SAP and Google Cloud have announced a partnership focused on AI agents working between their systems. The update that came out last week explains how their tools will connect so that businesses can run tasks between SAP software and Google Cloud without jumping between platforms.
Gemini Enterprise will act as the main control point. It connects data and coordinates how different AI agents act. SAP’s Engagement Cloud, Customer Experience tools and Joule agents plug into this system, giving users one place to manage activity.
The companies explain that this allows agents to access shared data securely and act on a goal typed in by a user. A marketer can enter a request such as increasing repeat purchases over 30 days, and the system handles the work from start to finish.
Balaji Balasubramanian, President and Chief Product Officer at SAP Customer Experience and Consumer Industries, said, “This is more than a data integration; it’s a leap forward for AI agents that can collaborate naturally and execute seamlessly. By combining SAP Business Data Cloud Connect for Google with interoperable AI agents across SAP and Google Cloud, we’re giving organizations a path from AI experimentation to AI-enabled customer experience at scale. Marketers can spend less time on manual tasks and more time shaping the customer journey.”
Kevin Ichhpurani, President of Global Partner Ecosystem at Google Cloud, added, “To realize the full potential of agentic AI, businesses need their systems to speak the same language. By uniting SAP’s enterprise data and customer engagement platform with Google Cloud’s AI, we’re enabling marketers to move beyond simple automation to multi-agent orchestration, driving dynamic campaigns that reason and adapt to market shifts in real time.”
What Is Multi Agent AI And How Does It Work?
Multi agent AI, often called a multi agent system, works as a group of independent software agents that interact in a shared environment. Each agent has its own task and can make decisions on its own, but they communicate and work together to reach a goal.
This is a bit different from a single AI system that handles everything alone. In a multi agent system, work is divided. One agent may analyse data while the other creates content and another manages communication. This structure allows the system to deal with more complex work.
More from Artificial Intelligence
- What Will Monetisation Look Like For Creators In The AI Era?
- Meta Will Be Using AI Chat Controls To Manage Parental Controls – How Will It Work?
- It May Not Be Intentional, But AI Bias Is Real, And It’s Already Distorting Real-World Outcomes: Experts Comment
- How Do NVIDIA Chips Power Alibaba’s AI Car Systems?
- Akeneo Unveils “The Great Restack” As Agentic Commerce Reshapes Global Retail Architecture
- More Experts Share: How The UK’s Cybersecurity Is Being Impacted By AI & Geopolitics
- AI Whisperer, Prompt Engineer, Chief AI Officer. Welcome To The Weirdest Jobs Market In Tech History
- Can’t Find Your Car? AI Can Now Help You Locate Your Parking Spot
Agents observe their environment and collect data. They then process that data, often using LLMs, to decide what to do next. After that, they act and share updates with other agents. This interaction keeps the system moving.
Orchestration organises tasks into a structured flow, with each agent called at the right time. It works like a project plan where responsibilities are assigned and managed so the final goal is met.
This structure brings flexibility and scale. More agents can be added when needed, and if one fails, others continue the work. That makes the system reliable and suited to complex, changing environments.
How Will This Show Up In Marketing And Business Tools?
The partnership places marketing as the first use case. SAP says more than half of marketers report that fragmented and outdated data prevents them from acting in the moment. This new model deals with that by joining data and letting agents act on it instantly.
Joule agents in SAP Engagement Cloud handle full campaign processes. This covers content creation, personalisation, visual outputs and conversational engagement with customers. All of this runs without manual input between different tools.
The system also uses SAP Business Data Cloud Connect and Google BigQuery to allow data to move between platforms without copying it. This keeps security and governance intact while letting agents access what they need in real time.
SAP says businesses using this model can do things like generate campaigns automatically, refine them continuously and in turn, improve results over time. It also means faster launch times and lower running costs, as fewer manual steps are needed.
The rollout for marketing is expected in the second half of 2026. SAP adds that the same model can work in other areas of its Customer Experience tools, so it can build a system where AI agents handle the more complex business tasks through shared data and coordinated action.
