Tax Systems and Artificial Intelligence in Latin America and the Caribbean

preparation

The general objective is to analyze how AI will affect tax systems in LAC — their revenue capacity, efficiency, relative burdens, and redistributive impact — and identify policy responses. The TC proposes five lines of work. First, diagnosing how current tax structures interact with AI adoption — whether existing incentives and payroll tax designs inadvertently discourage or encourage technology adoption — and identifying reforms that improve the system under most scenarios without worsening it under any. Second, analyzing responses the region may need to maintain collection, improve equity, and enhance efficiency under different scenarios — varying adoption speed, automation-augmentation balance, and international transmission — distinguishing adjustments robust across outcomes from those warranted only under specific conditions. Third, defining how institutional arrangements must be modified as AI advances — including whether adjustment capacities could be delegated to tax authorities within legislatively defined parameters, enabling faster response without sacrificing accountability. Fourth, assessing AI's potential to strengthen tax administration — risk assessment, enforcement, and taxpayer services — while managing risks to tax morale, fairness, and legal frameworks. Fifth, identifying tax policy measures that steer AI adoption toward complementarity with labor, supporting a less disruptive transition for workers.