One of the first applied GenAI-native business degree suites in the country
The Master of Science in Artificial Intelligence (AI) in Business launches Fall 2026 with two majors:
Digital Transformation (100% online)
For experienced professionals. Prepares graduates to lead enterprise AI strategy, governance, and organizational change. Career paths include GenAI Program Manager and Digital Transformation Lead.
Enterprise Integration (in person)
For recent graduates and early-career professionals. Prepares graduates to design, build, and deploy applied AI systems in business. Career paths include AI Analyst, GenAI Agent Architect, and AI engineer Architect.
Graduates work in businesses such as banking, healthcare, consulting, energy, retail, entertainment, telecom, and other sectors. This is a STEM-designated program.
Note: The above majors replace the Master of Science in Artificial Intelligence (AI) and Business Analytics.
Compare the Majors
MS AI in Business & Digital Transformation
Lead and govern applied AI.
Who It's For
- Experienced professionals
- Future AI and digital leaders
- Learn how to lead, govern, and scale GenAI & Agentic AI in business.
What You'll Learn
- Digital transformation strategy and ROI
- Enterprise architecture and data strategy
- Evaluation, vendor selection, and deployment
- Agentic AI systems and process redesign
- AI governance, risk, and security
- Change management and GenAI adoption
- Current trends: Orchestration, process mining, data lakes, MCP, RAG, SLMs, guardrails, model evaluation, & others.
- Capstone: Board-ready AI transformation blueprint
Career Paths
-
AI strategy and transformation leadership
-
AI program and portfolio management
-
Applied AI product and functional leadership
- GenAI program manager
Format
- 100% synchronous online weekend classes
- 10 courses, 30 credits
MS AI in Business & Enterprise Integration
Build, deploy, and integrate applied AI in business.
Who It's For
- Recent grads
- Early-career professionals
- Learn how to apply, build, deploy, and integrate AI, GenAI, and Agentic systems.
What You'll Learn
- Data analytics with GenAI
- Applied machine learning and deep learning
- GenAI data pipeline & RAG
- GenAI enterprise applications
- Agentic AI and business process design
- AI governance, security, and privacy
- Current trends: MCP, A2A, Agent frameworks (e.g., LangGraph), vector databases, LLMOps, LoRA, & others
- Capstone: AI integration blueprint and prototype
Career Paths
- GenAI analyst, RAG integration, Agentic AI analyst
- AI engineer
- AI and machine learning architect
- Data pipeline architect
Format
- In-person and full-time
- 10 courses, 30 credits