Research with ChatGPT
Use search and deep research to find, analyze, and synthesize information from across the web.
ChatGPT can be a helpful research partner because it quickly brings together information from many sources, making it easier to explore ideas, spot patterns, and understand complex topics. By reasoning through context, citing sources, and producing clear, structured summaries, it helps turn open questions into well-defined insights.
There are two different ways to search the public internet with ChatGPT—search and deep research. Below is an explanation of both, and when to use each.
ChatGPT search allows ChatGPT to pull in the latest information from the internet directly into your conversations. This means you can go beyond ChatGPT’s built-in training knowledge and get up-to-date answers on things like current events, market trends, competitor activity, or niche details not included in its training data.
Instead of toggling between multiple browser tabs and summarizing information yourself, search brings those updates directly into ChatGPT, streamlining your research and saving you time. It also makes it easy to combine fresh web data with the reasoning and summarization power of ChatGPT models.
Open a new chat in ChatGPT.
Ask a question that requires current or detailed information (e.g., “What are the top three AI trends in healthcare in 2025?”), or click Web Search from your tools menu.
Look for the small globe icon 🌐 next to the model’s response—this indicates that search was used.
Click the citation links in the response to review the original sources.
Follow-up with clarifying prompts, like “Summarize this in 3 bullet points for executives” or “Turn this into a customer-facing email draft.”
Citations: Always review linked sources before making decisions, since search results reflect what’s available on the web.
Scope: Search won’t replace specialized databases (e.g., subscription research tools or proprietary data).
Admin settings: In enterprise environments, Workspace Owners may choose to enable or disable search.
Deep research in ChatGPT uses reasoning to quickly gather, summarize, and interpret extensive information from across the web, helping you answer complex questions more thoroughly than a standard web search.
Every output is designed to be documented, with clear citations to sources, making it easy to verify and reference the information. Deep research is also particularly effective at finding niche, non-intuitive information that would otherwise require reviewing many sources.
Unlike a traditional web search, deep research is agentic, meaning that it actively plans and carries out a multi-step research process—searching, evaluating sources, refining queries, and synthesizing findings—rather than simply returning a list of links.
1. Open ChatGPT and select deep research from your tools menu
2. Ask a clear and detailed prompt. Include your topic, goal, timeframe, and key details. If deep research needs more context, it will automatically ask follow up questions.
I’m researching [topic] for [audience/decision/meeting]. Provide a report including recent key opportunities and risks, and 3-5 actionable insights.
3. Review your report
Deep research may run for 5–30 minutes while it explores the web. You’ll get a notification when your report is ready.
Ask follow-up questions or request further analysis, and deep research will refine the output as needed.
These features sound similar, but are best for different use cases. Below is a quick comparison of the two features:
Otsing | Süvauuring | |
|---|---|---|
Eesmärk | Leida veebist või ühendatud allikatest kiiresti konkreetseid fakte, dokumente või värsket teavet. | Teha mitmeetapilist põhjalikku analüüsi keerukate või mitmeti tõlgendatavate küsimuste kohta, mis nõuavad arutlust ja eri allikatest pärit teabe sünteesimist. |
Tüüpiline kasutusjuht | Leida värske pressiteade, toote tehniliste andmete leht, uudisartikkel või üksik andmepunkt (nt „Kui palju pealtvaatajaid oli eelmise aasta suveolümpiamängudel?“). | Uurida laiemaid küsimusi, näiteks „Millised tegurid mõjutavad suurte rahvusvaheliste spordiürituste külastatavust?“ või „Kuidas valmistuvad eri riigid olümpiamängude korraldamiseks?“ |
Väljundi põhjalikkus | Annab lühikesi tulemusi, otseseid vastuseid või linke – sarnaselt nutika veebiotsinguga. | Koostab põhjalikke, tõenditel põhinevaid kokkuvõtteid, mis sisaldavad sageli allikaviiteid, poolt- ja vastuargumente ning arutluskäiku. |
Kiirus | Kiire – tavaliselt mõni sekund. | Aeglasem – mitmeetapilise arutluse tõttu võib kuluda mitu minutit või kauem. |
Teabe värskus | Eelistab uusimat kättesaadavat teavet; sobib hästi värskete uudiste või kiiresti muutuvate andmete leidmiseks. | Kasutab vajaduse korral värskeid allikaid, kuid keskendub konteksti mõistmisele, mitte ainult teabe uudsusele. |
Küsimuse keerukus | Sobib kõige paremini selgelt piiritletud ja konkreetsete päringute jaoks. | Sobib kõige paremini avatud, uurimuslike või strateegiliste küsimuste jaoks, millel pole üht õiget vastust. |
