Comprehensive Mapping of U.S. Undergraduate AI Programs Reveals Rapid Growth and Curriculum Variability
Researchers have created a comprehensive database tracking over 350 undergraduate AI programs across more than 560 U.S. universities, representing 86% of all undergraduate computer science graduates. The study reveals significant variability in AI major and minor requirements, with notable gaps in ethics education coverage. This snapshot provides the first systematic overview of AI education infrastructure during a period of rapid program expansion.
A new report from researchers presents the most comprehensive survey to date of undergraduate AI programs in the United States as of Spring 2026. The team developed an automated tool (available at cicmap.ai) that detects and tracks AI majors, minors, concentrations, and certificates across 4-year universities, identifying over 350 programs at institutions representing 86% of all U.S. undergraduate computer science graduates. Analysis of 66 AI majors and 87 AI minors reveals substantial variation in program structure and requirements. Key findings include that while not all AI majors require a dedicated AI course, those that don't typically require Machine Learning instead. Additionally, ethics in AI courses are required by more than a third of AI majors but by less than a quarter of AI minors, suggesting inconsistent attention to ethical considerations across programs.
What different sources said
- arXiv cs.AICenter
Mapping AI Programs in the U.S: A Status Report from Early 2026 and an Analysis of AI Majors and Minors
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