Artificial Intelligence, Productivity, and Job Quality

Abstract

This evidence review examines artificial intelligence, productivity, and job quality. The organizing question is which task and organizational changes generate productivity while preserving autonomy, learning, fairness, and worker well-being. Ten related scholarly sources are synthesized through a decision-centered framework spanning problem definition, mechanism, measurement, evaluation, implementation, and governance. The review does not invent experiments, pooled estimates, or unreported quantitative results. It instead evaluates the strength and transferability of the available evidence, with particular attention to generalizing short-term task gains to firm productivity or social welfare. The resulting framework links technical or empirical performance to explicit use conditions and identifies tests that should precede wider adoption in workplace technology strategy and labour policy.