Phase 1: Executive AI Foundation
Goal: Build the AI fluency an executive needs to make confident strategy, investment, and governance decisions — without becoming an engineer.
| Attribute | Detail |
|---|---|
| Duration | 6 weeks |
| Time commitment | 6-8 hours/week |
| Cost | $0 (all resources below are free or free-to-audit) |
| Capstone deliverable | AI Opportunity Thesis — a 5-page executive brief mapping where AI creates commercial value in your business |
| Career signal | "Can translate AI capability into business strategy" — the #1 gap boards report |
Why This Phase Matters (Market Alignment)
McKinsey's research shows the top predictor of AI success is C-level ownership, not technical depth. Executives who can connect AI to enterprise strategy are scarce and highly valued. This phase builds exactly that muscle — positioning you for roles like Chief Commercial Officer, VP of Growth/Strategy, Chief Strategy Officer, and AI Transformation Lead in industrial and capital-intensive sectors.
Learning Objectives
By the end of Phase 1 you will be able to:
- Explain what AI, machine learning, generative AI, and agents can and cannot do — in business terms
- Distinguish high-ROI AI use cases from hype in a capital-intensive industrial context
- Read a data/architecture proposal well enough to challenge assumptions and cost
- Apply a basic AI risk lens (NIST AI RMF language) to any initiative
- Build and defend an AI opportunity thesis to a CEO or Board
Week-by-Week Structure
Week 1 — AI Literacy for Leaders
- Learn: Microsoft — Transform your business with AI (4 modules, ~2.5 hrs)
- Learn: Elements of AI — Chapters 1-2 (what AI is / isn't)
- Do: Draft a one-page personal AI glossary in plain language (terms: model, LLM, agent, RAG, hallucination, grounding, inference cost)
Week 2 — AI as a Business Strategy
- Learn: Andrew Ng — AI for Everyone (Weeks 1-2, free audit)
- Learn: Wharton — AI for Business, Course 1 AI Fundamentals for Non-Data Scientists (free audit)
- Do: List 10 candidate AI use cases across your commercial cycle (prospecting → qualification → proposal → negotiation → account growth)
Week 3 — Generative & Agentic AI (Hands-On)
- Learn: Google Prompting Essentials (5-step framework, ~10 hrs)
- Learn: Anthropic Academy — intro to working with Claude
- Do: Use a GenAI tool to draft a strategic account summary; document what worked, what failed, and where a human was essential
Week 4 — Data, Architecture & Constraints
- Learn: Andrew Ng — AI for Everyone, Weeks 3-4 (building AI projects, data)
- Learn: AI-900 study path (optional, non-coding baseline)
- Do: Write a half-page "data readiness" assessment of your own CRM/pipeline data — what's clean, what's missing, what blocks AI use
Week 5 — AI Economics & ROI
- Learn: Wharton — AI for Business, AI Applications in Marketing and Finance (free audit)
- Learn: Review McKinsey QuantumBlack insights on AI value (mckinsey.com)
- Do: Build a simple value model for your top use case (time saved × loaded cost, or conversion lift × average deal value)
Week 6 — Responsible AI Foundations + Capstone
- Learn: NIST AI RMF — read the framework's four functions (Govern, Map, Measure, Manage)
- Learn: Microsoft "Embrace responsible AI principles" module (within the Week 1 path)
- Do: Complete the capstone — AI Opportunity Thesis (see below)
Capstone Deliverable — AI Opportunity Thesis
A 5-page executive brief containing:
- Business context — your market, growth pressures, and commercial cycle
- Opportunity map — 3-5 prioritized AI use cases (value vs. effort vs. risk)
- Value hypothesis — a rough dollar/velocity model for the top use case
- Risk lens — key risks framed in NIST AI RMF language
- Recommendation — what to pilot first, and why
This becomes the input to Phase 2's account playbook and the First 90 Days plan. It's also a portfolio piece you can discuss in executive interviews.
Skills → Market Keywords (for LinkedIn/CV)
AI Strategy · AI Business Case Development · Responsible AI (NIST AI RMF) · Generative AI Literacy · AI ROI Modeling · Executive AI Decision-Making
Phase 1 Checkpoint (Gate to Phase 2)
You're ready to advance when you can:
- Explain GenAI vs. agents to a non-technical peer in 2 minutes
- Name your top 3 AI use cases with a value and risk rationale
- Complete the AI Opportunity Thesis capstone
- (Optional) Pass AI-900 or earn an Elements of AI / Google certificate
All resources are verified with primary-source links in Sources & Verification.