Salesforce and Google Cloud have expanded their strategic partnership. The latest collaboration aims to provide businesses with a greater degree of flexibility in how they build and deploy AI-powered agents, addressing one of today’s key challenges.
Breaking down the AI choice barrier
At the heart of this partnership expansion is a shift away from vendor lock-in. Businesses using Salesforce will soon be able to build Agentforce agents using Google’s Gemini models and deploy Salesforce applications directly on Google Cloud infrastructure.
This added flexibility is timely, as a Salesforce study indicates that agentic AI represents a $2trn market opportunity, with 84% of CIOs believing it will be as significant to businesses as the internet
Srini Tallapragada, Salesforce President & Chief Engineering and Customer Success Officer says: “Through our expanded partnership with Google Cloud and deep integrations at the platform, application, and infrastructure layer, we’re giving customers choice in the applications and models they want to use.”
Real-time intelligence and customer data
Amongst the key features of the expanded partnership is the integration of Google Search into Agentforce through Vertex AI. This builds upon the existing zero-copy data foundation between Salesforce Data Cloud and Google BigQuery, allowing agents to access up-to-the-minute information while maintaining contextual awareness.
In terms of practical applications, there are many. For example, in supply chain scenarios, an Agentforce agent could track shipments in Salesforce Commerce Cloud while simultaneously monitoring real-time external factors from Google Search that might cause disruptions—from weather events to geopolitical developments.
Multi-modal AI capabilities coming in 2025
Starting this year, Google’s Gemini models will be available for prompt building and reasoning directly within Agentforce, bringing multi-modal capabilities to Salesforce’s agent platform.
These enhancements will enable agents to:
- Process and interpret images, audio, and text simultaneously
- Leverage Gemini’s 2 million-token context window to reference massive amounts of information
- Deliver faster response times through Google’s Tensor Processing Units
Fiona Tan, CTO of Wayfair, highlights the potential impact: “The Salesforce and Google Cloud partnership, particularly the availability of Salesforce on Google Cloud infrastructure and the integration of Agentforce and Gemini, offers powerful new capabilities to personalise interactions and empower our teams to better serve our customers.”
Infrastructure flexibility and procurement simplification
Beyond AI model choice, the partnership is designed to help address infrastructure and procurement challenges. Customers will be able to deploy Salesforce’s unified platform, including Agentforce, Data Cloud, and Customer 360, on Google Cloud’s AI-optimised infrastructure.
Thomas Kurian, CEO of Google Cloud, highlights the significance: “Salesforce’s selection of Google Cloud as a major infrastructure provider means enterprise customers can now deploy some of their most critical applications on our highly secure, AI-optimised infrastructure, with minimal friction.”
Additionally, Salesforce offerings will become available through the Google Cloud Marketplace, creating new opportunities for joint customers to optimise their investments across both platforms.
The bigger picture: data, AI, trust, and actions
This partnership represents a holistic approach to enterprise AI adoption, addressing four main areas:
- Data: Zero-copy architecture that eliminates silos while maintaining security
- AI: Model flexibility across predictive, generative, and multi-modal options
- Trust: Multi-layered protection with encryption, data residency options, and built-in guardrails
- Actions: Seamless integration of automation and analytics across platforms
As businesses race to capitalise on the transformative potential of AI agents, partnerships that combine enterprise-grade security, model flexibility, and infrastructure choice have the potential to shape how organisations approach their AI sales strategy, moving beyond experimental deployments toward mission-critical implementations.
