Google I/O 2025: Gemini, AI Search, and the Evolving Business Model

May 20, 2025 / Max Weinbach

Summary of the News:

  • AI-Centric I/O: Google I/O 2025 heavily focused on Gemini AI and its integration across Google’s ecosystem, particularly Search, signaling a major strategic shift towards an AI-driven future. Android-specific news was largely separated.
  • Gemini Model Advancements: Continued evolution of the Gemini family (2.5 Pro, Flash) including a new “Deep Think” reasoning mode, alongside powerful multimodal features (seeing, understanding, talking, creating via tools like Imagen 4 and Veo 3).
  • Revolutionized AI Search:
    • AI Overviews: Rolling out globally, providing synthesized answers directly on search results pages, reportedly used by 1.5 billion monthly users.
    • AI Mode: A new flagship search experience in the U.S. featuring advanced capabilities like query fan-out, Deep Search for complex research, Search Live for real-time visual interaction (Project Astra), agentic tasks (Project Mariner) for actions like bookings, personal context integration, and custom chart generation.
    • Shop with AI Mode: A significant push into AI-powered e-commerce with visual discovery, virtual try-on, and agentic checkout features.
  • Business & Monetization Focus:
    • Google is processing ~480 trillion tokens monthly on its custom TPUs, about 183 million tokens per second.
    • Addressing concerns about search revenue (currently ~56.6% of Alphabet’s total, ~$198.08 billion in FY2024), Google claims AI is expanding search engagement.
    • New monetization strategies include ads within AI results, enhanced shopping features aiming to increase conversion and merchant fees, and new consumer/enterprise subscription tiers (AI Pro at $19.99/mo, AI Ultra at $249.99/mo).
  • AI Services & Data Ecosystem:
    • Emphasis on connecting Gemini to real-time data and services via tools, extensions, and protocols like MCP.
    • Leveraging Google’s vast data from Maps, YouTube, Gmail, etc., as crucial assets for AI, potentially creating new revenue streams through API access to this data.

A Clear Focus on AI

Google I/O 2025 marked a significant strategic focusing for the company. With Android-specific announcements largely separated into their own event, the main keynote was overwhelmingly dedicated to Gemini, Google’s flagship AI, and the company’s ambitious vision for an AI-driven future. This vision centers on transforming core products, especially Search, into a highly personalized, context-aware assistant. This strategy is being realized through several key advancements. The continued evolution of the Gemini family, including 2.5 Pro, the efficient 2.5 Flash, the powerful 2.5 Ultra, and the new “Deep Think” reasoning mode, underpins these efforts. Furthermore, Google is fostering an ecosystem where AI agents can interact and utilize each other’s capabilities, notably through support for protocols like the Model Context Protocol (MCP).

A strong emphasis was placed on making AI truly understand and interact with the world in a human-like way. This includes multimodal features such as Gemini Live allowing users to share their camera view or screen for real-time visual context understanding (Project Astra capabilities). Enhanced natural language processing and more natural-sounding voice output improve how the AI understands and talks. Powerful generative tools like Imagen 4 for sharper image creation with better text rendering, and Veo 3 for video generation, now with native audio tracks, showcase its creative abilities. Google’s leadership expressed the belief that these advancements are steps towards creating “world models” – AI systems with a deep, nuanced understanding of information and the world around them.

AI Search: A Paradigm Shift

The most prominent manifestation of Google’s AI-first strategy is the radical transformation of Google Search. The traditional “ten blue links” are evolving into a dynamic, conversational, and highly contextual information experience. AI Overviews, previously in Search Labs, are now rolling out globally and will appear on traditional search results pages for billions of users. These summaries, powered by a custom Gemini 2.5 model, aim to provide quick, synthesized answers to queries. Google reports 1.5 billion monthly users engaging with them and a greater than 10% increase in follow-on queries where Overviews appear.

A new, dedicated tab or experience, AI Mode, is positioned as the flagship AI search interface and is rolling out to all U.S. users. It’s where Google will debut its most advanced search capabilities. These include Query Fan-Out, where complex prompts are broken into multiple sub-queries processed in parallel, with the results fused into a comprehensive answer with citations. For complex research needs, Deep Search issues hundreds of sub-queries to return detailed, cited research memos or comparison tables (coming to Labs). Search Live, leveraging Project Astra, allows real-time, conversational interaction about what the user’s phone camera sees (rolling out summer 2025).

Further enhancing AI Mode, Agentic Tasks (Project Mariner) will enable the AI to perform actions on the user’s behalf, such as booking tickets, making restaurant reservations, or filling out web forms (early access for AI Ultra subscribers, then broader AI Mode integration). Users will also have the option to connect their Gmail, past search history, and eventually other Google app data for Personal Context, receiving highly personalized and tailored search results (opt-in, later this year). For queries related to sports, finance, or other data-intensive topics, AI Mode will be able to generate Custom Charts & Graphs on the fly (coming to Labs).

Shopping is a major focus within this new AI Search paradigm, manifested in Shop with AI Mode. This includes Visual Discovery through a right-hand visual panel, powered by Google’s Shopping Graph (tracking 50 billion product listings), which dynamically updates as users refine their shopping queries. A new diffusion model enables Virtual Try-On, allowing users to upload a full-length photo and see apparel SKUs realistically draped on their body. Finally, Agentic Checkout & Price Tracking empowers users to ask Gemini to track prices for specific items, receive notifications on price drops, and even have the AI (with confirmation) complete the purchase using Google Pay.

The Business Imperative: Navigating AI’s Financial Frontier

The heavy investment in AI, particularly in Search, comes amidst market concerns about the future of Google’s primary revenue engine and the still-nascent monetization strategies for generative AI. Google revealed it’s processing approximately 480 trillion tokens per month across all its Gemini workloads (Search, Gemini app, Cloud APIs, etc.). This massive scale is handled entirely by Google’s custom Tensor Processing Units (TPUs), including the new “Ironwood” generation, showcasing the success of its vertical integration and ASIC strategy.

Google Search and related advertising have long been the bedrock of Alphabet’s revenue. In fiscal year 2024, the “Google Search & Other” segment accounted for roughly 56.6% of Alphabet’s total revenue, amounting to approximately $198.08 billion. Any perceived threat to this dominance is a major concern for investors. In response, Google executives argue that AI is expanding search engagement rather than cannibalizing it, pointing to the >10% increase in follow-up queries with AI Overviews. Some reports also suggest that ads within AI Overviews are monetizing at rates comparable to traditional search ads.

The traditional advertising model, where Google earns when users click on ads (AdSense) displayed alongside search results, is challenged by AI providing direct answers. Google is addressing this by experimenting with integrating ads within AI Overviews and AI Mode, reported to be aiming for “hyper-relevant” ad placements informed by the richer context of AI-driven queries.

The enhanced shopping features in AI Search represent a clear attempt to create new revenue streams. By facilitating the entire shopping journey from discovery to transaction, Google aims to increase product conversion rates, potentially charge merchants higher Cost Per Acquisition (CPA) or commissions, and become a more central e-commerce platform, thereby potentially offsetting any decline in traditional search ad revenue.

AI Services, Data, and Diversified Revenue Streams

Beyond direct search and shopping monetization, Google’s AI strategy involves leveraging its vast data ecosystem and platform capabilities. LLMs like Gemini, while powerful, are inherently stateless and require connections to external data and services for real-time information and actions. Google facilitates this through tools and extensions and by supporting interoperability via protocols like the Model Context Protocol (MCP).

Google is deeply integrating its own services (Maps, YouTube, Gmail, Drive, Calendar, Keep, Finance, Sports, etc) as information sources and actionable tools for Gemini. This positions Google to monetize data access and APIs. Developers and enterprises already pay for using Gemini models via APIs (e.g., Gemini 2.5 Pro priced per million input/output tokens). Accessing Google’s rich, real-time data from its services is incredibly valuable for any LLM, and Google could potentially charge for API access to these data sources, regardless of whether the end application uses Gemini or another model. For instance, access to specialized data like real-time search information could become a significant revenue stream.

Google is also establishing direct consumer and enterprise revenue through tiered subscriptions. Google AI Pro ($19.99/month) offers access to more capable models, higher usage limits, and features like Deep Research. Google AI Ultra ($249.99/month) provides the highest limits, early access to cutting-edge models and experimental agentic features, plus substantial cloud storage. This strategy of resilience through diversification means that even if the direct monetization of AI search takes time to mature, by making its data and services indispensable to the broader AI ecosystem, Google aims to secure revenue streams less dependent on a single AI product’s success. These existing services already generate value and can be repackaged and monetized for the AI era.

In essence, Google I/O 2025 showcased a company aggressively pushing towards an AI-centric future, betting that enhanced user experiences, new agentic capabilities, and the strategic monetization of its vast data and infrastructure will redefine its core business and open up new avenues for growth.

The Vision: A Universal AI Assistant

Underpinning all these advancements is Google’s overarching ambition for Gemini: to evolve it beyond a collection of models and features into a universal AI assistant. This vision, as articulated by Google DeepMind, sees Gemini becoming a true “world model” capable of not just understanding and responding, but also of planning, simulating aspects of the world, and even imagining new experiences.

The goal is to develop a more general and profoundly useful form of AI that is intelligent, deeply understands the user’s context across any device, and can proactively plan and take action on their behalf. Google aims to transform the Gemini app, and by extension its AI interactions across all surfaces, into this universal assistant. Such an assistant would seamlessly handle everyday tasks, manage mundane administrative duties, surface insightful new recommendations, and ultimately empower users to be more productive while enriching their lives. This long-term vision paints a future where AI is an indispensable, intuitive, and empowering partner in navigating the complexities of daily life and achieving personal goals.


Ultimately, Google I/O 2025 painted a picture of a company not just adapting to the AI wave, but striving to lead it by deeply integrating advanced AI into the fabric of its most critical products and services, all while navigating the complex path to sustainable monetization and pursuing the ambitious goal of creating a truly universal AI assistant for everyone.

Google’s a company built on search, but part of being good at search also meant building up the infrastructure of services and tools that also give them an edge not only at training models, TPUs and scale to serve them globally, but also data sources and access to provide those back as services outside their first-party products.

Join the newsletter and stay up to date

Trusted by 80% of the top 10 Fortune 500 technology companies