These are GenAI questions of the kind Accenture actually asks — the patterns that keep coming back in Accenture's GenAI and AI-project interview rounds, where the focus is on applying LLMs sensibly for clients rather than research depth. My advice: treat this page as a mock interview. Say every answer out loud before revealing it — GenAI rounds are conversations, not written tests. If an answer surprises you, the lesson behind it is linked at the bottom.
Accenture GenAI concept questions
A client wants a chatbot that answers employee questions from internal policy documents. Walk through your end-to-end solution approach as you would in a client discussion.
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Zero-shot, few-shot, RAG, fine-tuning — arrange them as an escalation ladder for adapting an LLM to a task, with the trigger for each step up.
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Your client-facing bot occasionally states wrong policy details very confidently. The client is alarmed. What do you tell them, and what is your fix plan?
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Accenture GenAI applied & hands-on questions
Design the guardrail list for a retail-banking customer chatbot: give 3 input-side guardrails, 3 output-side guardrails, and the single rule you'd call non-negotiable.
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How to use this page: Accenture rarely asks a question you've never seen — they ask standard GenAI concepts and then push one level deeper ("why?", "what would you do if..."). Master the concept in the GenAI course lessons, and the follow-up stops being scary.
Keep practising: How LLMs Work, Prompting Basics, RAG and Fine-tuning vs RAG cover what most Accenture GenAI rounds test — and the Accenture exam guide covers the rest of their selection process.