BU’s New Online MS in Software Engineering for AI Prepares Engineers for the Age of AI - Boston University

Artificial intelligence is changing both what software engineers build and how they build it. Engineers are incorporating AI into products, using AI-assisted development tools, managing new types of data and models, and making decisions about reliability, security, transparency, and responsible use. These changes are happening quickly and software professionals cannot wait for the field to settle before developing the skills to work within it.

In Fall 2026, Boston University welcomed the inaugural cohort of its Online Master of Science in Software Engineering for Artificial Intelligence. Designed for experienced software engineers, developers, and technical professionals, the program prepares students to build, deploy, and manage AI-enabled software systems while strengthening the engineering foundations those systems require.

Preparing for a Field That Is Still Evolving

Software engineers now face two connected challenges. They must learn how to build software that incorporates AI, and they must understand how AI is changing the process of developing software itself.

BU’s program addresses both challenges. The curriculum combines software engineering fundamentals with machine learning, AI- and LLM-aided software development, scalable data systems, MLOps, responsible AI, and human-centered design. Through a year-long capstone, students bring these areas together by developing an end-to-end AI-enabled application designed to operate at scale.

Students will be learning in a field that is still being invented. That requires faculty who are not simply teaching established material, but actively studying how the discipline is changing.

“Software engineering for AI is developing in real time. Our goal is to bring current research into the classroom while it still reflects the realities of the field. We are preparing engineers not only to work with the systems available today, but also to evaluate and shape what comes next.”

— Mohamad Kassab, Program Director

Program Director Mohamad Kassab conducts research in software architecture, software quality, requirements engineering, and AI-intensive systems. Associate Chair Ed Solovey brings more than 25 years of experience building data-intensive and distributed systems, including senior engineering roles at Oracle, Adobe, Brightcove, Twitter, and Google. Their current work examines questions that software engineers are confronting now, including AI-assisted development, verification, responsible AI, and the growing role of autonomous tools.

That connection to current research and practice helps the program evolve with the field. Rather than centering the curriculum on a specific product that may soon change, faculty focus on principles students can use to evaluate new tools, understand their limitations, and make sound engineering decisions as technology advances.

Learn With Professionals Solving Real Problems

The program’s inaugural cohort reflects the range of industries already adapting to AI. It has attracted professionals working at organizations including Microsoft, Amazon Web Services, Adobe, Boeing, Lockheed Martin, American Express, Capital One, Citi, Bristol Myers Squibb, GSK, National Grid, and the U.S. Department of Defense.

Students also come from telecommunications, manufacturing, health care, government, consulting, higher education, startups, and independent ventures.

“We are delighted to welcome an inaugural cohort whose experience spans industries and professional backgrounds. That range will strengthen the learning experience. Students will build new skills, challenge their thinking with accomplished peers, solve real problems together, and put what they learn to work immediately in a field being reshaped in real time.”

— Adelaide Adams, Director of Marketing and Enrollment, BU Virtual

Those employer names demonstrate the caliber of professionals interested in the program, but the greater value comes from the different perspectives they bring into the classroom.

An engineer working in aerospace approaches reliability and failure differently from someone developing a commercial technology platform. Financial services professionals operate in environments shaped by security, governance, and accountability. Health care and life sciences professionals bring experience with sensitive data and responsible use. Energy professionals understand the demands of resilient infrastructure.

When students examine an AI-enabled system together, these perspectives reveal risks, requirements, and possible solutions that one industry alone may overlook. A classmate may have already encountered a similar integration problem. Someone working under different regulatory requirements may challenge an assumption. A peer responsible for large-scale systems may identify why a promising prototype will struggle in production.

In this way, the cohort becomes part of the learning experience. Students learn from faculty, course materials, and the experience of professionals applying technology under real operating constraints.

Apply What You Learn While You Work

Because the program is designed for working professionals, students do not have to wait until graduation to connect their education with their careers.

They can bring workplace questions into class and apply new approaches to the systems, projects, and decisions they already manage. A lesson about AI-assisted testing may inform a current development workflow. Work on scalable data architecture may help a student evaluate an existing system. A discussion about responsible AI may change how a team approaches governance, user experience, or risk.

Applying new knowledge at work also strengthens the classroom. Students can examine how a concept operates under real conditions, return with questions, and share what they have learned with their peers. This creates a continuing exchange between academic study and professional practice.

The result is an education grounded in current workplace realities rather than hypothetical technical exercises alone.

A Connected Classroom, Wherever Students Are

Working professionals need flexibility, but flexibility does not have to mean learning alone.

Students participate in weekly live sessions supported by the BU Virtual Studios. Faculty work with instructional designers, learning facilitators, producers, and technical teams to create an online environment built for discussion, demonstration, collaboration, and problem-solving.

Students can ask questions, work through technical concepts, and engage with classmates joining from different locations and time zones. Recordings and online course materials help them manage their studies around work, family, and other responsibilities.

This model brings the classroom to students wherever they are while preserving the interaction that makes graduate education valuable. Students are not simply watching lectures. They are learning with faculty and peers, exchanging ideas, and working through problems together.

Building What Comes Next

No one can predict every tool or capability that will define artificial intelligence several years from now. Software engineers can, however, develop the foundations, technical judgment, and practical experience needed to adapt.

BU’s Online Master of Science in Software Engineering for Artificial Intelligence prepares students to understand AI as both a component of modern software and a force changing the engineering profession. Students learn from faculty working at the field’s forefront, collaborate with experienced professionals across industries, and apply what they learn in their current work.

For software engineers preparing for the age of AI, the goal is not simply to keep pace with change. It is to build the knowledge and judgment needed to shape what comes next.