Drawing parallels to the Industrial Revolution, Demis Hassabis warns that AI's societal transformation will be significantly more compressed and impactful. He predicts it will be '10 times bigger' and happen '10 times faster,' unfolding over a single decade rather than a century, demanding rapid adaptation from global institutions.

In the current AI landscape, knowledge and assumptions become obsolete within months, not years. This rapid pace of evolution creates significant stress, as investors and founders must constantly re-educate themselves to make informed decisions. Relying on past knowledge is a quick path to failure.

Many dot-com era predictions, like the demise of physical retail, were directionally correct. The primary forecasting error was "timeline compression"—assuming a multi-decade societal transformation would happen in just a few years. This serves as a cautionary tale for the current AI boom, where the "when" is as important as the "what."

To grasp AI's potential impact, imagine compressing 100 years of progress (1925-2025)—from atomic bombs to the internet and major social movements—into ten years. Human institutions, which don't speed up, would face enormous challenges, making high-stakes decisions on compressed, crisis-level timelines.

Dell notes that new technology waves are adopted 5-10 times faster than previous ones. This compression of time means leaders must be relentlessly open-minded and seriously consider all "wild ideas," as dismissing them has become increasingly risky.

An anecdote of a 600-person company CEO feeling 'terrified' highlights the immense pressure on established businesses. The strategic landscape shifts in weeks, rendering plans obsolete before they can be implemented. This pace creates a risk of strategic paralysis or constant, frantic pivoting for non-native AI companies.

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.

There is a brief grace period, estimated at about one year, for workers to learn and integrate AI into their roles. After this window, companies will actively seek to replace employees who haven't become significantly more efficient with AI tools, as the productivity gap will be too large to ignore.

Unlike gradual agricultural or industrial shifts, AI is displacing blue and white-collar jobs globally and simultaneously. This rapid, compressed timeframe leaves little room for adaptation, making societal unrest and violence highly probable without proactive planning.