Technical Context
I watched Google's video and a simple thought struck me: we are being quietly led to a model where the agent lives not in an app or a separate chat, but right within the system UX. This is no longer "open the assistant and ask," but almost an OS-native action layer. For AI integration, this is far more important than any new demo bot.
The first thing that catches the eye is that the agent becomes an interface intermediary between the user's intent and a set of applications. Whether this is Android in its final form or an intermediate prototype, the direction is clear. The OS is starting to understand the entire task, not just passing text to a model.
And this is where it gets most interesting for those building AI automation. If the agent resides at the OS level, it doesn't need to reteach the user which button to press in which app every time. It gets a chance to assemble an action from multiple steps: open the right screen, pull in context, suggest the next move, and sometimes even execute it.
Essentially, the UI becomes thinner, and the orchestration becomes thicker. I would expect a combination of system intents, a permission model, access to on-device context, and possibly a hybrid scheme where some logic runs locally while heavy reasoning goes to the cloud. Without this, such a UX will either be slow or quickly run into privacy and security issues.
A separate issue I'd focus on immediately is error control. When an agent is built into the OS, the cost of a mistake is higher than for a website chatbot. If it's not just advising but actually acting across applications, a very rigid architecture for confirmations, rollbacks, and authority limits is required.
Impact on Business and Automation
Products with complex user journeys currently spread across five screens will win. If an agent can complete this journey in a single scenario, conversion and retention get a real, not just cosmetic, boost.
Interfaces built on the user having to search for the right button will lose. An agent will simply bypass such a UX. And yes, the classic "here's another chat in the corner" will look drastically outdated against this backdrop.
For businesses, the takeaway is practical: you need to think not only about the model but also about AI architecture, access rights, system actions, and control points. At Nahornyi AI Lab, we solve these kinds of problems in practice: determining where automation with AI is appropriate and where a careful human failsafe is needed. If you see that your product can be transformed from a set of screens into a coherent agent-based scenario, let's look at it together and build an AI solution development plan tailored to your actual operations, processes, and risks.