With the rapid advancement of AI affecting all sectors of society, Columbia Engineering announced a new Master of Science in Artificial Intelligence (MSAI) program that combines core AI courses in computer science and engineering with a broad range of concentrations, through a partnership with many Columbia schools, to provide students with specialized domain-specific training.
This new program comes at a time of unprecedented demand for talented graduates with solid foundational skills in AI and the ability to apply them across different domains. The program will have both an in-person, on-campus version and a fully online version. Both share the same rigorous requirements, and the online program will feature a high-touch cohort-based approach designed to enhance the online learning experience.
Specialized concentrations are designed to leverage the Engineering School’s unique excellence in related fields such as advanced computing, robotics, operations and finance, biomedical engineering, infrastructure and hardware, and in various academic disciplines across the university, such as policy, medicine, public health, architecture, statistics, as well as media and the arts. Students completing the program will be awarded an MS in Artificial Intelligence degree with an annotation of the specific concentration on their transcript.
“The MSAI fills a gap between pure technical degrees, like computer science and data science, and programs focused on specific domains such as health or finance,” said Vishal Misra, RKS Family Professor of Computer Science and vice dean of computing and AI, who is co-director of the program. “With Columbia’s extensive AI research presence, students have all the resources they need to support their education in this highly interdisciplinary area.”
Preparing leaders for the AI era
The MS program will be a 30-credit degree program consisting of four core AI foundational courses and four courses in a chosen concentration. Two additional courses will be electives or an option for a two-semester capstone project that includes working with industry partners on real-world challenges.
All incoming students must possess proficiency in programming (especially Python), data structures/algorithms, linear algebra, and calculus/probability. With its interdisciplinary scope, the program seeks to attract talented students from diverse backgrounds and will provide a pathway to support interested students in need of preparatory or bridge courses.
“While we expect many students will have a computer science, computer engineering, or software background, the program is designed to accommodate students from other disciplines and professionals with different backgrounds without diluting the rigor of the core curriculum,” said Garud Iyengar, Avanessians Director of the Data Science Institute, and professor of industrial engineering and operations research, who is also co-directing the program. “For example, someone with a healthcare background and basic programming skills can learn AI to become a specialist in AI for healthcare, whereas someone with a computer science background may want to deepen their foundation in a domain like finance or policy. The mix of backgrounds will enrich all aspects of the program.”
Columbia’s efforts in AI span across the University and include external industry and government partners. The Engineering School has more than 70 full-time faculty members and 10+ large research centers focused on AI across departments and collaborations with other schools. The School also hosts an ongoing Lecture Series in AI, bringing leading voices in AI to campus. In the fall of 2025, the School announced a minor in AI for undergraduates. The MSAI program will begin in the fall of 2026.
“With its unique rigor and broad scope, this program is the first AI graduate program to include such comprehensive cross-disciplinary concentrations,” said Shih-Fu Chang, Dean of Columbia Engineering. “21st-century society demands that these kinds of educational pathways be made possible for our students. We’re proud to offer such a unified and rigorous AI curriculum with opportunities to apply AI in various domains so that students are prepared for success in their chosen field.”
Professional outlook
Graduating with a graduate degree in Artificial Intelligence offers numerous career prospects due to the booming demand and persistent talent shortage in the AI field. The Columbia MS in Artificial Intelligence program is designed to meet industry needs by offering technical depth in AI, domain fluency across sectors such as finance and health, and an emphasis on ethics and governance. With the global AI market projected to reach $407B by 2027 and 97 million new AI-related roles expected worldwide by 2030, opportunities are abundant. Positions such as AI/ML engineer, applied scientist, and data scientist (AI focus) are ranked among the fastest-growing job categories. Graduates from the MSAI program, strategically located in New York City, a hub for industries like finance, healthcare, media, and law, gain a distinct advantage. Industries are actively seeking skilled professionals for roles in AI models/tools/systems developers, algorithmic trading, fraud detection, AI-driven medical imaging, and AI content generation, among others.
The application process for the Fall 2026 term is open with the initial target deadline of March 15, 2026, for the on-campus program and a deadline of August 15, 2026, for the online program. Students interested in the program may find further information on the program websites.
An interdisciplinary offering
The degree will be offered with concentrations across Columbia in medicine, public policy, public health, the arts, statistics, and architecture.
The program draws on faculty and academic support from the Vagelos College of Physicians and Surgeons, the Mailman School of Public Health, the School of the Arts, the School of International and Public Affairs, the Department of Statistics, and the Graduate School of Architecture, Planning and Preservation.
Additional concentrations—such as Journalism—may be added in the future.
