Deep Research
Deep Research
What is deep research?
- AI researches multiple sources autonomously, then writes the report
- A multi-step research feature with sources and citations
- Hallucinations remain a risk, so always check the original sources
What deep research really changes is not the time research takes but the order of the work. It used to be that a staffer changed search terms twenty times to gather material, then read it, exhausted, in whatever time was left. With deep research, the work starts where collection and a first summary are already done, so the human job shifts toward reading, selecting, and challenging. The bottleneck in research moves from “finding” to “filtering.”
It is not the same as a regular chatbot answering with web search. A typical search answer runs one or two searches and finishes in seconds. Deep research runs for roughly 5 to 30 minutes, opens dozens of pages, and corrects its own research direction along the way. That is why even paid plans often cap monthly usage, so it is not a feature to throw at every question. One more boundary: deep research only sees the public web. To have it answer from internal HR data or past proposals, you need a separate RAG environment connected to your company documents.
Output quality depends on how specific the question is. A prompt like “tell me about the EV battery market” returns an encyclopedia-level summary. Pin down the period (last 18 months), scope (Korean listed companies), source tier (regulatory filings and institutional statistics first), and output format (a 5-row table), and the density changes dramatically. Specifying the research scope and source tier is, in effect, research design. The 30 seconds you spend answering the AI’s clarifying questions before it runs set the direction for 30 minutes of research.
The most common mistake in practice is assuming that “it has sources, so it’s true.” Even with links attached, the original often doesn’t contain the figure, and competitor press releases and personal blogs are frequently cited as if they were primary sources. For information that isn’t public, such as private-company revenue or internal org charts, it fills the gap with plausible estimates. If those go into a proposal unchecked and a client executive asks, “Where does this number come from?”, trust collapses on the spot. At the very least, open the original links and verify the three or four key figures that go into the report before moving on.
John KimInstructor John Kim, author of B2B Marketing Design and CEO of Nanum Consulting
Seolyeong ParkGenerative AI and AX training specialist with 17 years of hands-on experience and 200+ lectures, helping non-technical staff put AI to work right away“Deep research” went mainstream in 2024–2025, when Google Gemini and OpenAI ChatGPT each launched a feature of the same name. What they share: reasoning models, real-time web search, and agentic tool use combined to run multi-step research autonomously.
Consider a hypothetical case. A training company is proposing a team-leader leadership program to Company A, a battery-component manufacturer with 900 employees. Four days remain until the proposal deadline, the client’s industry is unfamiliar, and the company knows nothing about its recent reorganization. In the past, two consultants would have spent three full days on research alone.
- Kim, a senior manager on the proposal team, told deep research to summarize “Company A’s business structure, reorganization, three competitors, and training-related issues, using only filings and trade media from the last 18 months, with source links.”
- After 27 minutes of moving between filings and industry media, the AI returned a nine-page A4 draft with six sections and 41 cited sources.
- When Kim opened the citation links one by one, the passage about “three overseas subsidiaries” turned out to say two in the original, and one revenue estimate had no supporting page linked at all.
- In the review meeting, the CEO said, “This is our hypothesis, not fact,” and told the team to remove all four unverified figures. Only the verified reorganization content was condensed into a one-page proposal.
- Cutting prep research from three days to half a day freed up time for two interviews with client team leads. Those interviews proved decisive and led to an annual contract for 12 courses.