Scenarios for our Economic Future

Source: Anthropic · 2026

In scenarios ranging from business as usual to an economy where AI increases growth to about twice the normal rate, unemployment stays within the historical range and wages remain flat or rise depending on the industry. But in scenarios where growth is faster than anything in economic history, there are adverse impacts on wages and job prospects for knowledge workers. In those scenarios, society is far wealthier, so the challenge is making sure that the gains are broadly shared.

In the modest scenario, AI has roughly the same kind of impact as the internet did. It drives real economic gains, but they’re within the historical norm for new technologies, and they arrive gradually.

In the substantial scenario, AI is capable of doing half of all knowledge work by 2030, the majority of it autonomously, but it’s not adopted for all of that work: most knowledge work tasks are still done without AI. The economy grows at twice its normal rate. Wages for knowledge workers don’t rise, but other workers see gains.

In the extreme scenario, AI is more productive than humans at the vast majority of knowledge-work tasks. It does nearly all of them autonomously, and it creates essentially no new knowledge tasks for people. This scenario would likely require recursively self-improving AI, adopted quickly for knowledge work.

As AI diffuses, annual GDP growth rates reach 15% a year, leading the economy to double in size every 4.5 years. As a society, we’re far richer than we’ve ever been, but many fewer workers have jobs in knowledge work, and unemployment has risen beyond typical recessionary levels.

The typical respondent’s answers imply outcomes close to the “substantial change” scenario: GDP is 10% higher by 2030 than it would be without AI, and the overall unemployment rate has risen to around 5%. Around 10% of respondents have views in line with the extreme scenario.

This model isn’t a complete map of reality, but it shows us some interesting findings. The country’s GDP will grow, but a larger share of that prosperity might go to the resources and technology used to create more wealth (capital) compared to workers, even if society as a whole is much wealthier.

And in most scenarios, job reallocation and unemployment both stay within ranges history has seen before, with one exception. In the extreme scenario, if we see recursive self-improvement and rapid adoption, unemployment could spike to historic levels.

Switching to a new occupation is difficult for a few reasons: workers may not want to change occupations. They may need to learn new skills. And even when they do, it’s not easy to get a new job. In the extreme scenario, as large swathes of knowledge work are automated more quickly, affected workers may be unemployed for a prolonged period.

We find that the labor share falls noticeably in the substantial and extreme scenarios, and the capital share rises. Average wages rise—non-knowledge workers are paid much more—but wages for knowledge workers stagnate or decline alongside worsening unemployment.

In the extreme scenario, the gains from a rapidly expanding economy are unevenly distributed. Most knowledge workers face either lower wages or unemployment, and workers overall get a smaller fraction of the larger pie. Total labor income is barely changed by 2030.

Ultimately, what the economy looks like in 2030 depends on many factors, like what AI can do, and how companies and workers choose to adopt it.