Google releases Gemini 3 with new reasoning and automation features

Google has launched Gemini 3 and integrated the new AI model into its search engine immediately, aiming to push advanced AI features into consumer and enterprise products faster as competition in the AI market intensifies.

The release brings new agentic capabilities for coding, workflow automation, and search, raising questions about how quickly businesses can adopt these tools and what impact they may have on existing IT operations.

Google also introduced new agent features, including Gemini Agent and the Antigravity development platform, designed to automate multi-step tasks and support software teams.

Gemini 3 comes in a Deep Think mode as well, which “outperforms Gemini 3 Pro’s already impressive performance on Humanity’s Last Exam (41.0% without the use of tools) and GPQA Diamond (93.8%). It also achieves an unprecedented 45.1% on ARC-AGI-2 (with code execution, ARC Prize Verified), demonstrating its ability to solve novel challenges.”

The update introduces a generative UI that can build custom visual layouts in response to prompts, allowing Gemini to present answers in interactive, application-like formats.

Gemini 3 also brings long-context reasoning and improved multimodal support, enabling the model to handle larger documents, richer datasets, and complex multimedia inputs, the company said.

Immediate integration

For enterprise IT leaders, the key question is how quickly Gemini 3’s capabilities will be integrated into real-world workplace applications and whether agentic features like Deep Think and Antigravity can deliver measurable productivity gains without introducing new operational risks.

According to Sanchit Vir Gogia, chief analyst at Greyhound Research, Google’s decision to embed Gemini 3 directly into Search from day one is one of the most consequential shifts in the enterprise AI market this year.

“This is not an AI feature layered on top of Search,” Gogia said. “It is a fundamental rewrite of the global information distribution engine that billions rely on every day. For enterprises, this marks a decisive moment where AI is no longer a separate capability but the default interpreter of user intent, workflow context, and knowledge retrieval.”

By tightly coupling Gemini 3 with Search, Google is converting its most powerful distribution surface into a permanent AI gateway, which reshapes how organizations consume intelligence and structure their digital workplace experience, Gogia said.

Others suggested that the integration could also reshape how enterprises rely on Google’s ecosystem.

“For enterprises, Google Search might become a one-stop shop for all secondary information, whether it is normal search or for generating content,” said Sharath Srinivasamurthy, research vice president at IDC.  “Also, the ad business for Google will go through a change as it will consider AI-driven search and prompts to push relevant ads. The search and prompts (now) will start feeding into Google training models, which will eventually make the search and Gemini’s responses better.”

Charlie Dai, VP and principal analyst at Forrester, said that Google’s integration decisions reflect its confidence in the model’s performance and its native multimodal capabilities. It also shows Google’s intent to monetize AI through core products rather than standalone offerings.

“As enterprise search becomes an AI gateway, enterprise CIOs must have a holistic view on the dependencies in the AI stack for long-term observability and governance,” Dai added.

Automating multi-step workflows

While Google is positioning Gemini 3’s agentic capabilities as a step toward hands-free automation, analysts caution that most enterprises are still far from running fully autonomous workflows. Srinivasamurthy said the complexity of real-world processes remains a major barrier.

“Workflows that cut across multiple systems, involve human exceptions, compliance reviews, or high-risk decision points still require careful orchestration and typically human-in-the-loop supervision,” Srinivasamurthy added. “Enterprise adoption is in its early stages, and scaling from pilot or siloed implementations to organization-wide workflows continues to be a significant challenge.”

Dai agreed that while agentic tools like Gemini Agent and Antigravity with increasingly powerful reasoning capabilities will continue to move enterprises closer to workflow automation, safety hinges on robust guardrails and AI readiness of enterprise data.

“CIOs need governance frameworks for identity, data lineage, and action approval, plus continuous monitoring for non-deterministic behavior,” Dai said.

Gogia said that Gemini Agent and Antigravity will unlock meaningful productivity gains, but only once enterprises build the frameworks required to manage autonomous systems responsibly. “The technology may be ready for demonstration, but enterprise governance is still catching up,” Gogia said. “Organizations that scale agentic automation prematurely may expose themselves to operational, regulatory, and reputational risks that outweigh the short-term benefits.”