AI pilots are everywhere but production-grade AI systems are not. The gap between proof-of-concept and enterprise deployment is where careers and organizations stall. The online MS in Enterprise AI prepares you to design, deploy, and govern AI-enabled systems at organizational scale. As AI moves from pilots to production, organizations need leaders who can integrate models into real products and workflows—securely, reliably, and responsibly.
You’ll build practical skills in AI system architecture, large language model applications, deployment and monitoring, data pipelines, security, and governance. This online masters in AI program blends technical foundations with hands-on work so you can translate strategy into enterprise-ready systems. Graduates pursue careers in AI leadership, enterprise architecture, and AI strategy across industries.”
Courses
Degree Requirements
Dates and Deadlines
Requirements
Application Requirements
- Transcripts
- CV/Resume
- Personal Statement
- Optional letter of recommendation
- GMAT/GRE not required
How You Benefit from the Online MS in Enterprise AI
- Build the AI Stack: Learn how data pipelines, infrastructure, models, and applications come together—plus how to deploy, monitor, and improve them over time.
- LLMs and Modern AI Applications: Explore how large language models and agent-style systems are used in products and operations, and what it takes to run them reliably.
- Security, Governance, and Responsible AI: Develop the guardrails organizations need: risk management, privacy, compliance, and practical governance for production AI.
- Affordable and Accessible: A 100% online format with live sessions helps you learn actively and apply new skills without pausing your career. At $25,000 total tuition, BU’s MS in Enterprise AI offers a high-quality education at an accessible price point without sacrificing rigor, relevance, or connection.
Skills You’ll Gain
- AI System Architecture & Integration. Design how models, services, and data fit into real enterprise systems.
- MLOps, Deployment & Monitoring. Ship AI to production, track performance, and keep systems healthy over time.
- AI Governance, Risk & Responsible AI. Set practical guardrails for security, privacy, compliance, and model risk.
- LLM Applications and Agentic Workflows. Build and manage LLM-powered applications that support real business processes.
- Data Pipelines & AI Infrastructure. Understand the data and platform foundations that make AI scalable and reliable.
- Value Measurement & Operational Adoption. Define success metrics and drive adoption so AI work translates into impact.
- Performance Telemetry & Continuous Improvement. Track system health, quality, and drift so AI systems improve safely over time.
Azer Bestavros
“This program takes the deep technical foundations from data science and computer science and connects them to real enterprise challenges. You’ll learn how to operationalize AI, build resilient AI systems, manage risk and governance, and lead interdisciplinary teams.“
Warren Distinguished Professor of Computer Science
Associate Provost for Computing & Data Sciences