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How I Use Generative AI as a Business Analyst

Generative AI can accelerate exploration and documentation, but it cannot supply the business context, accountability, or validation that analysis requires.

  • Generative AI
  • Requirements Analysis
  • Documentation
  • LLM Evaluation

Generative AI is most useful to me as a productivity and analytical aid. It can help explore an unfamiliar domain, organize a draft, compare approaches, or identify questions that deserve further investigation. It does not replace the work of understanding a business.

Research and exploration

AI can help turn a broad research topic into a more structured starting point. This is useful when preparing questions, considering process patterns, or exploring alternative ways to frame a problem.

Requirements and documentation support

It can assist with early drafts of user stories, acceptance criteria, documentation structures, or requirement summaries. Those outputs must be reviewed against the actual business context and the team’s agreed terminology.

Feature validation and LLM evaluation

Using AI well includes evaluating response quality, accuracy, and suitability for a specific use case. A plausible answer is not automatically a reliable one. Validation remains essential.

Human-led decisions

Business stakeholders and delivery teams provide the context, accountability, and judgment that tools do not have. AI can help make the analytical process more efficient; it should not make the final decision in isolation.