AI for your role

AI for Insights & Research Analysts

Let AI do the gathering and coding so you can spend your time on the insight that reframes a decision.

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The shift

How AI is changing the Insights / Research Analyst role

In 2026, AI compresses the gather-and-summarize half of research — coding open-ended survey responses, synthesizing interviews, compiling competitive scans — from days into minutes. What concentrates in value is designing research that answers the real question, separating genuine signal from noise and bias, and turning findings into a recommendation the business acts on rather than a report it files.

What AI can take off your plate

  • Coding and theming open-ended survey responses
  • Transcribing and summarizing interview sessions
  • Compiling competitive and market scans
  • Drafting first-pass research reports and readouts
  • Generating hypotheses to test with further research

What stays distinctly human

  • Designing research that answers the real question
  • Separating genuine signal from noise and bias
  • Judging when a sample or method can't support a claim
  • Synthesizing into a clear, decision-ready story
  • Making the recommendation and standing behind it
Tools

Five AI tools for Insights & Research Analysts

Claude
Paste dozens of open-ended responses or a long transcript and get themes, tensions, and representative quotes you can verify and refine.
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ChatGPT
Draft a discussion guide, cluster survey verbatims, or turn a pile of findings into a tight executive readout.
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Dovetail
A research repository with AI that tags, themes, and summarizes qualitative data across studies so insights stay findable.
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Perplexity
Runs cited web research for competitive and market scans, with sources you can check rather than trust blindly.
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Notably
An AI-assisted analysis canvas for coding interviews and surveys and clustering them into shareable insight boards.
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Prompts

Five prompts to try today

Paste these into Claude or ChatGPT and replace the bracketed parts with your own details.

1. Theme open-ended responses
Here are open-ended survey responses: [paste]. Identify the main themes, estimate how common each is, pull a representative quote for each, and flag any surprising tension.
2. Design a discussion guide
I'm researching [question] with [audience]. Draft a 30-minute interview guide with open, non-leading questions, plus follow-up probes for the moments that matter most.
3. Pressure-test a finding
Here is a finding I want to present: [finding], based on [method/sample]. Challenge it for sampling bias, leading questions, and over-generalization, and tell me what I can and can't claim.
4. Turn research into a recommendation
Here are my key findings: [paste]. Restructure this around the decision it informs: lead with the recommendation, then the evidence, then the risks and open questions.
5. Synthesize multiple sources
Here are notes from [surveys, interviews, analytics]: [paste]. Triangulate them into one view, noting where sources agree, disagree, and leave gaps.
The playbook

Every AI play for Insights & Research Analysts

Your full AI playbook for your role — updated every week. Tap any card for a step-by-step walkthrough and examples.

✦  New AI plays are added every week — and go straight to subscribers in their morning brief. Skip the scrolling and get yours delivered free. Get my free brief →
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A day in your inbox

This is the kind of brief a Insights / Research Analyst gets, every weekday morning.
Monday morning
✦ Personalized for: Insights / Research Analyst
Data PlaybookAd-hoc data pull
Get answers from a messy CSV without writing a single query

The move for when a stakeholder wants numbers now and you do not want to spin up a notebook. Free tier, plain English in, charts out.

Julius AI FREE  a free tier that analyzes spreadsheets and data in plain English, with charts

1

Go to julius.ai (free account), start a new chat, and upload the raw export the stakeholder sent you, for example the sales_export.csv.

2

Ask it in one line, so it cleans and computes in one pass:

Using [sales_export.csv], group revenue by [region] and [month], drop any rows where [amount] is blank or negative, and show me the top 3 regions by total revenue as a bar chart.
3

Then pressure-test the result before you send it up:

How many rows did you drop and why? Show me 5 example rows you excluded so I can confirm the logic.

You answer a same-day request in minutes with a chart and a clean audit trail, instead of hand-writing SQL against a file nobody has profiled yet.

Your role, all in one place
  
Tools, prompts & tricks
Your full library, one tap away.
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Your playbook
Every entry, building each week.
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How AI is changing your role
Where your work is heading.
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