Chapter 1 Quiz: The AI-Powered Organization

Chapter 1 Quiz: The AI-Powered Organization

Multiple Choice

Question 1. Which of the following best describes the relationship among AI, machine learning, and deep learning?

(a) They are three different names for the same technology.
(b) AI is a subset of machine learning, which is a subset of deep learning.
(c) Deep learning is a subset of machine learning, which is a subset of AI.
(d) Machine learning is a subset of deep learning, which is a subset of AI.

Question 2. According to the chapter, what percentage of organizations reported adopting AI in at least one business function by 2024 (per McKinsey's annual survey)?

(a) 35 percent
(b) 55 percent
(c) 72 percent
(d) 90 percent

Question 3. A company has launched three AI pilot projects in different departments, hired a small data science team, and purchased enterprise licenses for several AI tools. However, AI initiatives are driven by individual champions rather than a coordinated strategy, and ROI has not been rigorously measured. At which stage of the AI maturity model is this company?

(a) Stage 1: Ad Hoc
(b) Stage 2: Opportunistic
(c) Stage 3: Systematic
(d) Stage 4: Differentiated

Question 4. What distinguishes generative AI from other forms of AI?

(a) Generative AI can process larger datasets than traditional AI.
(b) Generative AI creates new content rather than only analyzing or classifying existing content.
(c) Generative AI does not require training data.
(d) Generative AI is more accurate than other forms of AI.

Question 5. Which of the following was NOT identified in Ravi Mehta's initial assessment of Athena Retail Group?

(a) Customer data is split across four siloed systems with no unified customer ID.
(b) The analytics team consists of two business analysts using Excel and Tableau.
(c) The company has a well-functioning data governance framework but lacks AI-specific policies.
(d) The point-of-sale system is 15 years old and stores data in a proprietary format.

Question 6. The chapter describes two "AI winters." What was the primary cause of the first AI winter (1970s)?

(a) AI systems became too expensive for commercial deployment.
(b) Government regulators banned AI research.
(c) AI failed to deliver on its grandiose early promises, leading to funding cuts.
(d) Deep learning algorithms proved fundamentally flawed.

Question 7. According to the chapter, what was the most significant business impact of the machine learning era (1997-2011)?

(a) AI created enormous value but often under brand names like "analytics" and "personalization" rather than "AI."
(b) Expert systems were deployed across most Fortune 500 companies.
(c) Generative AI tools became available to consumers for the first time.
(d) The first AI regulations were enacted in the European Union.

Question 8. Which of the following is an example of supervised learning?

(a) Grouping customers into segments based on purchasing behavior without predefined categories
(b) Training a model to predict customer churn based on historical examples of customers who did and did not churn
(c) Optimizing warehouse robot navigation through trial-and-error rewards
(d) Generating new product descriptions based on catalog data

Question 9. What is "shadow AI" as described in the chapter?

(a) AI models that operate behind firewalls and are invisible to external auditors
(b) Employees using AI tools without organizational sanction or oversight
(c) AI systems that learn from dark data — unstructured information stored but never analyzed
(d) Competitor AI strategies that are hidden from public view

Question 10. According to the chapter, for every dollar companies spent on AI technology, McKinsey estimated they needed to spend how much on change management, training, and process redesign?

(a) Fifty cents to one dollar
(b) One to two dollars
(c) Three to five dollars
(d) Ten to fifteen dollars

Question 11. Which recurring theme of the textbook is BEST illustrated by the gap between the 90 percent of executives who call AI a "top three priority" and the 26 percent who report significant financial impact?

(a) Human-in-the-Loop
(b) Build vs. Buy
(c) The Hype-Reality Gap
(d) Responsible Innovation

Question 12. The Athena Retail Group's AI Transformation Initiative has a budget of $45 million over three years. This represents approximately what percentage of the company's annual revenue?

(a) 0.5 percent
(b) 1.6 percent
(c) 3.2 percent
(d) 5 percent

Question 13. Which of the following best describes why Professor Okonkwo argues that marketing professionals (like NK) need AI literacy?

(a) Every business professional needs to learn to code machine learning models.
(b) Marketing departments will be the first to be automated by AI.
(c) Business leaders need to evaluate AI solutions, interpret AI outputs, manage technical teams, and make investment decisions — all of which require understanding.
(d) AI tools are replacing traditional marketing techniques entirely.

Question 14. What event is commonly identified as the beginning of the generative AI revolution?

(a) The launch of IBM Watson in 2011
(b) Google DeepMind's AlphaGo defeating Lee Sedol in 2016
(c) The release of ChatGPT in November 2022
(d) The passage of the EU AI Act in 2024

Question 15. According to the chapter, approximately what percentage of large enterprises were at Stage 5 (AI-First) of the maturity model in 2025?

(a) 3 percent
(b) 12 percent
(c) 20 percent
(d) 30 percent

Short Answer

Question 16. In two to three sentences, explain the concept of "pilot purgatory" and why it is a common challenge for organizations at Stage 2 of the AI maturity model.

Question 17. Ravi Mehta summarized his assessment of Athena's readiness in one sentence. Paraphrase that sentence in your own words, and explain why it captures the central challenge of enterprise AI transformation.

Question 18. The chapter introduces three types of machine learning: supervised, unsupervised, and reinforcement learning. Provide one business application for each type that is NOT mentioned in the chapter.

Question 19. Explain the difference between AI inference costs and AI training costs. Why does the chapter describe their recent trajectories as moving in opposite directions, and what is the business implication?

Question 20. The chapter identifies "Data as Strategic Asset" as a recurring theme. In three to four sentences, explain why proprietary data is described as a more durable competitive advantage than algorithms or models.

True or False (with Justification)

For each statement, indicate whether it is true or false and provide a one-sentence justification citing evidence from the chapter.

Question 21. The term "artificial intelligence" was first coined at the Dartmouth Conference in 1956.

Question 22. According to the chapter, the primary reason most AI projects stall or fail is that the underlying algorithms are not sophisticated enough for real-world applications.

Question 23. Athena Retail Group's e-commerce revenue as a percentage of total revenue is below the industry average for specialty retail.

Question 24. The chapter argues that a company at Stage 4 (Differentiated) of the AI maturity model faces no significant business risks related to AI.

Question 25. According to a study cited in the chapter, companies whose senior leadership teams included at least one member with deep AI expertise were 2.4 times more likely to report significant value from AI investments.

Answer key available in Appendix B.