Exam Generative-AI-Leader Topic 2 Question 36 Discussion
Actual exam question for Google's Generative-AI-Leader exam
Question #: 36
Topic #: 2
Question #: 36
Topic #: 2
A company wants to choose a generative AI (gen AI) use case that will be successful and have the most impact. What key factor should they determine first according to Google Cloud-recommended practices?
Suggested Answer: B Vote an answer
According to Google's principles for successful AI adoption, organizations should adopt a "problem-first" approach to ensure their investments deliver measurable value. The strategic choice of a use case should always be motivated by a clear business imperative.
Determining the specific business problems and desired outcomes (B) is the foundational step in any successful Gen AI strategy. Without a well-defined problem (e.g., "reduce customer response time by 30%") and a measurable desired outcome (e.g., "increase customer satisfaction scores"), any AI solution runs the risk of being a technology in search of a purpose, leading to limited adoption or failure to deliver meaningful ROI.
Options A, C, and D are considerations secondary to the initial strategic alignment:
Availability of models (C) only dictates the technical feasibility, not the business value.
Training employees (A) is a resource requirement, not the goal itself.
Model updates (D) is a technical concern related to model longevity, not the primary strategic driver for use case selection.
The priority is always to align the AI solution with high-value business objectives.
(Reference: Google Cloud Generative AI strategy guidelines state: "A fundamental principle for successful AI adoption, including generative AI, is to start with clear business problems and desired outcomes. Without a well-defined problem, the AI solution might not deliver meaningful value, regardless of the technology used. This 'problem-first' approach is crucial for impactful AI strategy.")
Determining the specific business problems and desired outcomes (B) is the foundational step in any successful Gen AI strategy. Without a well-defined problem (e.g., "reduce customer response time by 30%") and a measurable desired outcome (e.g., "increase customer satisfaction scores"), any AI solution runs the risk of being a technology in search of a purpose, leading to limited adoption or failure to deliver meaningful ROI.
Options A, C, and D are considerations secondary to the initial strategic alignment:
Availability of models (C) only dictates the technical feasibility, not the business value.
Training employees (A) is a resource requirement, not the goal itself.
Model updates (D) is a technical concern related to model longevity, not the primary strategic driver for use case selection.
The priority is always to align the AI solution with high-value business objectives.
(Reference: Google Cloud Generative AI strategy guidelines state: "A fundamental principle for successful AI adoption, including generative AI, is to start with clear business problems and desired outcomes. Without a well-defined problem, the AI solution might not deliver meaningful value, regardless of the technology used. This 'problem-first' approach is crucial for impactful AI strategy.")
by Burton at Dec 19, 2025, 08:31 AM
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