# Syllabus: AINS6202 AI Strategy for Executives

## Catalog Description

Frames AI strategy, investment, operating models, governance, metrics, talent, and executive decision-making.

## Course Structure

Each week includes readings, a lecture/slide sequence, an executable lab, and an applied deliverable. Students maintain a reproducible project record and submit work through the LMS or GitHub workflow selected by the instructor.

## Weekly Schedule

| Week | Topic | Essential Question | Deliverable |
|------|-------|--------------------|-------------|
| 1 | AI strategy and competitive positioning | How does AI change an organization's strategic options? | Lab notebook + assignment brief |
| 2 | Investment thesis and portfolio design | How should leaders allocate AI investment? | Lab notebook + assignment brief |
| 3 | Capability maturity and operating model | What capabilities must exist to execute strategy? | Lab notebook + assignment brief |
| 4 | Build, buy, partner, or wait | Which sourcing choice fits the strategic context? | Lab notebook + assignment brief |
| 5 | Risk appetite and governance | How do executives set boundaries for AI use? | Lab notebook + assignment brief |
| 6 | Metrics, value realization, and accountability | How will leaders know AI strategy is working? | Lab notebook + assignment brief |
| 7 | Talent, culture, and change | What human systems make AI adoption durable? | Lab notebook + assignment brief |
| 8 | Executive AI strategy brief | What decision should the executive team make now? | Lab notebook + assignment brief |

## Assessment

| Component | Weight |
|-----------|--------|
| Weekly labs and notebooks | 30% |
| Applied assignments | 35% |
| Participation and technical critique | 15% |
| Final synthesis portfolio | 20% |

## Graduate Expectations

Submissions must show technical reasoning, evidence awareness, clear limitations, and responsible use of AI assistance. Code and analysis should be reproducible enough for instructor review.