The consensus that artificial intelligence cannot replace search engines in the short term is profoundly reshaping the strategic logic of tech giants. Alphabet, once perceived as conservative, has demonstrated structural advantages with its "dual-track" strategy—continuously optimizing its search business while independently developing AI conversational products like Gemini. Meanwhile, OpenAI, which bet heavily on chatbots, faces growth bottlenecks due to a mismatch between technological breakthroughs and actual user needs.
According to disclosures, OpenAI recently found that despite ongoing advancements in core technologies like reasoning models, most users still employ ChatGPT for simple queries rather than tackling complex scientific or mathematical problems it excels at. Earlier, CEO Sam Altman issued a "red alert" to his team, urging a refocus on mainstream user appeal.
In contrast, Alphabet CEO Sundar Pichai explicitly stated during an April earnings call that while search and Gemini have "partial functional overlap," they serve "entirely different use cases," formalizing the company's parallel development strategy for search and AI. This approach allows Alphabet to leverage its existing distribution channels and infrastructure cost advantages for rapid market adaptation.
The strategic divergence is evident in growth metrics and capital market performance. Alphabet continues expanding AI product coverage through integration advantages, whereas OpenAI, despite surpassing $19 billion in annualized revenue, lags behind its early-year target of 1 billion users. Notably, OpenAI is now seeking a new funding round at a $750 billion valuation, approximately 50% higher than its valuation two months prior.
**OpenAI's Mismatch Between Tech and Market Demand** OpenAI's core challenge lies in the disconnect between its R&D focus and mainstream user needs. This year, the company prioritized developing "reasoning models" that excel in complex math and science problems—even achieving gold-medal performance in international math Olympiads.
However, internal observations reveal most ChatGPT users don’t utilize these advanced capabilities. Peter Gostev of LMArena notes average users prefer asking about movie ratings rather than engaging models that "think for half an hour." Reasoning models often take seconds or minutes to respond, creating a subpar experience for users accustomed to Alphabet's near-instant search results.
OpenAI product lead Nick Turley likened ChatGPT’s text-centric design to MS-DOS in the 1980s, arguing it limits feature discoverability. Apps head Fidji Simo acknowledged the need to shift from text dialogues to more generative and intuitive interfaces.
**Alphabet’s Foresight Validated** Alphabet’s strategy of keeping search and AI chatbots separate is gaining market validation. While many expected AI chatbots to replace traditional search, Alphabet maintained they serve distinct scenarios—a view rooted in user behavior. Search remains optimal for quick answers, while chatbots suit complex problems requiring deep analysis. Amazon mirrors this approach, operating its shopping search engine separately from the Rufus AI chatbot.
Reports indicate Alphabet’s AI models now rival ChatGPT in image generation and coding. Crucially, Alphabet’s competitive moat includes dominant distribution channels (Search, Chrome, Gmail) and cost efficiencies from in-house AI chips.