Bring us a real business problem — we’ll build an AI solution with you.

The MS-AIB Capstone pairs sponsor organizations with student teams to deliver applied, business-ready AI outcomes (LLM/agentic workflows, analytics, automation, evaluation, and governance) over a semester-long engagement.

Agentic AI & workflow design LLM apps & copilots Predictive modeling Responsible / mindful AI Data strategy & governance
Engagement
1 semester
Structured cadence with weekly touchpoints (typical).
Deliverables
Prototype + report
Working demo, documentation, and sponsor handoff.
Best fit
Real data + owner
A committed point-of-contact + accessible data/systems.
Modes
Onsite / Online
Teams operate hybrid-friendly with sponsor preference.

Why sponsor an MS-AIB capstone?

Get an applied AI build, a business case, and a pipeline to top talent — with faculty oversight and structured milestones.

Business-ready outcomes

  • Prototype / demo (LLM app, agent workflow, model, dashboard)
  • Feasibility + ROI narrative
  • Deployment considerations (data, security, governance)

Low-lift for sponsors

  • Dedicated point-of-contact + scoped requirements
  • Weekly/biweekly sponsor sync (you choose)
  • Clear artifacts for handoff and future build

Talent & brand impact

  • Early access to skilled candidates
  • Visibility on campus and in program showcases
  • Support mindful / responsible AI practice

Good project fits

We can support a range of AI-in-business initiatives. The best projects have a clear owner, clear business question, and a feasible data path.

Examples (adapt as needed)

  • Agentic process automation: multi-step workflows (intake → triage → draft → review → route)
  • LLM copilots: search + summarize + cite internal knowledge (policies, tickets, SOPs)
  • Analytics & forecasting: demand, churn, capacity, risk, pricing, anomaly detection
  • Customer/employee insights: sentiment, topic modeling, VOC, call/email mining
  • Evaluation: LLM quality metrics, guardrails, bias/fairness checks, red teaming
  • Data strategy: data product roadmap, governance, KPI design, experimentation plans

What we typically need from sponsors

  • Point-of-contact (decision-making + availability)
  • Data access plan (sample data early; secure access later)
  • Constraints (privacy, compliance, tools, cloud restrictions)
  • Success criteria (what “good” looks like)
Tip: If you’re unsure about feasibility, submit anyway — we can help scope it into a capstone-sized project.

Timeline & process

A simple, repeatable workflow to keep projects scoped and moving.

1

Submit idea

High-level problem, context, and sponsor contact info.

2

Scope & feasibility

We align on goals, constraints, data, and deliverables.

3

Team match

Student team assigned; kickoff meeting + cadence set.

4

Build & handoff

Prototype, documentation, final showcase, and transition plan.

Milestones (typical)

  • Week 1–2: discovery + scoping
  • Week 3–5: solution design + data pipeline
  • Week 6–9: build + iterate + evaluation
  • Week 10+: final demo + handoff package

Handoff package (typical)

  • Demo / prototype (code or tool workflow)
  • Technical notes + architecture
  • Business narrative (value, costs, risks)
  • Next steps roadmap

Submit a capstone project idea

Fill out the form below. If you already have a formal intake form (e.g., Google Form), link it and we’ll route it.

This “Send (Email)” button opens your email client with a pre-filled draft to: capstone-contact@asu.edu (placeholder). Update the email address and Google Form link in the script below.

Contact

  • Program: MS-AIB (W. P. Carey School of Business, ASU)
  • Faculty lead: Dr. Sang-Pil Han (placeholder text — edit as desired)
  • Email: capstone-contact@asu.edu (replace)
  • Official Program Page: wpcarey.asu.edu → MS-AIB

Downloads

Want this to auto-save submissions to a spreadsheet? Use Google Forms (fastest) or Formspree/Make.com/Zapier with a webhook.

FAQ

Common questions from sponsor organizations.

Do we need to share sensitive data?

No. Many projects can start with de-identified samples or synthetic data. We can scope to constraints and discuss guardrails early.

What tools do teams use?

Depends on sponsor constraints. Common options include Python, notebooks, cloud services, enterprise LLM platforms, and automation tools. We can adapt to your environment.

How much time is required from the sponsor?

Typically 30–60 minutes per week or every other week, plus quick async feedback. The point-of-contact’s responsiveness matters more than meeting length.

What do we get at the end?

A working demo/prototype, documentation, a business case narrative, and a transition plan. Exact artifacts are scoped at kickoff.