used more widely and with less human involvement, and the time it saves on a task to be much larger. For example, 91% of staff expect AI to be able to make a Nobel-level discovery by 2030, compared to 39% of US adults.
Second, there are sharp differences concerning people's own jobs. On average, staff members expect AI to be able to do 75% of their current work by 2030, compared to 28% for US workers overall.
Why it matters
The divergence in expectations highlights a potential gap between AI developers and the broader workforce, affecting investment, policy, and workforce readiness.