Universities in the U.S. are rapidly rolling out undergraduate majors, minors, and specializations in artificial intelligence to meet the growing demand for AI expertise.
What’s new: There are at least 1,000 AI programs across nearly 584 U.S. colleges and universities, including 78 majors and 103 minors as of April, according to the Center for Inclusive Computing at Northeastern University. These numbers have risen dramatically. In 2021, just five schools offered majors in AI, The New York Times reported.
How it works: Course requirements for a bachelor’s degree in artificial intelligence run the gamut. Some programs are highly technical and math-intensive, while others take a broader, interdisciplinary approach that includes courses in ethics, policy, or domain-specific applications. Some emphasize the theoretical foundations of AI, while others focus on how to build and deploy AI systems in practice.
- Carnegie Mellon University, a university in the state of Pennsylvania with one of the country’s top Computer Science programs, became the first U.S. university to offer a bachelor’s degree in artificial intelligence in 2018. Its curriculum emphasizes mathematical rigor, requiring seven courses in mathematics and statistics, five in computer science and principles of computing and programming, three in artificial intelligence, one in ethics, and additional courses spanning human cognition, perception and language, machine learning, and human-computer interaction.
- The University of Oklahoma Polytechnic Institute’s applied AI degree focuses on practical knowledge. Apart from math and statistics requirements, it requires students to complete 15 AI and computing courses in subjects including robotics, machine learning, reinforcement learning, computer vision, cloud computing, and DevOps.
- Other AI degrees are more interdisciplinary. Drake University in Iowa offers a bachelor of arts in AI tailored to students in humanities and business. The course requirements are flexible, allowing students to choose from clusters of courses in philosophy, English, computer science, information systems, and psychology. Only two math classes are required for the degree.
- Many schools that don’t provide AI degrees offer specialized AI concentrations. Students on the AI track at Stanford University take seven qualifying courses in fields such as natural language processing, computer vision, and robotics. (Disclosure: Andrew Ng serves as an adjunct professor in Stanford’s Computer Science department.)
Behind the news: Some commentators argue that universities have moved too slowly to prepare students for employers that expect AI competency. Others dismiss AI degrees as a fad. However, even some proponents warn that specialized AI degrees may come at the expense of broader computer science foundations, which students may need to adapt in a rapidly evolving field.
Why it matters: Today’s curricula could shape who enters the profession and what skills the next generation of AI engineers brings with them. It’s only natural to expect a standardized, one-size-fits-all education in a field as varied as AI. Some roles in industry resemble traditional software engineering jobs with AI components; others require deeper expertise in machine learning research, distributed systems, or data engineering. There will also always be large gaps between programs designed to prepare students for graduate work and others that assume the bachelor’s will be a terminal degree.
We’re thinking: AI is moving so quickly that many universities are struggling to adapt. The established pace of change in academic curricula — in which the faculty learns a topic, proposes new courses, gets approval from a curriculum committee, and perhaps modifies degree requirements — is poorly matched to the rapid pace of change of AI. However, we are glad that universities are moving in this direction, and that a number of innovative faculty and administrators are finding ways to move faster. This will be important to prepare students not only for the jobs of 2026, but for those in many years beyond.