Google‘s search engine is set to “change profoundly” in 2025.
CEO Sundar Pichai made the claim at The New York Times’ DealBook Summit this week and said users will be “surprised” by how it answers “more complex questions”. The summit, which attracts leaders from various sectors, has historically been a platform for major tech announcements.
“I think we are going to be able to tackle more complex questions than ever before,” he said of Google Search. The company’s current search engine processes over 3.5 billion queries daily, demonstrating its crucial role in global information access.
“I think you’ll be surprised, even early in ’25, the kind of newer things Search can do compared to where it is today.” This statement comes as search technology evolves rapidly, with AI integration becoming increasingly sophisticated.
Pichai also responded to Microsoft Satya Nadella’s comment suggesting Google should have been the “default winner” in the AI race, but pointed out that Microsoft uses “someone else’s models” (OpenAI), and said Google is in the “earliest stages of a profound shift”. This rivalry between tech giants has intensified as AI capabilities expand, with investment in AI research reaching record levels.
“I would love to do a side-by-side comparison of Microsoft’s own models and our models,” he said at the summit. Such comparisons could provide valuable insights into the effectiveness of different AI approaches, as the global AI market is expected to reach $190.61 billion by 2025.
“When I look at what’s coming ahead, we are in the earliest stages of a profound shift. I just think there’s so much innovation ahead. We are committed to being at the state of the art in this field, and I think we are.” Google’s commitment to AI research is evident in its substantial investments, with the company spending over $31.6 billion on R&D in 2021 alone.
Google has already added AI features to its search engine and has promised a major update to its Gemini chatbot, which is rival for Microsoft’s Copilot and OpenAI’s ChatGPT. These AI-powered tools are transforming how users interact with search engines, with natural language processing becoming increasingly sophisticated.
The upcoming changes to Google Search represent a significant evolution in search technology, building on decades of development since the company’s founding in 1998. Experts suggest that these advancements could fundamentally change how we access and process information online.
Industry analysts predict that the enhanced search capabilities could lead to more personalized and contextually relevant results, potentially revolutionizing fields such as education, research, and business intelligence. The integration of advanced AI could enable users to receive more nuanced and comprehensive answers to complex queries.
The competition between major tech companies in this space has accelerated innovation, with each player pushing the boundaries of what’s possible in search technology. Microsoft’s partnership with OpenAI and Google’s development of its own AI models highlight different approaches to achieving similar goals.
Recent studies indicate that AI-enhanced search engines could reduce search time by up to 45% while improving result accuracy by 30%. These improvements could have significant implications for productivity across various sectors.
Privacy experts also note the importance of balancing these technological advances with user data protection. As search engines become more sophisticated, questions about data collection and usage become increasingly relevant.
The evolution of search technology reflects broader trends in AI development, with natural language processing and machine learning playing crucial roles. These advancements could lead to more intuitive and conversational interactions with search engines.
Economic forecasts suggest that improvements in search technology could generate significant value across industries, with potential productivity gains estimated at $2.6 trillion to $3.7 trillion annually by 2025. This impact could be particularly significant in knowledge-intensive sectors.
The development of more advanced search capabilities could also address current limitations in information retrieval, such as understanding context, handling ambiguity, and processing complex queries. These improvements could make search engines more accessible to users with varying levels of technical expertise.
