I’ve been thinking about how much of a Data Scientist’s role can realistically be replaced by AI. A big part of the job is analyzing data and translating results into actionable business recommendations. That already seems very doable with current AI tools — you can feed in your findings, describe the business context, and get reasonable suggestions. Even for things like problem framing: What should we analyze? What metric matters? What defines success? People often say AI struggles here because it doesn’t “own” business goals or understand constraints. But in practice, couldn’t you just provide that context explicitly in the prompt? For example, if I clearly specify: Business objectives Constraints (budget, timeline, resources) Domain context Why wouldn’t AI be able to help frame the problem and suggest what to analyze? So my question is: If a human provides sufficient context, is there anything fundamentally left that AI can’t do in a Data Scientist’s workflow? Curious to hear from people working in industry — especially where AI is already being used heavily. submitted by /u/Excellent_Copy4646
Originally posted by u/Excellent_Copy4646 on r/ArtificialInteligence