Google’s Agentspace has emerged as a major development in the enterprise AI landscape. First launched in December and now expanding with new features, this platform creates an interconnected ecosystem where AI agents from various developers can work together while providing enterprise-grade security and compliance features critical for business adoption.
What Is Google Agentspace?
Agentspace serves as both a marketplace and communication framework for AI agents. The platform lets businesses access agents built by Google, third-party developers, or create their own. Different agents communicate through the A2A (Agent-to-Agent) protocol, while users discover agents based on specific capabilities. Complex tasks get broken down and assigned to specialized agents according to their expertise.
Early adopters include major organizations like Banco BV, Cohesity, Gordon Food Services, KPMG, Rubrik, and Wells Fargo, showing enterprise-level interest in this technology.
New Features Expanding Agentspace Capabilities
Google has recently announced several important expansions to Agentspace:
Unified Search in Chrome now gives employees access to Agentspace’s search capabilities directly from the Chrome search box, integrating AI-powered search into existing workflows. This search capability works across diverse information types – text, images, websites, audio, and video.
Agent Gallery provides a centralized view of all available agents across the enterprise, including those from Google, internal teams, and partners. Companies can choose agents published by partners in Google Cloud Marketplace and enable them in Agent Gallery.
Agent Designer offers a no-code interface for creating custom agents that connect to enterprise data sources. This allows employees with limited technical experience to build agents tailored to their specific needs. These agents can integrate with those built in Vertex AI Agent Builder.
Google has also introduced new expert agents to the platform. The Deep Research agent explores complex topics across internal and external sources, synthesizing information into comprehensive reports. The Idea Generation agent helps employees develop novel ideas and evaluates them using a competitive system inspired by scientific methods.
The A2A Protocol: Foundation of Agent Communication
The A2A (Agent-to-Agent) protocol represents a significant technical advancement for building agent ecosystems. As the first hyperscaler to drive this initiative, Google has created an open protocol that enables agent capability advertising in standardized formats, secure communication between agents across different ecosystems, information exchange while maintaining data security, and support for both quick tasks and multi-day processes.
With over 50 technology partners already participating, including Anthropic, Salesforce, Deloitte, Langchain, MongoDB, and PayPal, Google is establishing A2A as an industry standard for agent communication.
Breaking Down Information Silos
A key advantage of Agentspace is its ability to connect previously isolated information sources. The platform searches across common work applications like Google Workspace, Microsoft 365, Jira, Salesforce, and ServiceNow. It builds an enterprise knowledge graph connecting employees with their teams, documents, and accessible software. This transforms disjointed content into actionable knowledge while understanding organizational context when providing information.
As Matt Jansen, Manager of Emerging Technology at Gordon Food Service, notes: “Employees are benefitting from easier access because they can search across multiple systems in one place, which translates to better decision-making, and less legwork to discover information.”
Enterprise-Grade Security and Compliance
For businesses concerned about data protection when deploying AI agents, Agentspace offers robust security features. Companies can scan systems for sensitive information such as PHI, PII, and confidential elements. They have options to block sensitive assets from agent access and search. Role-based access controls for different permission levels ensure appropriate data handling. Additional features like encryption with customer-managed keys and data residency guarantees further enhance security posture.
These protections allow businesses to adopt agent technology while maintaining compliance with data protection requirements and organizational security policies.
Real-World Applications Across Industries
While Google has showcased financial services examples, Agentspace’s architecture supports transformative workflows across sectors:
In healthcare, patient intake agents can coordinate with insurance verification agents. Research agents gather latest treatment protocols across internal and external sources. Idea generation agents develop novel approaches to patient care challenges.
For supply chains, deep research agents analyze market trends and supplier capabilities. Agents work across procurement, inventory, and logistics systems. Custom agents built by non-technical staff address specific workflow needs.
In software development, requirements analysis spans code repositories and documentation. Research agents explore internal and external best practices. Agents work across development, testing, and deployment environments.
The Growing AI Agent Marketplace
Google is expanding the AI Agent Marketplace within Google Cloud Marketplace. This allows customers to browse and purchase AI agents from partners like Accenture and Deloitte. Organizations can make these agents available within Agentspace for employee use and build personalized “teams” of agents for different work requirements.
This marketplace approach creates significant economic potential. Specialized agents can offer services for specific business needs. Companies can monetize their expertise through agents. Partners can build industry-specific or function-specific agents to address niche requirements.
Strategic Implementation Considerations
For organizations evaluating Agentspace, several strategic considerations emerge:
Data preparation is essential. Before agents can effectively work across silos, companies need to assess their information architecture and potentially restructure data to be more accessible while maintaining appropriate security controls.
Organizations must decide between custom versus off-the-shelf agents. With Agent Designer and the marketplace, companies must determine which functions require custom agents versus adopting pre-built solutions. This resembles traditional build vs. buy decisions but with more flexibility.
Employee training and adoption strategies are crucial. While Agentspace aims for ease of use, organizations will need approaches to help employees effectively leverage and build agents for their specific roles.
Integration with existing AI investments requires careful planning. Companies with existing AI initiatives need to consider how Agentspace complements or replaces current approaches to enterprise search, chatbots, and workflow automation.
The Future of Work: From Search to Agents
Google built its empire on search, but Agentspace suggests a future where AI agents become the primary interface for finding and acting on information. If successful, this would position Google at the center of a new AI economy where employees interact primarily with agents rather than search boxes. Tasks are executed through multi-agent collaboration. Organizations compete based on their effective use of agent ecosystems.
For businesses, this shift represents both opportunity and challenge. Early adopters who successfully integrate agents into their workflows could gain significant productivity advantages, while those who delay might struggle to catch up in an increasingly agent-driven business environment.
Getting Started
Agentspace is currently generally available via allowlist. Interested organizations can visit Google’s website to request access. Given the expanding feature set and growing partner ecosystem, early exploration of this platform could provide valuable insights into how agent technology might transform enterprise workflows.
As this ecosystem develops, businesses should monitor how agents evolve from simple assistants to collaborative teams that enhance human capabilities across the organization.
