SAP and Google Cloud are expanding their partnership to develop a new agentic commerce architecture designed to automate marketing and retail operations at enterprise scale.
The move comes as artificial intelligence becomes a core part of customer retention strategies. According to SAP research, 78% of businesses consider AI essential for retaining customers in 2026. However, customer data sharing remains a major challenge, with fewer than two in five companies sharing customer data across customer experience platforms or CRM systems.
The partnership between SAP and Google Cloud aims to address this gap by connecting data, AI, customer engagement, and commerce operations within a more integrated architecture.
Addressing Data Fragmentation in Digital Commerce
Many digital commerce systems still suffer from fragmented data across marketing, inventory, payment, and customer service platforms. This can create poor customer experiences, such as when a customer receives a promotional offer for a product, only to discover at checkout that the item is out of stock.
Customer support teams may also lack a complete view of the customer journey, making it harder to resolve issues quickly and accurately.
The new architecture developed by SAP and Google Cloud is designed to unify this journey, from product discovery to checkout and post-sale support. The system is intended to recognise the customer, their context, and their needs across different digital channels.
The Role of the Universal Commerce Protocol
SAP Commerce Cloud is adopting the Universal Commerce Protocol to standardize data exchange between retailers, payment providers, and intelligent agents.
The protocol allows autonomous agents to interact directly with commerce platforms and manage different stages of the purchasing journey. This includes product search, cart management, payment processing, order tracking, and post-sale issue resolution.
By using this approach, businesses can reduce technical integration costs and accelerate their entry into AI-powered commerce channels without needing to rebuild their existing digital infrastructure.
SAP Commerce Cloud Integrates Google Gemini
SAP plans to work with Google to help merchant products appear more effectively across the Gemini app and Google Search, including AI Mode capabilities.
In this experience, consumers interact with search or conversational interfaces, while the backend architecture processes inventory checks, cart management, and payment operations.
SAP Commerce Cloud also integrates Google Gemini capabilities to power an intelligent shopping assistant that brands can offer directly to customers through text, voice, or chat-based interactions.
The Shopping Assistant retains customer context throughout the shopping journey. It uses live data such as customer behaviour, inventory availability, warehouse capacity, and current marketing information to deliver more accurate recommendations. This helps ensure that suggested products are actually available and can be fulfilled.
Connecting Marketing Campaigns with Real-Time Inventory
One of the key problems the SAP and Google Cloud partnership aims to solve is the gap between marketing campaigns and actual inventory availability.
In traditional systems, marketing teams may launch a campaign for a specific product without real-time synchronisation with warehouse data. As a result, customers may click on an ad or email promotion, reach the online store, and find that the product is no longer available.
The new solution allows the Shopping Assistant to query live inventory records before displaying or recommending products. This means products are only suggested after the system verifies their availability and fulfillment capability.
Bidirectional Data Flows
The architecture also connects SAP Engagement Cloud with Google Cloud to build a multi-agent framework capable of managing customer engagement more autonomously.
The technical foundation relies on SAP Business Data Cloud Connect for Google BigQuery, enabling bidirectional data linking without traditional data duplication. This approach helps reduce storage costs and lower latency while maintaining administrative and security controls.
Google BigQuery can process live variables such as weather conditions, location data, and advertising engagement rates. At the same time, SAP Customer Experience solutions provide internal customer context, including customer profiles, transaction history, service interactions, and consented engagement data.
SAP Engagement Cloud then activates this combined intelligence, using autonomous agents to coordinate personalised interactions across different stages of the customer lifecycle.
AI-Generated Marketing Campaigns
The joint architecture uses Google Gemini models, including Nano Banana 2, to generate localised marketing messages, customised visuals, and different campaign variations based on available enterprise data.
The system also goes beyond traditional text messaging. Through Google Rich Communication Services, marketing messages can be transformed into more interactive customer experiences.
With every interaction, the system analyzes the customer response, compares it with their profile and previous behavior, and automatically adjusts the next message, creative, or offer.
From Manual Campaign Execution to Goal-Based Marketing
The architecture gives marketing teams more room to focus on business objectives instead of managing every campaign step manually.
Rather than building customer segments, writing messages, preparing visuals, and testing campaigns separately, teams can define the business goal and provide the required enterprise data through SAP Engagement Cloud.
Autonomous agents can then analyze audiences using Google BigQuery, generate content through Google Gemini, and adjust campaigns based on real-time performance.
What This Means for the Future of E-Commerce
The SAP and Google Cloud partnership signals a major shift in how enterprise digital commerce may operate.
Instead of moving separately between an ad, website, mobile app, and customer support channel, consumers can express purchasing intent through a search engine or conversational interface. Intelligent agents can then execute the transaction by connecting directly with the company’s backend systems.
At the same time, retailers retain ownership of the customer relationship, even when the transaction takes place within a third-party environment such as search or an AI application.
Consented engagement and transaction data can be sent back into SAP Customer Experience solutions, updating the customer profile and giving Google Gemini models more accurate context for the next interaction.
In this way, the SAP and Google Cloud partnership is not only adding AI tools to e-commerce. It is reshaping how marketing, sales, inventory, and customer service connect inside one scalable enterprise commerce architecture.
Source: AINEWS
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