Distribution of benefits describes how gains from a technology-such as higher productivity, lower costs, or time saved-are allocated among workers, employers, and society. In AI-driven automation, efficiency alone does not determine whether those gains become higher profits, better pay, shorter working hours, increased output, or public benefits.
This matters in cyber security and technology governance because automated systems can reshape work and economic power without deciding who benefits. In practice, employers may use AI to reduce labor costs or expand output, while workers may gain through wages or reduced hours if workplace policies, bargaining, and institutions support that outcome. Evaluating an automation claim therefore requires distinguishing technical capability from realized outcomes and examining who controls and receives the resulting value.