The Economics of AI

The University of Virginia examines AI through economic models of production and technological change. Intelligence and information provide an opening framework before the course turns to growth scenarios and labor-market effects. It is an advanced comparison for learners who want to assess the assumptions behind a forecast rather than accept a prediction about automation as an inevitable outcome.

What you will learn

• Connect AI with models of production and technological change.
• Compare economic-growth scenarios and their assumptions.
• Analyze proposed effects on labor markets.

Who this suits

The provider identifies advanced study. Review the expected economics and modeling background before enrolling, particularly if formal production and growth models are unfamiliar.

Before you enroll

Scenario analysis describes consequences under assumptions. It does not establish a certain forecast for wages, employment or economic growth. Separate model structure, empirical evidence and unresolved uncertainty when comparing conclusions.

Coursera offers paid enrollment or subscription access. Check the enrollment screen for included assessments, certificate terms, trials and any financial-aid options. Access conditions can change; review the current offer before paying.

Put it into practice

Choose one model-based claim about AI and employment. State its main assumptions, change one of them and explain how the conclusion may differ, identifying the evidence needed to assess the original claim.

Source and review

This overview is based on the provider's published information, checked on 14 October 2026. It is an editorial assessment, not a claim that we completed the resource. Time filters are approximate study ranges; projects and exercises can take longer.

View the curriculum and current access options at Coursera.

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