“Deep Research” becomes AI’s latest recycled buzzword as labs race to rebrand similar tech

The phraseology power of “deep dive” may be dwindling, but “Deep Research” is just getting started.

The tech marketing machine has recycled yet another term, as “Deep Research” becomes 2025’s hot AI buzzword. Following the pattern of previous industry crazes like RAG (2023) and agentic systems, major AI labs including Google, OpenAI, Perplexity, DeepSeek, Alibaba, and xAI have all launched versions of “Deep Research” capabilities without establishing a consistent definition. This rebranding phenomenon highlights how frontier AI companies continually repackage similar technological approaches under new marketing terms, creating confusion while competing for market attention.

The big picture: Multiple major AI labs have released similarly named but technically distinct “Deep Research” products, creating market confusion about what the term actually means.

• Google released Gemini 1.5 Deep Research in December 2024, followed by OpenAI and Perplexity launching their own Deep Research implementations in early 2025.
• Simultaneously, companies like DeepSeek, Alibaba’s Qwen, and Elon Musk‘s xAI have introduced “Search” and “Deep Search” features for their chatbots.
• Open-source developers have contributed to the trend with numerous “Deep Research” implementations appearing on GitHub.

Why this matters: The inconsistent use of “Deep Research” as a marketing term mirrors previous AI industry hype cycles, making it difficult for users and businesses to evaluate the actual capabilities of these systems.

• The pattern resembles the RAG (Retrieval-Augmented Generation) trend of 2023 and subsequent “agents” and “agentic RAG” marketing waves.
• Without standardized definitions, organizations may struggle to make informed decisions about which technologies to adopt.

Reading between the lines: The rapid proliferation of similar-sounding “Deep Research” products suggests intense competitive pressure in the AI industry to match feature announcements from market leaders.

• Each company wants to signal they’re not falling behind in the AI arms race, regardless of substantial technical differences in their implementations.
• This marketing-driven approach prioritizes consistent branding over technical clarity and user understanding.

The historical context: The AI industry has established a pattern of rebranding existing technologies with catchy new terms to generate renewed market excitement.

• RAG systems were rebranded as “agents” in late 2023, which evolved into “agentic RAG” before the latest transition to “Deep Research” terminology.
• These cycles typically begin with flagship product launches from industry leaders that competitors then imitate to maintain market relevance.