News

AI Agents Move From Product Feature to AGI 'Dress Rehearsal'

• By John K. Waters
• 05/26/2026

Google used its I/O developer conference last week to present artificial intelligence agents not as a distant research project, but as a product strategy spanning Search, personal assistants, productivity software, developer tools, and smart glasses.

The announcements added to a broader industry push toward AI systems that can do more than answer questions. These systems are being designed to plan tasks, use software, act across apps, interpret images and video, and help users complete work with less manual input.

Google’s I/O announcements centered on the company’s Gemini platform, including deeper AI integration into Search, YouTube, Gmail, Docs, Chrome, shopping, creative tools, and smart glasses. The company also introduced new Gemini models, a redesigned Gemini app, and agentic tools meant to automate or assist with more complex tasks.

The move reflects how quickly AI agents have become central to the competitive strategy of large technology companies. For much of the past two years, generative AI products were defined primarily by chat interfaces. The current race is increasingly about whether AI can act, not just generate text.

That shift was underscored this week by Google DeepMind CEO Demis Hassabis, who told Axios that current AI agents are a “practice run” for artificial general intelligence. Hassabis said AGI could arrive as soon as 2029, earlier than his previous estimate of 2030.

The comment matters because Google is among the companies with the largest financial, technical, and product stakes in agentic AI. Its AI strategy now spans research labs, consumer products, cloud services, Android, and Search, making the company one of the clearest tests of whether agents can be useful at scale.

Alphabet and Google CEO Sundar Pichai described ChatGPT’s arrival as a catalyst for a major internal pivot at Google, including the unification of AI research under Google DeepMind, the creation of centralized AI infrastructure, and leadership changes across Search, YouTube, Cloud, Android, and Chrome.

The company’s agentic push also reaches into computing interfaces. Google showed “intelligent eyewear” at its I/O event, developed with partners, including smart glasses designed to support voice AI, live translation, and augmented-reality functions.

That makes agents less like standalone apps and more like a layer across daily computing.

In that model, an AI system might summarize messages, generate documents, plan a purchase, answer questions about a video, help write code, or interpret what a user sees through wearable hardware.

The business case is clear. If AI agents become reliable, companies can integrate them into products that already have billions of users. But the risks are also more immediate than they were when agents were confined to demos and research prototypes.

Agents that act across apps and services may need access to personal data, enterprise files, calendars, email, payment systems, code repositories, and corporate workflows. That access creates questions about permissions, logging, error correction, security, privacy, and user consent.

The technical challenge is also unresolved. AI systems can still produce incorrect answers, misunderstand instructions, or behave unpredictably when operating in open-ended environments. Those limitations matter more when systems are asked to complete tasks, rather than simply respond to prompts.

Hassabis called for greater urgency from governments, economists, and the public in preparing for more powerful AI systems, and he endorsed federal moves toward AI safety regulation, including proposals requiring pre-release testing.

For Google, the near-term question is not whether agents amount to AGI. It's whether users will trust them enough to delegate real tasks. For the broader AI industry, the stakes are larger: agents are becoming the bridge between today’s AI products and the more autonomous systems that leading labs say may arrive within years.