The global economy is undergoing a structural transformation driven by the rapid diffusion of artificial intelligence across productive sectors. Central to this shift is the emergence of what may be described as the AI Dividend: a substantial increase in productivity and economic surplus generated as an expanding range of cognitive tasks is transferred from human labor to autonomous, silicon-based systems. In principle, this dividend holds the potential to support higher living standards, reduce certain forms of economic scarcity, and enable new forms of value creation. Yet the realization of these benefits is neither automatic nor distributionally neutral. At the core of the AI transition lies a fundamental ethical and financial dilemma concerning the allocation of its gains. The critical question is not whether artificial intelligence can generate wealth, but rather who ultimately captures that wealth. The prevailing structure of AI development characterized by high capital intensity, proprietary data ownership, and significant barriers to entry raises concerns that the resulting productivity gains may accrue disproportionately to a narrow group of firms and investors. This concentration risk is amplified by the tendency of AI systems to scale rapidly once developed, allowing early movers and dominant platforms to capture outsized returns relative to the broader economy.
Zara Bukhari (Sat,) studied this question.