OpenAI, the parent company of ChatGPT, has developed a groundbreaking AI agentic tool called “deep research”. “Deep research” enables you to conduct multi-step research on the Internet for complex tasks. According to OpenAI’s official blog, “deep research” can be achieved in minutes which would take you hours. Also, the “deep research” tool can work independently, without any human intervention, to create a comprehensive report. 

Interestingly, the model takes anywhere from 5 to 30 minutes to complete its work, while you relax on the couch. The model enables you to search for anything ranging from a competitive analysis of AI models to a personalized report on the best motorcycle. As it processes anywhere from hundreds to thousands of web pages, you will see a sidebar displaying the sources analyzed giving users full transparency into its research process. This extensive drive into the sea of web pages contributes to the waiting period.

OpenAI’s deep research: Still, 30 Minutes?

While this depth of research is impressive, it also raises a key question: Why does deep research take so long? So, it assesses the sea of data available on the Web, ranging from texts and PDFs to even images. The process of finding, analyzing, and synthesizing this data—on par with a research analyst’s work—is likely why deep research takes longer than conventional AI models. Also, it generates a well-documented work product and not merely a quick summary, which any usual AI model does. 

Read about OpenAI's previously launched AI agent Operator at: Test Scores of ChatGPT’s All-new Computer-Using Agent “Operator” Might Blow Your Minds

Ultimately, deep research is designed for multi-faceted, domain-specific inquiries where depth and accuracy matter more than speed.

OpenAI’s deep research: Human-Like Approach

Humanity’s Last Exam, a recently released evaluation, finds the model to have a human-like approach by effectively seeking out specialized information when necessary. It means, the model discovers, reasons about, and consolidates insights from across the Web, without any human intervention. It is because of its training on real-world tasks requiring browser and Python tool use, using reinforcement learning methods.

Deep research builds on many real-world challenges demanding extensive context and information gathering from diverse online sources making it the best choice for you. Its accuracy ranks at an all-time high of 26.6 percent while others remain somewhere between 3.3 - 13 in the same tests. Interestingly, Deep Seek R1, the Chinese AI Model, scores 9.4 percent. 

Read more about DeepSeek R1 at: Let's Dive Into How China’s AI “DeepSeek R1” Plans to Dominate the AI Race 

While its slower response time may seem like a drawback, the depth and accuracy of its analysis set it apart from conventional AI models. As AI continues to evolve, will users prioritize speed over substance, or is this the beginning of a new era where AI thinks before it speaks?