2025 AI Degree Report: The Landscape of AI Degrees in the United States

Artificial intelligence education is expanding rapidly in U.S. universities, with hundreds of bachelor’s and master’s degrees in AI now available. To get a better grip on this phenomenon, we decided to take a snapshot of the 2025 AI education landscape, analyzing trends in degree offerings, state & regional availability, research spending, admissions requirements, and delivery methods. Learn why Southern schools win on volume but the Midwest may be the region to watch. Explore why Texas currently has the lead over California. And discover which universities & students are being left behind in the AI race.

2025 AI Degree Report Methodology

Our 2025 report on artificial intelligence degree programs in the United States is designed to give you a clear picture of the state of AI higher education at a critical moment in the country’s history. To that end:

• Program Inclusion: This report focuses specifically on bachelor’s and master’s degrees in artificial intelligence. There are a number of certificates and PhD programs in AI, which we profile in our MastersinAI.org directories and guides, but they were not included in this particular analysis.
• Degree Classification: For the purposes of this report, the term “AI” degrees includes any standalone degree in AI; any computer science, engineering, or related program with an AI specialization/concentration/track; and any degree in an AI subject such as Master’s in Machine Learning (ML). Tech-adjacent majors like data science were not included unless they had a specific AI concentration or track.
• Program Availability: All data on program availability was sourced from our comprehensive database of artificial intelligence degrees. The database was launched in 2021 and is updated regularly.
• Data Sources: Other data sources used in this higher education report include: Carnegie Classifications of R1 & R2 institutitions; IPEDS data for simple categorization (e.g. university types, profit vs non-profit, etc.); and U.S. Census Reports for regional classifications.

AI degree programs are launching constantly, so this report will be refreshed over time as additional data points become available. If you know of an AI degree program not yet included in our directory, or have questions about the findings in this report, we would love to hear from you. Contact us at [email protected].

National Overview of AI Higher Education

Within the past five years, artificial intelligence degrees have become one of the most popular academic offerings at U.S. colleges and universities. 304 higher education institutions across the nation have developed undergraduate & graduate programs in AI. In 2025, 153 universities in the United States offered master’s qualifications in AI; 85 universities offered bachelor’s programs; and 66 universities offered both bachelor’s & master’s programs in AI. It is the degree of the decade.

Traditionally, it has been graduate schools that have been in the vanguard of AI. In 2022, there were 116 master’s in AI programs in the USA. In 2025, there were 310, a number which includes closely related fields such as Machine Learning (ML). These types of programs frequently build on preexisting AI expertise & research labs within a Department of Computer Science or College of Engineering. U.S. business schools are also increasingly aware that technical AI skills are required in management & business settings.

But the real seismic change in AI learning is occurring at the undergraduate level. Bachelor’s in AI degrees in the USA experienced a 114.4% growth rate from 2024 to 2025 (90 programs to 193 programs) as universities scrambled to catch up with demand from younger learners and competition from China and India. Many universities are now following the example of Carnegie Mellon University, which launched the nation’s first BS in AI in 2018. Even small private colleges have expanded their BS in Computer Science programs to include an AI track.

Regional Distribution of AI Degree Programs

It seems counterintuitive that the South should be the #1 provider of AI higher education in the United States. Until one realizes that the Southern region is home to Texas, Florida, and North Carolina. Within these states, government investment and growing student markets are helping to fuel STEM research & degree development at public universities. Texas alone has 21 schools offering AI undergraduate & graduate programs, making it the largest state in the country for artificial intelligence degrees. Even lesser known states like Georgia are being buoyed by major AI players like Georgia Tech.

More intriguing is the emergence of the Midwest as the #2 provider of AI higher education. This region is home to innovative multi-state projects such as the Midwest Big Data Innovation Hub (MBDH), NSF National AI Research Institutes such as AI-EDGE, flagship schools like the University of Michigan with impressive R&D expenditures (see the NCSES HERD Survey for more details), and an increasing number of MAANG-funded data centers. It’s also a well-known hub of advanced manufacturing, robotics, and ag-tech—three critical sectors that rely on AI for their existence.

In the Northeast, Pennsylvania, New York, and Massachusetts are the leaders in artificial intelligence degree offerings. Here you’ll find initiatives such as the NSF-funded Northeast Big Data Innovation Hub (NEBDHub), the unique New York public-private university consortium Empire AI, and—of course—Carnegie Mellon University and MIT. Their graduates don’t need to go far. According to a 2025 Public Insight report on AI and Machine Learning Job Trends, New York City (fintech) and Boston/Cambridge (biotech & robotics) consistently rank among the top U.S. metro areas for AI job postings.

And then there’s the West. In 2025, Western schools offered less than half of the AI degrees offered by Southern schools; the West itself accounts for just 17% of universities in our AI program directory. Stanford and the University of California System continue to wave the AI flag for California, but tech-friendly states like Colorado and Washington appear to be faltering. But it’s important to note that this may be down to naming traditions. Instead of developing new AI programs, West Coast schools like the University of Washington are simply incorporating artificial intelligence studies into their existing (and prestigious) computer science & data science degrees.

State-Level Trends in AI Education

The #1 state in artificial intelligence higher education is Texas—21 schools in the Lone Star State offered 39 AI degree programs in 2025. Thanks to a constellation of factors, Texas is particularly strong in AI graduate studies. Public universities in Texas are supported by state incentives such as the Governor’s University Research Initiative (GURI) and the Texas University Fund (TUF). R1 universities are busy developing their own supercomputers & AI institutes (see UT Austin’s Texas AI). And oil & gas companies are pumping money into advanced energy initiatives with AI applications (e.g. University of Houston’s Energy Transition Institute).

It’s also not surprising to see California and New York in the top 5 states for artificial intelligence degrees. California has a long history of tech investment & startup funding, supported by top-level AI research at Stanford and schools within the UC System. New York is the home of the New York Stock Exchange (NYSE), the Empire AI consortium, and the largest fintech sector in the USA.

New York’s neighbor, Pennsylvania, is the seat of two massive university presences in artificial intelligence. Carnegie Mellon University (CMU) and the University of Pennsylvania account for the lion’s share of AI graduate degree offerings in PA. Because of CMU, there’s now a dense robotics & AI commercialization ecosystem in Pittsburgh. The university is also spearheading the $20 million NSF AI Institute for Societal Decision Making (NSF AI-SDM).

In Florida, it’s the big public universities that are helping to spur innovation (AI programs in the Sunshine State burgeoned from 3 programs in 2022 to 30 programs in 2025, a 900% growth rate). In 2020, the University of Florida announced a $70 million artificial intelligence partnership with NVIDIA. In 2023, it distributed nearly $19 million in state funds to support AI projects in 10 colleges. And in 2025, it planned to inject $24 million into a upgrade of its HiPerGator AI. But UF isn’t the only player in town. In 2024, the University of South Florida (USF) launched its $40 million Bellini College of Artificial Intelligence, Cybersecurity and Computing.

But we also wanted to know which areas were punching above their weight! So we decided to analyze state growth rates in AI degree programs from 2022 to 2025. Iowa was an unusual standout—it had 1 AI degree program in 2022 and 11 programs in 2025 (1,000% growth rate). Due to the driving force of SD public universities, South Dakota had a similar story, growing from 1 AI degree program in 2022 to 9 programs in 2025, especially at the undergraduate level (800% growth rate). These statistics reflect the overall regional surge of AI higher education in the Midwest.

Types of Universities Offering AI Programs

There is a clear correlation between research spending and AI education in the USA. To take just one example, in 2025, 16 universities in Texas attained R1 status. This designation is granted to schools that spend at least $50 million on research and award at least 70 research doctorates on average per year. It’s no accident that Texas R1 institutions have also developed a staggering 18 master’s degrees and 5 bachelor’s degrees in AI. It’s a similar story in Florida, Pennsylvania, Massachusetts, and New York—R1 universities in these states easily outpace their R2 and non-designated counterparts in offering AI programs.

Fascinatingly, different university systems are driving change. In Southern states such as Texas, Florida, North Carolina & Virginia and Midwest states such as Indiana & Ohio, public universities are the clear leaders in providing AI higher education programs. In the Northeast, it’s famous private universities in Pennsylvania, New York, and Massachusetts that offer the most choice. The Northeast has a dense cluster of private R1/R2 and Ivy League institutions with prestigious engineering & computer science departments. In contrast, the South and the Midwest are dominated by well-funded public research flagship and land-grant universities.

It’s a more challenging narrative for Historically Black Colleges and Universities (HBCUs). In 2025, only 5% of HBCU schools had developed degrees in artificial intelligence and only one of them—Howard University—had achieved an R1 designation. The largest HBCU provider of AI programs in 2025 was North Carolina A&T State University, which only offered 2 bachelor’s programs and 1 master’s degree. In addition to being underfunded by decades, HBCUs lack the endowments, federal R&D dollars for AI centers, faculty, and MS/PhD ecosystems of R1 & R2 institutions. These are serious headwinds.

Departmental Trends: Where AI Degrees Are Housed

It makes sense that the vast majority of AI degrees have a technical parent. In 2025, 37% of AI programs in the USA were being offered by Departments of Computer Science and 22% by Colleges or Departments of Engineering. As always, it’s the South that leads the way. In 2025, computer science departments in the Southern region of the USA were responsible for 86 AI degree programs. Texas alone had 18 AI programs under the banner of computer science and Florida had 17.

And while the Northeast has a diverse range of AI degree offerings from multiple departments, the West and the Upper Midwest are making names for themselves in AI engineering. For example, in Michigan, there are multiple engineering-focused graduate degrees in AI at big public research universities (e.g. University of Michigan-Ann Arbor) and smaller private universities (e.g. Kettering). This trend probably reflects the Upper Midwest’s strengths in manufacturing and ag-tech and the region’s increasing need for 21st century engineers. Farther to the west, you’ll find plenty of engineering-focused AI programs within California.

But the real story is the astronomical rise of business-focused AI programs, including MBA offerings. Across every region of the country, Schools of Business have been scrambling to develop AI qualifications that will equip corporate leaders with strategic skills. You’ll now find 68 business AI degrees in over half of the states, with more programs coming on-board each year. Our guide to MBA in Artificial Intelligence Programs has details on this phenomenon, including the dominance of schools in the Mid-Atlantic region like CMU Tepper and UPenn Wharton.

AI Graduate Admissions: Requirements and Trends

Admissions standards for master’s degrees in artificial intelligence are typically dependent on the department that created them. For example, within a Department of Computer Science or a College of Engineering, it’s common to find AI degrees that are only open to applicants with an undergraduate major in a STEM field (e.g. computer science, math, physics, engineering, etc.) and skills in programming, math, statistics, calculus, and algorithms. In contrast, AI master’s degrees from Schools of Business, Colleges of Professional Studies, and interdisciplinary departments often welcome candidates with a bachelor’s degree in any major and little or no skills in programming.

In the past, the Graduate Record Examinations (GRE) test was a standard requirement for admissions to master’s and doctoral degrees in the USA. But COVID-19 changed the game. Many universities suspended the GRE requirement during the pandemic and eventually adopted a “No GRE” or test-optional policy going forward. Some decided the GRE was serving as a barrier to equity & diversity. Others made the decision to shift to a holistic review process. The result? Over half (62%) of master’s degrees in AI in the USA do not require GRE scores for admission. The minority that continue to insist on GRE scores are often interested in an applicant’s quantitative skills.

The standard minimum GPA requirement for a master’s degree in AI is a 3.0 GPA on any undergraduate work. This precept holds true for prestigious R1 & R2 universities, as well as small private colleges and state universities. But there is a sting in the tail. When we analyzed class profiles for some of the top graduate programs in AI, we found that the average GPA of successful applicants was often higher than 3.5. At Rutgers, the average GPA of a recent entering class for the MSCS in AI/Machine Learning was 3.6. At Stanford, the average GPA for the MS CS in Artificial Intelligence was 3.7. As you might expect, computer science and engineering degrees in AI tend to have higher GPA standards than business degrees in AI.

Online AI Degrees in 2025: Availability and Growth

Online learning in AI is on the rise, driven by market demand, employer acceptance, and changes in higher education habits brought on by COVID-19. This is especially noticeable at the graduate level, where online master’s degrees in artificial intelligence grew from 42 programs in 2022 to 158 programs in 2025. The majority of these programs (42%) can be found in Southern universities located in states such as Texas and Florida. We explore online master’s degrees in AI and profile the nation’s top offerings in our rankings of the 21 Best Online Master’s in Artificial Intelligence Programs.

Interestingly, although Midwestern and Western universities can’t compete with Southern universities on the graduate level, they are often more “online-friendly” to AI undergraduates. In 2025, 26% of AI bachelor’s degrees in Western schools and 22% of AI bachelor’s degrees in Midwestern schools were delivered online. In contrast, only 15.5% of AI bachelor’s degrees in Southern schools and only 4.3% of degrees in Northeastern schools were delivered online. And it’s not California that’s driving change in the West. It’s states like Arizona that are championing distance learning for AI undergraduates.

These trends indicate that access to AI higher education is being democratized outside traditional tech hubs and R1 institutions on the East & West Coast. For instance, it didn’t surprise us to learn that only 29% of AI degrees within R1 universities are delivered in an online format (67 programs out of 235 programs). R1 institutions pride themselves on developing in-person graduate education experiences and on-campus research opportunities through their AI institutes. It’s part of the reason their tuition costs are so high!

On the other hand, in 2025, 37% of AI degrees in R2 institutions and 49% of AI degrees in non-designated institutions were being offered online. If you want to know where distance learning in AI is really taking off, look to non-R1 universities in the South, Midwest, and Southwest.

Conclusions: The State of AI Degree Programs in 2025

Artificial intelligence degrees are becoming a well-known factor in U.S. universities, both at the graduate level and the undergraduate level. Standalone degrees in AI are now joining AI concentrations in traditional majors like computer science and computer engineering. Business schools are pumping out MBA in AI programs. Even smaller Departments of Math and Informatics are jumping on the education bandwagon and beginning to develop quantitative-focused degrees in artificial intelligence.

However, the growth of AI higher education programs is not evenly spread across the country. Certain states are surging ahead while other areas are being left behind.

• College students who are fortunate to live in Texas and Florida can take advantage of a huge number of AI degree options, including some from prestigious R1 institutions with NSF-funded artificial intelligence institutes.
• Midwest students in Illinois, Indiana, and Michigan can look to their public flagship universities for AI education opportunities, especially in engineering disciplines. Similarly, California students can enroll in respected AI programs within the UC System.
• Intelligent students from Pennsylvania, New York, and Massachusetts can tap into the AI strengths of prestigious private schools like Carnegie Mellon, Columbia & MIT. Having said that, they will be competing with talented out-of-state applicants and paying a hefty tuition price for their education.

It’s a bleaker scenario for students living in AI educational deserts. Smaller state and private universities who lack endowments, money from public/private tech partnerships, and NSF funding often do not have the resources or expertise to develop in-depth artificial intelligence degree programs, especially at the graduate level. At HBCU schools, AI program offerings are extremely limited. And in places like Kansas, Arkansas, North Dakota, and New Mexico, there may only be one AI degree available within the entire state. Unless more funding and support is provided at city, state & regional levels, the gap between the “haves” and the “have nots” in AI higher education could continue to increase.

There are some bright spots on the horizon:

• U.S. universities are taking a more holistic approach to AI graduate program admissions, often omitting the GRE requirement and considering candidates without an undergraduate degree in a STEM field.
• There’s also been impressive growth in online AI degree programs at both the graduate and the undergraduate level. Although R1 universities are sometimes hesitant to commit to 100% online learning, R2 and non-designated universities are coming on strong.

The chance to earn a bachelor’s or master’s in AI remotely can reduce the barrier to entry for many students—especially those on a budget—but it doesn’t deal with the issue of prestige. An employer is more likely to pick a candidate with an on-campus computer science or AI degree from an R1 institution in Texas than an online AI degree from an obscure state school in West Virginia.

One solution is for universities to follow the lead of Upper Midwestern schools and develop expertise in a realm of AI that aligns with local industries (e.g. Michigan’s strengths in robotics, AI engineering, ag-tech & automotive AI). This approach helps to attract funding for programs. And it gives students a clear pipeline to employment after graduation.