A concrete example
I ask it to 'compare the 3 best CRMs for small businesses in France.' Deep Research reads 30 sources, synthesizes them, and gives me a report.
Why it matters
It's the most powerful form of AI research available. ChatGPT, Perplexity, and Claude all offer a version.
You see it in ChatGPT, Gemini, the OpenAI API, curation agents, and in-depth research workflows.
Don't mix it up with
Agentic workflow: An agentic workflow is a sequence of steps where the AI plans, uses tools, checks its work, and keeps going until it hits the result.
RAG: RAG lets an AI answer using documents pulled up at the moment you ask the question.
Common mistakes
- Using it for questions where a normal search would do.
- Thinking Deep Research guarantees accuracy (it still hallucinates).
- Forgetting to check the cited sources (sometimes made up).
Quick checklist
- First I check whether the word names a concept, a tool, a risk, or a metric.
- I tie it to a concrete case: I ask it to 'compare the 3 best CRMs for small businesses in France.' Deep Research reads 30 sources, synthesizes them, and gives me a report.
- I keep the main trap in mind: Using it for questions where a normal search would do.
Quick questions
What is Deep Research in AI?
Deep Research runs a long search, cites its sources, and hands back a structured report.
Where will I run into Deep Research?
You see it in ChatGPT, Gemini, the OpenAI API, curation agents, and in-depth research workflows.
Which word should I read next?
Start with Agentic workflow, RAG, Web Search tool.