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:
Căutare | Cercetare aprofundată | |
|---|---|---|
Scop | Găsește rapid date concrete, documente sau informații recente de pe web ori din surse conectate. | Realizează analize aprofundate, în mai multe etape, ale unor întrebări complexe sau ambigue care necesită raţionament și sintetizarea informațiilor din mai multe surse. |
Utilizare tipică | Găsirea unui comunicat de presă recent, a fișei tehnice a unui produs, a unui articol de știri sau a unei singure date concrete (de exemplu, „Câți spectatori au fost la Jocurile Olimpice de vară de anul trecut?”). | Explorarea unor întrebări mai ample, precum „Ce factori influențează numărul de spectatori la marile evenimente sportive internaționale?” sau „Cum se pregătesc diferite țări pentru a găzdui Jocurile Olimpice?” |
Nivelul de detaliu al rezultatelor | Oferă rezultate concise, răspunsuri directe sau linkuri, asemenea unei căutări inteligente pe web. | Produce rezumate ample, susținute de dovezi, adesea cu citări, compromisuri de luat în calcul și etape de raţionament. |
Viteză | Rapidă — de obicei, câteva secunde. | Mai lentă — poate dura câteva minute sau mai mult, din cauza raţionamentului în mai multe etape. |
Actualitatea informațiilor | Prioritizează cele mai recente informații disponibile; ideală pentru știri de ultimă oră sau date care trebuie obținute la timp. | Folosește surse recente când sunt relevante, dar se concentrează pe înțelegerea contextului, nu doar pe actualitatea informațiilor. |
Complexitatea întrebării | Ideală pentru întrebări bine definite și specifice. | Ideală pentru întrebări deschise, exploratorii sau strategice, fără un singur răspuns corect. |
