Unit 2: Design Thinking with AI and its Relevance in Business - Practice Quiz

1 Which stage of the innovation life cycle can AI tools support by rapidly analyzing large volumes of customer data to uncover needs?

2 How do AI tools primarily speed up the prototyping phase of innovation?

3 Which of the following is a benefit of using AI in the innovation life cycle?

4 In the innovation life cycle, AI-based sentiment analysis is most useful for which activity?

5 Design Thinking combined with AI mainly aims to create solutions that are:

6 How does AI enhance the 'Empathize' stage of Design Thinking?

7 Which is a key impact of using AI in Design Thinking for business innovation?

8 In Design Thinking with AI, humans and AI ideally work in a relationship that is:

9 In the banking domain, AI chatbots are commonly used to:

10 In retail, AI-based recommendation systems help by:

11 How does AI help FMCG companies in demand forecasting?

12 In the Food & Beverage industry, AI can help improve which of the following?

13 In sales and distribution, AI is often used to optimize:

14 AI-based fraud detection is most commonly associated with which domain?

15 Which of the following is an important ethical concern in AI innovation?

16 Protecting user data in AI systems relates most directly to which value?

17 What does 'transparency' mean in the context of ethical AI?

18 Who should ultimately remain accountable for decisions made using AI systems?

19 What is a 'prompt' in the context of AI language models?

20 Prompt engineering mainly focuses on:

21 During the empathize phase of an innovation life cycle, a team wants to understand customer sentiment from thousands of online reviews. Which AI capability is most directly applicable?

22 A product team uses generative AI to rapidly produce hundreds of design variations before selecting a few for testing. This most directly accelerates which stage of the innovation life cycle?

23 Which combination correctly matches an AI tool type to its innovation life cycle contribution?

24 A startup automates the collection and clustering of raw research data to spot unmet needs. What is the primary benefit AI provides here?

25 How does integrating AI into Design Thinking most fundamentally change the traditional process?

26 A company claims AI-augmented Design Thinking improves innovation. Which statement reflects a correct understanding of AI's role?

27 Which scenario best illustrates AI enhancing the define phase of Design Thinking?

28 In balancing AI and human input during innovation, which approach is generally considered best practice?

29 A bank uses AI to analyze transaction patterns and flag unusual activity in real time. This is a classic application of AI for:

30 An FMCG company wants to predict which new snack flavor will succeed before a full launch. Which AI approach is most suitable?

31 A retail chain personalizes each shopper's online homepage based on browsing history. Which AI technique underlies this?

32 A food-delivery company uses AI to estimate accurate delivery times and optimize driver routes. This primarily improves:

33 In sales & distribution, an AI system recommends optimal stock levels for each warehouse based on demand forecasts. This helps most directly to:

34 A beverage brand analyzes social media images to spot emerging drink trends. Which AI capability is central to this task?

35 A loan-approval AI is found to reject applicants from certain neighborhoods at higher rates. This is an example of which ethical concern?

36 Why is transparency considered a key ethical value in AI innovation?

37 A company collects user data for one purpose but reuses it to train an unrelated AI model without consent. Which principle is violated?

38 Which practice best supports accountability in an AI-driven business decision?

39 Which of the following prompts is likely to produce the most useful and targeted output from a large language model?

40 In prompt engineering, providing a few examples of the desired input-output format within the prompt is known as:

41 A product team uses AI across the innovation life cycle. During the ideation phase they rely on generative models, while in the validation phase they use predictive analytics. Which statement best explains why using generative AI for validation instead of ideation would be a methodological error?

42 An innovation manager maps AI tools to the phases Empathize → Define → Ideate → Prototype → Test. She wants AI to reduce the risk of solving the wrong problem. At which phase does AI most directly mitigate this specific risk, and how?

43 A bank integrates AI into its Design Thinking process. Critics warn of an automation paradox: the more the team trusts AI-generated insights, the more they risk a specific failure. What is this failure most precisely?

44 In human-centered innovation, AI is best framed as augmenting rather than replacing the designer. Which scenario represents a misapplication that undermines the human-centered principle?

45 A retailer deploys an AI recommendation engine that maximizes short-term click-through. Sales rise, but repeat-purchase rate falls over two quarters. From a Design Thinking lens, what is the most likely root cause?

46 An FMCG company uses AI to analyze social sentiment for new flavor development. Two competing signals emerge: high volume of neutral mentions versus low volume of intensely positive mentions. Which interpretation best supports a defensible innovation decision?

47 A bank's AI loan-approval model shows strong overall accuracy but is challenged for disparate impact. Which analysis correctly distinguishes accuracy from fairness here?

48 In Sales & Distribution, an AI demand-forecasting model performs well historically but fails badly during a sudden market shock. This failure is best described as a limitation of which kind?

49 A Food & Beverage chain uses AI to personalize menus per outlet. Outlet A's AI suggests dropping a low-margin item, but store staff report it drives foot traffic for higher-margin combos. What does this reveal about AI-driven decisions?

50 A team debates whether an AI feature is ethical. One member argues it is fine because it is legal and profitable. Why is this reasoning insufficient from an ethics-in-innovation standpoint?

51 An AI system is highly accurate but opaque (a 'black box'). In a high-stakes domain like healthcare triage, why might a slightly less accurate but interpretable model be the more ethical choice?

52 A company collects user data 'to improve the product' via broad consent. Which principle is most directly at risk, and why?

53 Consider a feedback loop: an AI hiring tool trained on past hires favors candidates resembling current employees. Deployed, it hires similar people, whose data then retrains the model. What is the ethical danger?

54 A user gets vague answers from an LLM. Which prompt modification is most likely to improve factual grounding rather than just fluency?

55 Two prompts request the same classification task. Prompt X gives the instruction only; Prompt Y gives the instruction plus three labeled examples. Prompt Y performs better. What technique does Y illustrate and why does it help?

56 An engineer notices that adding 'think step by step' improves an LLM's performance on multi-step reasoning tasks. What is the most accurate explanation of this effect?

57 A prompt asks an LLM for a legal citation and it returns a confident but nonexistent case. This is a hallucination. Which prompt-engineering strategy most directly reduces this risk?

58 A team wants AI to accelerate divergent thinking early and convergent thinking later. Which pairing of AI capabilities correctly matches these two modes?

59 A startup claims AI lets them 'skip the empathize phase' because models already contain human data. What is the strongest critique of this claim?

60 A company must choose between two AI models: Model A slightly higher accuracy but trained on scraped data of uncertain provenance; Model B slightly lower accuracy but with fully documented, consented data. Which factor makes Model B the more defensible ethical choice despite lower accuracy?