The article argues that AI’s first automation shock is likely to hit richer economies harder because their labor markets contain more clerical, professional and digital work. Developing economies face lower immediate exposure, but that is not pure protection. It often reflects weaker electricity, connectivity, institutions and managerial capacity, which limit their ability to turn AI adoption into productivity gains.

Using the proposed Google data center hub in Visakhapatnam as a test case, the piece warns that hosting compute is not the same as building technological sovereignty. Data centers can bring infrastructure, jobs and cloud access, but they also consume scarce power, water and public concessions. The article argues developing economies should prioritize adoption and adaptation before frontier imitation, approving large AI infrastructure only when it leaves behind durable capability, local value capture and broad economic benefit.