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AI Consultant Research-to-Report Workflow

Consultants need a reliable path from messy research and meeting notes to a client-ready report without losing assumptions, evidence, or next actions.

Quick verdict

Use this as a repeatable operating workflow, then verify tools, permissions, and data handling before rollout.

Data freshness

This record was last checked on 17/05/2026.

Tools needed

  • Claude
  • ChatGPT
  • Notion AI
  • Fireflies.ai
  • Airtable AI

Recommended workflow

Consultants need a reliable path from messy research and meeting notes to a client-ready report without losing assumptions, evidence, or next actions.

  1. 1. Centralise source material

    Collect call notes, documents, links, interview findings, and assumptions before asking AI to draft conclusions.

  2. 2. Summarise and tag evidence

    Use AI to group findings by theme, confidence, source, and client impact.

  3. 3. Draft the report structure

    Generate an outline with executive summary, findings, recommendations, risks, and implementation steps.

  4. 4. Review claims and hand off actions

    Check every claim against source material, then turn recommendations into owners, deadlines, and next steps.

Act as a consulting analyst. Summarise these notes into findings, evidence, assumptions, risks, recommendations, and open questions. Do not invent facts or cite sources that are not provided.

Template downloads

Consulting report outline

Download handling is staged for the MVP; connect this to a file or email gate later.

Evidence and assumption log

Download handling is staged for the MVP; connect this to a file or email gate later.

Prompt examples

Act as a consulting analyst. Summarise these notes into findings, evidence, assumptions, risks, recommendations, and open questions. Do not invent facts or cite sources that are not provided.

Methodology

Workflow pages should be practical enough to execute: problem, tools, steps, prompts, templates, mistakes to avoid, and related profession/tool pages.

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