Anthropic staff expect AI to do 75% of their work by 2030 and GDP growth to hit 17.1%; one said 28%, and the lowest was 6%. Site visitors guessed 12.5%, US adults 5.4%, and the FOMC 2%.

Leaders from OpenAI, Google, and Anthropic are openly and consistently predicting profound disruption to the labor market from AI. This view, once an outlier, has become the conventional wisdom in the tech C-suite, signaling a major shift in expectations for the near-term future of work.

Julian Schrittwieser, a key researcher from Anthropic and formerly Google DeepMind, forecasts that extrapolating current AI progress suggests models will achieve full-day autonomy and match human experts across many industries by mid-2026. This timeline is much shorter than many anticipate.

Anthropic's Sholto Douglas stated that AI models will possess the technical capability to automate 95% of computer-facing jobs by 2028. However, he predicts actual mass job displacement will lag until the 2030s due to practical barriers like compute shortages, policy hurdles, and diffusion complexity.

There's an 'eye-watering' gap between how AI experts and the public view AI's benefits. For example, 74% of experts believe AI will boost productivity, compared to only 17% of the public. This massive divergence in perception highlights a major communication and trust challenge for the industry.

According to research from Anthropic, the most likely future scenario involves AI agents creating massive productivity multipliers. This will enable small, agile teams to compete with large enterprises by doing the work of organizations 100x to 1000x their size, revolutionizing knowledge work.

People deeply involved in AI perceive its current capabilities as world-changing, while the general public, using free or basic tools, remains largely unaware of the imminent, profound disruption to knowledge work.

While a 2027 superintelligence timeline was once considered aggressive, conversations with current employees at OpenAI and Anthropic reveal internal sentiment has shifted. They now believe this accelerated timeline is plausible, urging forecasters to shorten their own updated, more conservative estimates.

Mainstream economists forecast AI will add ~0.8 percentage points to annual labor productivity. However, Anthropic's internal data, based on observed task-level time savings, suggests a potential boost of 1.8 percentage points. This indicates a significant gap between micro-level efficiencies and macro-level forecasts.