Brad Smith Says A.I. Must Learn from History to Avoid Industrial Revolution Mistakes
The rise of A.I. is frequently described as a new industrial revolution, following the sweeping economic transformations brought by mechanized manufacturing, mass production and the digital age. Because of this, A.I. leaders should study history carefully to avoid repeating past mistakes, Microsoft president Brad Smith said during a talk at Web Summit Vancouver yesterday (May 28).
Smith emphasized the importance of equitable access to emerging technologies. He pointed to the uneven global diffusion of electricity following Thomas Edison’s invention of the light bulb—a foundational moment in the Second Industrial Revolution. “How can it be that we moved from electricity to computers and now A.I., and we haven’t yet even finished diffusing electricity itself?” he asked, noting that hundreds of millions of people still lack access to electricity nearly 150 years later.
Calling this disparity potentially the “greatest tragedy” in the history of technology, Smith urged the A.I. industry to ensure its benefits are distributed more broadly. “We can do better, not just to create better technology, but to bring the benefits of that technology to everyone around the world,” he said.
Widespread A.I. adoption, he argued, depends on significant investment in the infrastructure that underpins innovation—a domain where Microsoft is making a major play. The company plans to invest $80 billion this year in A.I. and data center infrastructure across 40 countries. This infrastructure, alongside platforms and applications, forms what Smith described as the “tech stack” of the A.I. economy.
Past industrial revolutions also built out such tech stacks. The spread of electricity, for example, spurred demand for fuels, turbines, electrical grids, transformers, wiring and appliances—industries that in turn created new categories of employment, said Smith.
He also stressed the critical role of education in unlocking job growth. During the First Industrial Revolution, the U.K. pulled ahead by training workers to use iron and new machinery. The U.S. later surged ahead by producing engineers skilled in electricity and machine tools, and reaped further gains by embracing computer science education during the Information Age. These examples, said Smith, underscore why teaching A.I. skills “will need to become one of the great causes of our industry.”
Ultimately, Smith argued, investment in education—not optimism alone—is what will determine whether A.I. augments human labor or replaces it. “Hope by itself is not a strategy,” he said. “I think history offers some important lessons.”