SAP and Google Cloud Revolutionize Commerce with Agentic AI

SAP and Google Cloud Join Forces for a New Era of Commerce

SAP and Google Cloud have announced the deployment of an agentic commerce architecture, a technological advancement aimed at automating marketing and retail operations on a large scale. This initiative is based on a SAP study revealing that 78% of companies consider artificial intelligence (AI) a crucial element for retaining their customers by 2026. However, a major obstacle remains: fewer than two in five companies effectively share customer data between customer experience platforms (37%) and customer relationship management (39%).

To overcome this challenge, SAP and Google Cloud have decided to strengthen their partnership by developing an agentic customer experience architecture. This new structure aims to seamlessly integrate data, AI, customer engagement, and business operations.

A New Approach to AI in Commerce

The deployment of this architecture relies on a complete overhaul of AI interaction with commercial platforms. Currently, most digital commerce infrastructures depend on fragmented APIs. To address this, SAP Commerce Cloud is adopting the Universal Commerce Protocol, a framework that standardizes data exchange between retailers, payment gateways, and autonomous agents. This protocol allows software to autonomously manage the entire retail process, from initial search to transaction processing and post-sale management.

Integration of the Universal Commerce Protocol

Engineering teams are working on integrating the Universal Commerce Protocol, facilitating direct interactions between intelligent agents and commercial platforms. This standardization aims to reduce integration costs and accelerate the adoption of AI-driven channels.

SAP plans to work closely with Google to ensure that merchants' products are organically visible in the Gemini app and Google search results, utilizing the advanced features of AI Mode. Consumers interact with these interfaces while the backend architecture supports stock checks, cart management, and payment processing, without requiring changes to retailers' existing infrastructure.

An Intelligent Shopping Assistant

SAP Commerce Cloud also integrates the capabilities of Google Gemini to create a dedicated Shopping Assistant. This tool is deployed by brands directly to their consumers, facilitating interactions via chat, voice, and text. The assistant maintains constant tracking throughout the purchase cycle, integrating real-time behavioral data, current warehouse capabilities, and active marketing data to provide relevant product recommendations.

Enterprise systems often struggle when promotional campaigns generate demand that physical inventory cannot meet. Frontend interfaces that are not synchronized with backend warehouse systems can block digital purchases. Consumers, after clicking on promotional emails, often face stockouts when validating their carts. Fulfillment updates can also experience delays, leaving support agents without a complete overview of the situation. The joint solution from SAP and Google Cloud aims to correct these systemic dysfunctions in the customer experience.

Towards a Unified Customer Experience

Rather than managing disconnected touchpoints, this new architecture unifies the entire process. Traditional business configurations often force consumers to re-enter information already provided. Additionally, support staff often lack access to unified records, complicating problem resolution. The integration proposed by SAP and Google Cloud aims to eliminate these operational breaks, ensuring that the system instantly recognizes the user and their context across all digital platforms.

Bidirectional Data Flows for Increased Accuracy

Marketing execution requires highly accurate data pipelines. SAP Engagement Cloud partners with Google Cloud to create a multi-agent autonomous framework. The technical foundation relies on SAP Business Data Cloud Connect for Google BigQuery. This deployment is based on bidirectional, copy-free data links, secured by strict administrative controls. By keeping vast data stores in place rather than duplicating them, storage costs and network latency are reduced.

BigQuery ingests real-time variables such as weather conditions, precise locations, and active advertising interaction rates. SAP Customer Experience solutions provide internal behavioral context, tracking customer profiles, exact transaction histories, specific service interactions, and consented engagement records. SAP Engagement Cloud activates combined intelligence, deploying autonomous agents to orchestrate personalized interactions throughout the customer lifecycle.

Immediate Stock Synchronization

Routing information through the Business Data Cloud, while BigQuery manages the logic, enforces immediate stock synchronization. The Shopping Assistant actively queries warehouse records in real-time before displaying a product. The software checks physical supply against consumer demands, confirming availability before making a suggestion.

Generative Execution in Production Environments

Advanced generative models dictate the localized output of marketing campaigns. Google Gemini models, including specifically the Nano Banana 2 iteration, provide specialized agentic skills. The models dynamically generate localized messages, personalized images, and campaign variations based on the exact specifications provided by the bidirectional data flow.

The deployment enhances standard text messages into immersive and interactive interfaces via Google Rich Communication Services. Advertising creations continuously evolve based on incoming engagement data. The system processes the interaction, evaluates the response against the user profile, and instructs the Nano Banana 2 model to adjust the next communication.

Towards Increased Marketing Efficiency

Marketing departments achieve high efficiency by abandoning manual execution. Instead of configuring rigid campaign parameters, teams set business objectives and provide access to enterprise data in the SAP Engagement Cloud. Autonomous agents coordinate the necessary steps, segmenting audiences based on Google BigQuery analytics and generating specific content variations through Google Gemini models.

Assessing the Impact of the Infrastructure

The deployment of the architecture restructures standard business operations. Consumers dictate their purchase intent to search engines and conversational interfaces. Integrated AI agents process intent, navigate the connections of the Universal Commerce Protocol, and finalize the purchase directly against the enterprise backdrop.

Retailers retain full ownership of the customer relationship, even if the transaction occurs in a third-party environment. The architecture captures consented engagement data, returning transaction history to SAP Customer Experience solutions. The system updates the localized customer profile, providing Google Gemini models with fresh context before the next engagement cycle.

The system continuously improves campaign performance without requiring direct human intervention. The multi-agent framework evaluates the success of a text message generated by Rich Communication Services, adjusting variables before the next automated send.