I went straight into use cases and kind of skipped the 'should we even do this' part, which I think hurt me.
Start by clarifying the business goal and the specific problem generative AI would solve, then evaluate feasibility, value, and risks through a structured lens. Emphasize that technology should only be adopted if it creates measurable business impact and aligns with strategic priorities.
Pro tip: Frame your answer around business outcomes, not technology features—show that you can say 'no' to GenAI if it doesn't make sense, which demonstrates strategic maturity.
Identify the specific pain point or opportunity (e.g., reducing design time, improving customer support) and articulate how GenAI could address it. Ensure the problem is worth solving and aligns with company strategy.
Evaluate whether GenAI can reliably solve the problem given data availability, model capabilities, and integration constraints. Consider build vs. buy and the maturity of the technology for the use case.
Estimate potential impact on key metrics (e.g., cost savings, revenue growth, customer satisfaction) and compare against investment. Use a simple ROI or value framework to prioritize.
Identify risks such as data privacy, bias, safety, and regulatory compliance, especially in automotive. Weigh these against benefits and define mitigation strategies.
Propose a small-scale pilot or proof of concept to test assumptions, measure outcomes, and decide whether to scale, pivot, or stop.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.