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1. How does generative AI reduce effort in data science work?
It automates data cleaning, organization, and preparation, allowing faster analysis and more time for insights.
2. Why is synthetic data important for sensitive industries?
It follows real patterns without exposing personal details, helping protect privacy and meet regulations.
3. Can non-technical teams use generative AI tools for data?
Yes, plain language questions and simple explanations make data easier to use across teams.
4. What role do humans still play in AI-driven data analysis?
Humans review results, check accuracy, manage bias, and guide responsible decision making.
5. How is generative AI changing data science careers?
Focus is shifting from coding to oversight, interpretation, and quality control of AI outputs.
