Even with superhuman AI, Dario Amodei argues the economic revolution won't be instant. The real-world bottleneck is "economic diffusion": the messy, human process of enterprise adoption, including legal reviews, security compliance, and change management, which creates a fast but not infinite adoption curve.

Even if AI progress stopped today, it would take 10-20 years for the economy to fully absorb and implement current capabilities. This growing gap between what's technologically possible and what's adopted in the market creates a massive, long-term opportunity for innovators.

A simplistic view of AI replacing tasks is misleading. A more robust model treats the outcome as a race between three competing forces: the speed of AI diffusion versus labor rebalancing, task destruction versus new task creation, and lost labor income versus indirect wealth effects from capital gains.

The idea that companies will fire everyone after buying ChatGPT is naive. Enterprise software sales cycles are 18+ months long, and integrating new tech into core systems takes years. This inherent inertia means AI's impact on jobs will be a gradual evolution, not an overnight revolution.

Concerns about immediate AI-driven job losses are premature. True labor displacement requires a lengthy phase-in period for broad enterprise adoption, building new application layers, and integrating AI into existing workflows and processes, which takes significant time.

The immense challenge of deploying AI within large enterprises, acknowledged by labs like OpenAI and Anthropic, is slowing widespread impact. This extended timeline provides a crucial adaptation period for businesses and workers to reskill and redesign roles, tempering fears of a sudden job apocalypse.

Past technological shifts occurred over decades, allowing labor markets to gradually adjust. AI's disruption is happening over years, a speed that historical models can't account for. This compressed timeline means new jobs and retraining won't happen fast enough, demanding immediate policy interventions like expanded capital ownership.

Despite fears of rapid job displacement, the slow pace of technology adoption in large corporations provides a crucial window to develop solutions. The fact that many firms are still migrating to the cloud indicates AI integration will take years, not months.

Just as electricity's impact was muted until factory floors were redesigned, AI's productivity gains will be modest if we only use it to replace old tools (e.g., as a better Google). Significant economic impact will only occur when companies fundamentally restructure their operations and workflows to leverage AI's unique capabilities.