University of Mary Washington — MS in AI in Business

Build AI solutions for real business problems

GBUS 563 is the applied core of the MS in AI in Business: eight weeks, fully asynchronous, one hands-on build per week across marketing, customer service, operations, and finance — culminating in a capstone AI solution you design, defend, and pitch for an organization you know.

  • 3 graduate credits · 8-week session · 100% asynchronous
  • Seven applied labs plus a capstone solution
  • Platform-neutral: Claude, ChatGPT, and no-code tools

This site is the course learning environment for enrolled GBUS 563 students. New accounts are approved against the course roster; all grades and official submissions live in Canvas.

Meet Anand.AI, your course guide

Anand.AI learns your role, industry, and goals on day one, then frames every week around your work — debriefing each lab, pressure-testing your capstone framing, and connecting course frameworks to your organization. It coaches and questions; it never grades you, never writes your deliverables, and the course teaches you to verify everything it says.

Eight weeks, eight builds

Each week pairs one business function with a working build. The first half covers the core functions; the second half integrates them into assistants and agents, responsible deployment, and your capstone.

  1. Framing AI Solutions for Business

    Lab: AI Opportunity Audit

  2. AI for Marketing and Sales

    Lab: AI-assisted campaign engine

  3. AI for Customer Service and Experience

    Lab: Customer-service assistant · capstone proposal

  4. AI for Operations and Process Automation

    Lab: End-to-end workflow automation

  5. AI for Finance and Decision Support

    Lab: AI-assisted financial analysis

  6. Building Integrated Solutions: Assistants and Agents

    Lab: Custom assistant or agent prototype

  7. Responsible Deployment: Risk, Governance, and Change

    Lab: Governance, risk, and ROI assessment

  8. Capstone: From Prototype to Pitch

    Lab: Prototype, solution report, recorded pitch

How the course works

One steady weekly rhythm

Modules open Monday morning. You watch short lecture segments, work through curated readings, post to the discussion by Thursday, and finish the week's hands-on lab by Sunday. The rhythm never changes, so the course fits around a working professional's week.

Build something every week

Every week pairs one business function with a working build: a campaign engine, a service assistant, an automated workflow, a financial analysis package. Labs are drafted here in a structured workspace, then submitted in Canvas, where all grading lives.

A capstone you can take to work

From Week 3 you design an AI solution for an organization you know: proposal, aligned prototype, governance and ROI assessment, and an executive pitch. The weekly Capstone Corner keeps it moving so nothing is left for the final weekend.

Designed around a working professional's week

Asynchronous, never absent

No required live meetings: short captioned videos, time-budgeted readings, and labs you can complete anywhere on free-tier tools. Instructor presence is scheduled into every week — a Monday kickoff, active discussion engagement, and feedback within five days of each deadline.

Accessible by design

The platform targets WCAG 2.1 AA throughout: full keyboard navigation with visible focus, screen-reader-labeled controls, transcripts and captions for media, readable text alternatives for every status indicator, and reduced-motion support. AI tutorials work in both voice and keyboard modes.

Enrolled this term? Start with Week 0.

Create your account, meet Anand.AI, set up your AI tool accounts, and walk through the orientation module — so Week 1 starts with building, not setup.