These are RAG questions of the kind Accenture actually asks — the patterns that keep coming back in Accenture's AI project interviews, where what matters is applying RAG sensibly for clients rather than research depth. Treat this page as a mock interview: say every answer out loud before revealing it. If one surprises you, the lesson behind it is linked at the bottom.
Accenture RAG concept questions
Walk through how you would design a RAG solution for a client with 50,000 documents across five departments, where employees may only see their own department's content.
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The client says the bot 'gives wrong answers'. How do you investigate systematically?
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When would you recommend agentic RAG over classic RAG to a client, and what would you warn them about?
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Accenture RAG applied & hands-on questions
The client wants a RAG assistant live in four weeks over 2,000 policy documents. Define what ships, what is deferred, and the two things you refuse to cut.
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How to use this page: Accenture rarely asks something you've never seen — they ask a standard RAG concept and then push one level deeper ("why?", "what would you do if..."). Master the concept in the RAG course lessons, and the follow-up stops being scary.
Keep practising: What Is RAG?, Chunking, Retrieval Techniques and Evaluating RAG cover what most Accenture RAG rounds test — and the Accenture exam guide covers the rest of their selection process.