AI Strategy & Implementation Flashcards
7 cards from real CAIC practice questions. Tap to flip, then mark Knew It or Still Learning โ missed cards come back until you master them.
Read the first 7 AI Strategy & Implementation flashcards as text
When building an AI implementation roadmap, which factor is most critical to assess FIRST?
Answer: Evaluating data readiness and quality
Data readiness and quality must be evaluated first because AI models are only as good as the data they are trained on.
A company wants to implement AI but faces resistance from employees who fear job loss. The BEST strategic response is to:
Answer: Frame AI as an augmentation tool and invest in reskilling programs
Positioning AI as augmentation rather than replacement, paired with reskilling, reduces resistance and builds a more AI-capable workforce.
Which metric best measures the business impact of an AI-powered customer service chatbot?
Answer: Reduction in average handling time and cost per resolved ticket
Business impact is measured by operational outcomes such as reduced handling time and cost savings, not technical implementation details.
An organization's AI strategy should align with its overall business strategy primarily to:
Answer: Ensure AI investments generate measurable business outcomes
AI initiatives must be tied to business outcomes to justify investment and ensure they solve real organizational problems.
A 'proof of concept' (PoC) in AI implementation is best described as:
Answer: A small-scale experiment to validate technical feasibility and business value before full investment
A PoC tests whether an AI solution can work at small scale before committing to full-scale implementation resources.
Which of the following is an example of a 'build vs. buy' decision in AI strategy?
Answer: Deciding whether to develop a custom recommendation engine or license a third-party solution
The build vs. buy decision involves weighing the cost and customization of in-house AI development against the speed and ease of purchasing an existing solution.
What is the primary purpose of an AI Center of Excellence (CoE) within an organization?
Answer: To centralize AI expertise, standards, and governance while enabling scaling across the enterprise
An AI CoE consolidates expertise and best practices to accelerate adoption and ensure consistent, responsible AI deployment across the organization.