There is a particular kind of technology announcement that sounds incremental on the surface and is actually structural underneath.
Google I/O 2026 was full of them.
New models. New tools. New features inside existing products. A familiar format for a familiar annual event. But read together, the announcements at I/O on May 19 form something more significant than a product update cycle. They describe a specific vision of how human beings will interact with information, make decisions, and complete transactions over the next five years.
For anyone whose job involves reaching people at the moments when those decisions are made, it is worth reading carefully.
The Model That Changes the Speed of Everything
Google launched Gemini 3.5 Flash at I/O and the numbers behind it matter more than the name.
The model delivers what Google describes as "frontier performance for agents and coding, excelling at complex long-horizon tasks." On benchmark tests, it outperforms Gemini 3.1 Pro across multiple dimensions while operating at speeds the Flash series has always been known for, at less than half the cost of comparable models.
The practical implication is not the benchmark performance. It is the cost and speed combination. When AI gets cheaper and faster simultaneously, the barrier to deploying it across every surface, every search result, every product recommendation, every customer interaction, drops toward zero. Google is not just building a better model. It is making the infrastructure for an AI-native internet economically viable at scale.
The Agent That Works While You Are Not Looking
The most significant announcement for how work operates, and by extension marketing, came in the form of Gemini Spark.
Spark is described by Google as a "24/7 personal AI agent that can work in the background across Workspace, custom connectors, and the open web." The key word is background. Spark does not wait to be asked. It monitors, executes, and reports.
The examples Google provided are specific and worth taking seriously. Spark can identify a product launch timeline conflict, automatically suggest code changes, create a Jira ticket, recalculate the launch timeline, update internal documents, and draft stakeholder emails, all without a human initiating any individual step. For sales teams, Spark can monitor an account's health across Salesforce and Zendesk, identify a churn risk, draft a retention strategy, and prepare a customer-ready email awaiting only explicit approval to send.
This is not an assistant. It is an employee that never stops working.
The marketing implication is direct. If the people you are trying to reach have agents managing their inboxes, screening their research, and preparing their decisions, your marketing is no longer reaching a human at every touchpoint. It is reaching a system that filters on their behalf. The question of how to be genuinely present in an agent-mediated world is one that most marketing teams have not yet started answering.
Video Creation Just Became a Text Prompt
Gemini Omni is Google's new model for video creation and editing. The description from Google's official announcement is precise: it "produces dynamic video content by blending text, audio, image, and video inputs" and "delivers a highly intuitive approach to video creation and editing using natural language."
The applications Google highlighted are directly relevant to marketing: interactive virtual try-ons for e-commerce, streamlined post-production workflows, and tailored video narratives for different audiences.
Combined with Veo 3.1, now integrated directly into Google Ads, and Google Pics, the new AI image generation and editing tool built into Drive, Docs, and Slides, the picture is clear. Google is systematically removing every production bottleneck that has historically required specialist teams and significant budget. The gap between having a marketing idea and executing it at broadcast quality is closing month by month.
The Infrastructure Behind Everything
The numbers Google committed to at I/O deserve attention.
Google confirmed it will spend $180 to $190 billion on AI infrastructure in 2026. AI Overviews now reach 2.5 billion users monthly across more than 200 countries.
These are not just large numbers. They are a signal of conviction. When a company commits $190 billion to a single year of infrastructure investment, it is not hedging. It is building the physical foundation of a specific future, one where AI mediates an increasing proportion of every digital interaction its users have.
For context: $190 billion is more than the GDP of most countries. It is being spent in a single year on data centres, chips, and the cables connecting them. The world that investment is building is the one that marketing will operate inside for the next decade.
What the Agentic Web Means for Discovery and Purchase?
Across the I/O announcements, Microsoft's April 2026 framing of "three eras of the web" remains useful: the human web, the LLM web, and the agentic web.
The human web is where people search, browse, and click. The LLM web is where people ask questions and get synthesised answers. The agentic web is where agents act, researching, comparing, and completing transactions without a human touching each step.
Google I/O 2026 was largely about the transition from the second era to the third.
Gemini Spark operates in the agentic web. The Managed Agents API Google launched at I/O, which allows developers to build custom agents that reason, call tools, and execute code inside secure Google-hosted environments, is the infrastructure for the agentic web. The Universal Cart and agentic commerce capabilities announced at Google Marketing Live the following day are the commercial layer of the agentic web.
The commercial implications are significant. When agents complete purchases on behalf of users, the entire customer journey changes. Awareness, consideration, and conversion, the three stages that marketing has organised itself around for decades, collapse into a single agent-mediated transaction. The brand that the agent selects may never have been consciously chosen by the human at all.
Conclusion
The distance between what Google announced at I/O and the daily reality of most marketing teams is large. Agents are not yet mediating most consumer purchases. The agentic web is emerging, not dominant.
But the direction is established, the investment is committed, and the infrastructure is being built at a scale that removes doubt about the destination.
The marketing teams that will navigate this well are the ones starting now to answer questions that are currently speculative but will be operational within three years. How does a brand get recommended by an AI agent? What does a brand need to look like inside an agent-mediated product comparison? How do you build a presence in a world where the human is one step removed from the decision?
