Google Cloud Next ’26 Spotlights Contextual AI as the Future of Intelligent Workflows

Google’s push into contextual AI with Workspace Intelligence signals a shift from passive tools to proactive digital collaborators. The move positions the company at the forefront of a rapidly evolving enterprise AI landscape.

A portion of Google Cloud Next ’26 was dedicated to announcing nearly a dozen new features for Google Workspace, a team collaboration platform permeated with AI. Though each feature contributes valuable functionality, the runaway star of the show was ‘Workspace Intelligence’, a contextual AI engine that gets work done on behalf of users. The inclusion of a contextual AI-driven feature keeps the company current with one of the latest and most impactful trends, according to GlobalData, a leading intelligence and productivity platform.

Gregg Willsky, Principal Analyst, Enterprise Technology & Services at GlobalData, comments: “The announced features reflect the diverse ways that Google, like other vendors, is delivering AI capabilities that assist workers in their daily activities. However, the feature that stands head and shoulders above the crowd is Workspace Intelligence. It demonstrates the ability of contextual AI to execute essential tasks and produce outputs that are highly relevant, allowing users to get meaningful work accomplished.”

Contextual AI is beginning to make a splash on team collaboration platforms. It uses real-time data including enterprise data, factors such as a user’s past actions and preferences, and environmental aspects to deliver responses that are more personalized, more tailored, and more timely.

Willsky continues: “The bulk of the new capabilities, especially Workplace Intelligence, reflect an evolving trend in the team collaboration space. Specifically, the use of AI is moving from silos to being leveraged on a far grander scale – across vendor platforms, connecting parts of organizations, and linking organizations with external partners, suppliers, and the like. AI is serving as connective tissue, threading sections of vendor platforms such as meetings, chat, and calling; establishing links between those platforms and third-party applications used in various parts of the business; and integrating platforms from different vendors.”

The common theme across these scenarios is the distribution and exchange of data regarding operations, customers, suppliers, partners, and similar groups. AI bots or agents often act on that data, performing tasks and orchestrating workflows. While these bots or agents are still in the early stages of deployment, they are increasingly proliferating, often created with relative ease by non-developers using low-code or no-code tools.

Willsky concludes, “The expanding reach of AI comes with a heavy price. Compliance, confidentiality, and security issues, among others, multiply when platforms are intra- and inter-connected with data flowing across boundaries and AI agents manipulating and disseminating that data. Vendors have made assurances regarding the integrity of their platforms, but there remains a sense that these issues have not been adequately addressed. Vendors need to take a much deeper look.”