I learned how to do data analysis with AI for you. Yes, I took 11 courses so you don’t have to. In this video, I break down when it actually makes sense to use AI for analysis using the ACHIEVE framework: aiding human coordination, cutting tedious tasks, providing a safety net (because humans hallucinate too), inspiring better problem solving, and enabling great ideas to scale faster. Think: summarizing messy meeting transcripts, cleaning workshop signup data, checking receipts against policy docs, and even generating personalized cheat sheets for every attendee. Then I show you how I approach AI-assisted analysis using the DIG framework: Describe → Introspect → Goal-set. The “Describe” step is non-negotiable—list columns, sample rows, catch missing values (hello, NaNs), and confirm the model is parsing correctly so you don’t propagate errors. “Introspect” is where I ask the AI for interesting questions and I stay skeptical, correcting it when it invents things (like extra currencies that don’t exist). Finally, “Goal-set” forces clarity: a LinkedIn report is a totally different output than a boss-ready memo. I also cover traceability + replication (README + one Python script per chart), plus fun power moves like analyzing zip files, manipulating video frames, and turning a chat workflow into a runnable Python program—or even a dashboard or full app using vibe coding.