Chapter 31 Exercises: AI Strategy for the C-Suite

Section A: Strategy Definition and Framing

Exercise 31.1 -- Strategy vs. Aspiration

Evaluate each of the following AI strategy statements. For each, determine whether it is (a) a genuine strategy, (b) a financial target, (c) a technology directive, or (d) a vague aspiration. If it is not a genuine strategy, rewrite it as one using the criteria from the opening scenario: it must specify where to compete, how to win, the enabling role of AI, and how to measure success.

a) "We will be an AI-first company by 2028." b) "Use AI to reduce claims processing time by 60% and become the fastest claims experience in the U.S. property insurance market, measured by customer-reported time-to-resolution." c) "Implement generative AI across all business units." d) "Achieve $50 million in AI-driven cost savings by 2027." e) "Leverage AI and machine learning to deliver best-in-class customer experiences and operational excellence, driving shareholder value."

Exercise 31.2 -- The AI Strategy Canvas

You are the Chief Strategy Officer at a mid-size hospital system (12 hospitals, $4.2 billion in revenue, 22,000 employees). The CEO has asked you to develop an AI strategy.

Complete the full AI Strategy Canvas (all 10 components from Section 31.2) for this organization. For each component, provide specific, realistic content -- not generic placeholders. Your canvas should reflect the unique characteristics of healthcare: regulatory constraints (HIPAA, FDA), clinical workflows, patient safety requirements, physician autonomy, and payer dynamics.

Exercise 31.3 -- Competitive Arena Identification

For each of the following organizations, identify: (a) the competitive arena where AI can create the most significant advantage, (b) the mechanism by which AI creates value in that arena, and (c) the key data assets that would power the AI advantage.

a) A national quick-service restaurant chain (3,200 locations, $6B revenue) b) A mid-tier management consulting firm (2,000 consultants, $800M revenue) c) A regional bank ($18B in assets, 1.2 million retail customers) d) A specialty chemical manufacturer ($2.5B revenue, 400 industrial customers) e) A mid-size university (15,000 students, $500M budget)

Section B: Competitive Dynamics

Exercise 31.4 -- Data Network Effects Assessment

For each of the following AI applications, assess whether data network effects are strong, moderate, or weak. Justify your assessment by evaluating: (a) whether each additional data point meaningfully improves model performance, (b) whether the improvement is visible to users, and (c) whether the data can be easily replicated by competitors.

a) A ride-sharing company's demand prediction and pricing model b) A law firm's contract review AI c) A music streaming service's recommendation engine d) A manufacturing company's predictive maintenance system e) A social media platform's content moderation AI

Exercise 31.5 -- Moat vs. Commodity Analysis

You are advising the board of a $1.2 billion specialty retailer. The company is considering five AI initiatives. For each, determine whether the AI capability would be a competitive moat or a commodity capability. Recommend build, buy, or partner for each, and justify your recommendation.

a) Personalized product recommendations based on purchase history, browsing behavior, and style preferences b) Automated email classification and routing for customer service c) Store-level demand forecasting incorporating local events, weather, and demographics d) Employee scheduling optimization across 180 locations e) Visual search ("find products that look like this photo") integrated into the mobile app

Exercise 31.6 -- First-Mover vs. Fast-Follower Decision

A pharmaceutical company is evaluating three AI opportunities. For each, recommend whether the company should move first or follow fast. Support your recommendation by assessing: data network effects, technology maturity, regulatory uncertainty, and competitive dynamics.

a) AI-powered drug discovery using the company's proprietary molecular database of 2 million compounds b) Using generative AI to automate the writing of regulatory submissions c) Deploying an AI-powered clinical trial matching system for oncology patients

Section C: Portfolio Management

Exercise 31.7 -- Three Horizons Portfolio Design

You are the VP of AI Strategy at a global logistics company ($12B revenue, 45,000 employees, operations in 30 countries). Design an AI portfolio using the Three Horizons model. For each horizon, propose three specific AI initiatives with the following details:

• Initiative name and brief description (one sentence)
• Business value driver (revenue growth, cost reduction, risk reduction, or customer experience)
• Estimated timeline to value
• Key data requirements
• Risk level (low/medium/high)

After designing the portfolio, allocate a hypothetical $30 million annual AI budget across the three horizons. Justify your allocation.

Exercise 31.8 -- Exploration vs. Exploitation Allocation

A consumer packaged goods company ($8B revenue) currently allocates 95% of its AI budget to exploitation projects (demand forecasting, trade promotion optimization, supply chain efficiency) and 5% to exploration. The Chief Digital Officer argues this balance is too conservative.

a) What risks does the current 95/5 allocation create over a 3-5 year horizon? b) What risks would a shift to 60/40 (exploitation/exploration) create? c) Propose an allocation that you believe is appropriate, and design a governance mechanism to manage the transition. d) How would you measure whether the exploration investments are generating value, given that exploration projects may not have clear ROI?

Exercise 31.9 -- Kill, Scale, or Continue

You are chairing the quarterly AI portfolio review at a financial services firm. Five AI pilots have been running for six months. Based on the following status reports, recommend whether each should be killed, scaled to production, or continued as a pilot. Justify each decision.

Section D: Governance and Leadership

Exercise 31.10 -- Board AI Literacy Assessment

You are preparing a board education session on AI. Design a 90-minute agenda that would bring a board of directors (most of whom have limited AI knowledge) to a level of literacy sufficient for effective AI oversight. For each agenda item, specify: the topic, the learning objective, the format (presentation, discussion, exercise, or demo), and the time allocation. Your agenda should be practical, not patronizing.

Exercise 31.11 -- Board-Level AI Risk Assessment

For each of the following AI-related scenarios, identify: (a) the risk category (operational, compliance, reputational, strategic, or cyber), (b) the potential severity (low/medium/high), (c) the board's oversight responsibility, and (d) a specific governance mechanism that would mitigate the risk.

a) The company's AI-powered hiring tool is found to systematically disadvantage candidates from certain demographic groups. b) A competitor launches an AI-powered product that makes the company's core product obsolete within 18 months. c) The company's AI recommendation engine is manipulated by malicious actors to promote counterfeit products. d) New AI regulations in the EU require significant changes to the company's AI systems, with a 12-month compliance deadline. e) The AI team's key talent (3 of 5 senior data scientists) accepts offers from a competitor.

Exercise 31.12 -- CEO AI Communication

Draft a 500-word internal memo from the CEO to all employees announcing the company's AI strategy. The company is a 5,000-person regional bank. The strategy involves deploying AI across customer service (chatbot), loan underwriting (decision support), and fraud detection. The memo should: (a) explain the strategic rationale in plain language, (b) acknowledge workforce concerns honestly, (c) describe specific upskilling commitments, and (d) avoid both hype and false reassurance.

Section E: Operating Model

Exercise 31.13 -- Operating Model Selection

For each of the following organizations, recommend an AI operating model (centralized, embedded, hub-and-spoke, or CoE) and justify your recommendation. Consider the organization's size, AI maturity, business diversity, and talent availability.

a) A $200M SaaS company with 500 employees and 4 data scientists, just beginning its AI journey b) A $15B diversified conglomerate with business units in aerospace, healthcare, and financial services c) A $3B specialty retailer with 500 stores, an e-commerce platform, and a growing AI team of 35 people d) A $50B global bank with AI teams in trading, risk, retail banking, and wealth management totaling 200+ AI professionals

Exercise 31.14 -- AI Center of Excellence Charter

Draft a one-page charter for an AI Center of Excellence at a mid-size manufacturing company ($4B revenue, 15,000 employees). The charter should include: mission statement, scope of responsibilities, services provided to business units, governance authority, staffing plan (roles and approximate headcount), success metrics, and reporting structure.

Section F: Strategic Alignment

Exercise 31.15 -- AI M&A Due Diligence

Your company is considering acquiring an AI startup ($15M revenue, 60 employees, 22 of whom are AI engineers/data scientists). The startup has built a computer vision system for quality inspection in manufacturing. Design an AI-specific due diligence checklist with at least 15 items, organized into categories (technology, data, talent, governance, commercial, risk). For each item, specify what a "green flag" and a "red flag" response would look like.

Exercise 31.16 -- Build-Buy-Partner Decision

A national insurance company ($9B in premiums) is evaluating three approaches to developing an AI-powered claims processing system:

• Option A: Build. Hire a team of 25 AI engineers and data scientists. Build custom models on proprietary claims data. Estimated cost: $12M over 3 years. Time to first production deployment: 18 months.
• Option B: Buy. License a claims AI platform from a specialized vendor. Annual license: $2.5M. Integration cost: $3M. Time to first deployment: 6 months.
• Option C: Partner. Co-develop with a technology partner who contributes AI expertise while the insurer contributes domain knowledge and data. Shared IP ownership. Estimated cost: $8M over 3 years. Time to first deployment: 12 months.

Evaluate each option across five dimensions: competitive differentiation, data leveraging, talent requirements, time-to-value, and long-term strategic flexibility. Provide a recommendation with a clear rationale.

Section G: Integrative Exercises

Exercise 31.17 -- AI Strategy Presentation

Working in a group of 3-4, develop a 15-minute AI strategy presentation for the board of directors of one of the following companies:

a) A national grocery chain ($22B revenue, 900 stores, 120,000 employees) b) A mid-size law firm (500 attorneys, $1.2B revenue, 12 practice areas) c) A regional health insurance company ($6B in premiums, 3 million members)

Your presentation should include: strategic context and competitive dynamics, AI strategic vision and objectives, strategic pillars (3-5), portfolio roadmap (Three Horizons), operating model recommendation, investment profile (3-year), governance framework, and key risks with mitigation strategies. Prepare to answer tough board questions.

Exercise 31.18 -- Strategy Autopsy: Diagnosing Failure

Read the following scenario and identify which strategic pitfalls from Section 31.11 are at play. Then write a 500-word analysis describing what went wrong and what should have been done differently.

A mid-size retailer ($1.8B revenue) launched its AI strategy in 2023 with great fanfare. The CEO announced to investors: "We are going all-in on AI. Within two years, AI will power every aspect of our customer experience." The company hired a Chief AI Officer from Google, invested $25 million in a "Retail AI Lab," and launched 32 AI pilot projects simultaneously. By 2025, the results were disappointing: 28 of 32 pilots were still running (none had been scaled), the Retail AI Lab had produced impressive demos but no production systems, the CAO had resigned citing "organizational resistance," and the board was questioning the entire AI investment.

Exercise 31.19 -- Competitive Response Simulation

You are the CEO of Athena Retail Group. NovaMart -- a digitally native retailer with $200M in venture capital -- has just launched an AI-powered personal shopping experience that is attracting Athena's core demographic (women 25-45, household income $75K-$150K). NovaMart has no physical stores but its digital experience is rated "excellent" by 89% of users. It is growing at 40% year-over-year.

a) Assess the strategic threat that NovaMart poses. Is it a first-mover advantage situation, or can Athena fast-follow? b) How does NovaMart's approach differ from Athena's AI strategy? What are the strengths and weaknesses of each? c) Should Athena accelerate its AI roadmap in response? If so, which strategic pillar should be prioritized, and what are the risks of acceleration? d) Draft a one-page competitive response brief for the Athena board.

Exercise 31.20 -- The AI Strategy Document

Using the template from Section 31.12, create a complete AI strategy document outline for an organization you know well (your employer, an internship, or a company you have researched). For each of the 10 sections, write 2-3 bullet points of specific content -- not generic placeholders. Then identify the three sections where you have the least clarity. What information would you need to fill those gaps, and who in the organization would you consult?

Suggested approach: Exercises 31.1-31.3 test conceptual understanding and should be completed individually. Exercises 31.4-31.9 involve analytical frameworks and benefit from small-group discussion. Exercises 31.10-31.16 address governance and organizational design. Exercises 31.17-31.20 are integrative and are best completed in groups simulating executive teams.