OpenAI’s ‘Superpower’ Just Dropped—But Here’s the Catch

OpenAI has introduced Deep Research, a powerful AI-driven agent within ChatGPT that promises to independently conduct in-depth research, analyze data, and compile reports—tasks that would typically take humans hours or even days. Available to Pro users, Deep Research aims to transform research workflows for professionals in finance, science, policy, and engineering, as well as for anyone needing thorough, precise, and reliable research.

With rising competition from Chinese AI firm DeepSeek, which has gained attention for offering high-performance AI tools at a lower cost, OpenAI’s latest launch marks an aggressive move in the battle for AI-driven knowledge discovery. But can Deep Research truly set OpenAI apart?

How Deep Research Works

Unlike standard chatbot-style AI models, Deep Research is built to autonomously plan and execute multi-step research tasks. Users can provide queries along with text files, PDFs, or spreadsheets for additional context. The AI then spends between five and 30 minutes analyzing hundreds of sources, displaying a sidebar tracking its process, and finally delivering a fully cited research report.

OpenAI CEO Sam Altman called Deep Research “like a superpower; experts on demand!”, highlighting a personal case where it helped him find a rare NSX car in Japan after he had given up searching manually.

Deep Research vs. DeepSeek: The Battle for AI Superiority

Deep Research enters a market increasingly defined by competition, particularly from China’s DeepSeek, which recently disrupted AI economics by claiming it can match ChatGPT’s intelligence at a fraction of the cost. While OpenAI’s Deep Research o3 model achieved an impressive 26.6% accuracy on the AI benchmark Humanity’s Last Exam, DeepSeek’s R1 model trailed far behind at 9.4%.

Despite this performance edge, OpenAI still faces challenges. DeepSeek claims to have trained its latest AI models for just $5.6 million using older Nvidia H800 GPUs, whereas OpenAI and its U.S. counterparts have spent upwards of $100 billion developing comparable AI models. The stark cost difference raises questions about scalability and sustainability in AI development.

The Limitations of Deep Research

While Deep Research is undeniably impressive, OpenAI acknowledges that it is not without flaws. The AI can sometimes hallucinate facts, make incorrect inferences, and struggle to differentiate between authoritative sources and misinformation. This limitation underscores the ongoing challenge of ensuring AI-generated research is both credible and trustworthy.

Currently, Deep Research is available to Pro users with a limit of 100 queries per month, with planned access for Plus, Team, and Enterprise users. OpenAI is also working on a faster, more cost-effective version to increase usage limits for paid customers.

The Future of AI-Driven Research

Deep Research represents a bold step toward fully autonomous AI-driven knowledge discovery, a significant evolution from the early chatbot era. As OpenAI and DeepSeek compete to define the future of AI research tools, one thing is clear: the AI arms race is heating up.

For now, the question remains—will Deep Research truly revolutionize AI-assisted research, or will it be just another premium AI feature in an increasingly crowded market?