Mapping AI Programs in the U.S: A Status Report from Early 2026 and an Analysis of AI Majors and Minors
This paper presents a comprehensive 2026 status report on U.S. undergraduate AI programs, introducing a dynamic mapping tool that tracks over 350 majors and minors across 560 institutions while analyzing curricular requirements to reveal significant variability in course structures, particularly regarding the inclusion of general AI and ethics courses.
Original paper licensed under CC BY 4.0 (http://creativecommons.org/licenses/by/4.0/). This is an AI-generated explanation of the paper below. It is not written or endorsed by the authors. For technical accuracy, refer to the original paper. Read full disclaimer
Imagine the United States as a massive, sprawling library with hundreds of different branches. For years, if you wanted to find a specific book on "Artificial Intelligence" (AI), you had to guess which branch had it, walk to the front desk, and hope the librarian knew exactly where it was hidden in the back. Sometimes the books didn't even have a clear label, or they were tucked away in a section that didn't look like a library at all.
This paper is like a team of librarians who decided to build a super-powered, living map of this entire library system. Here is what they did, explained simply:
The Mission: Finding the Hidden AI Classes
The authors (a team from Northeastern University) noticed that while everyone is talking about AI, no one actually knew exactly where these programs were located or what they contained. They wanted to stop the guesswork.
They built a digital "robot explorer" (a tool called cicmap.ai) that went out and visited over 569 universities across the U.S. Think of this robot as a very fast, tireless student who can read thousands of websites in a day. It looked for AI programs—whether they were full degrees (Majors), smaller add-ons (Minors), or special tracks (Concentrations).
The Robot's Journey
The robot didn't just guess; it had a human partner.
- The Search: The robot used search engines to find university websites.
- The Filter: It used a smart computer brain (an AI model) to find the specific pages for Computer Science and AI departments.
- The Human Check: Because computers sometimes get confused (about 1 in 3 times), a human team double-checked the robot's findings to make sure the links were real and correct.
- The Map: Once verified, the robot put all this data onto an interactive map. You can zoom in on any state, click on a school, and see exactly what classes you need to take to get that AI degree.
What They Found: A Patchwork Quilt
When the team looked at the data they collected (as of early 2026), they found a few interesting things:
- It's Growing Fast: They found 73 full AI majors and 89 AI minors just in the schools they checked. But the number is climbing fast—like a plant growing overnight.
- The "Concentration" Shortcut: The most common type of program wasn't a full new degree, but a "concentration." Imagine a big tree (a Computer Science degree) with a special branch (AI). It's easier for schools to grow a new branch than to plant a whole new tree, so many schools chose this path.
- Size Matters: Big universities were more likely to have full AI degrees, while smaller schools were more likely to offer just a minor or a concentration.
The "Recipe" for an AI Degree
The team also looked at the "recipes" (the required courses) for these degrees to see if they were all the same. They found that every school cooks a different dish, even if the main ingredient is the same.
- The "Must-Haves": Almost all AI majors (92%) require a general "Introduction to AI" class. If a school skips that, they almost always require a "Machine Learning" class instead.
- The Ethics Question: About one-third of the majors require a class on "Ethics in AI" (learning how to be a good, responsible AI creator). However, for the smaller "Minor" programs, only about one-quarter require this ethics class.
- The Mix: Some programs are very strict, forcing you to take specific classes like Robotics or Computer Vision. Others are more like a buffet, letting you pick and choose from a list of options.
Why This Map Matters
Before this tool, if you were a student, a parent, or a school counselor trying to find an AI program, you might have missed great options because they were buried in complex websites or didn't show up in a simple Google search.
This paper gives us:
- A Snapshot: A clear picture of where AI education stands in the U.S. right now.
- A Tool: A way for anyone to easily find these programs and see exactly what classes are needed.
- A Record: A history of how these programs are changing, which will help researchers and schools understand the future of education.
In short, the authors built a GPS for the world of AI education, helping everyone navigate the confusing landscape of college programs to find the right path for learning about Artificial Intelligence.
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