SAP and Google Cloud have announced a major expansion of their strategic partnership, unveiling an agentic commerce architecture designed to automate customer engagement, retail operations and marketing workflows through artificial intelligence.
The initiative aims to address one of the biggest challenges facing modern enterprises: fragmented customer data and disconnected digital commerce systems. By combining SAP’s enterprise software ecosystem with Google Cloud’s AI and data capabilities, the companies are building an infrastructure that enables intelligent software agents to execute complex retail and customer experience tasks with minimal human intervention.
The new framework arrives as organizations increasingly prioritize artificial intelligence to improve customer retention, operational efficiency and revenue growth.
AI Becomes Critical for Customer Retention
According to SAP research, 78 percent of businesses now view AI as essential for retaining customers in 2026. Yet many companies continue to struggle with disconnected systems and siloed customer information.
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Add INDYASTORY on GoogleThe study found that:
- Only 37% of businesses share customer data across customer experience platforms.
- Just 39% integrate customer information across CRM systems.
- Many organizations still rely on fragmented technology environments.
These limitations often result in inconsistent customer experiences, inaccurate recommendations and operational inefficiencies.
SAP and Google Cloud believe that solving these issues requires a fundamental redesign of how data, commerce platforms and AI systems interact.
What Is Agentic Commerce?
Agentic commerce refers to a model where AI agents can independently perform commercial tasks on behalf of users and businesses.
Instead of simply responding to commands, these systems can:
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Add INDYASTORY on Google- Understand customer intent
- Search for products
- Verify inventory
- Complete transactions
- Process payments
- Manage customer support interactions
- Optimize marketing campaigns
The goal is to create a seamless commerce experience where AI handles much of the complexity behind the scenes.
Universal Commerce Protocol Powers Automation
At the center of the initiative is SAP Commerce Cloud’s adoption of the Universal Commerce Protocol (UCP).
The protocol standardizes communication between:
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Add INDYASTORY on Google- Retailers
- Commerce platforms
- Payment systems
- AI agents
- Customer engagement tools
By creating a common framework for data exchange, businesses can connect their existing systems to AI-driven channels without extensive redevelopment.
Benefits of the Universal Commerce Protocol
| Feature | Business Impact |
|---|---|
| Standardized Integration | Lower implementation costs |
| Unified Data Exchange | Faster deployment |
| AI Compatibility | Supports autonomous commerce |
| Scalability | Easier onboarding of new services |
| Interoperability | Connects multiple ecosystems |
This architecture enables AI agents to manage the entire shopping process from product discovery to post-purchase support.
Google Gemini Becomes the Shopping Assistant Engine
The partnership integrates Google’s Gemini AI models directly into SAP Commerce Cloud.
The result is a new AI-powered shopping assistant capable of:
- Voice interactions
- Text-based conversations
- Product recommendations
- Personalized shopping journeys
- Real-time customer support
Unlike traditional recommendation engines, the system continuously analyzes customer behavior, inventory levels and promotional activity to generate context-aware suggestions.
Real-Time Commerce Intelligence
The assistant can evaluate:
- Current warehouse inventory
- Consumer preferences
- Purchase history
- Active marketing campaigns
- Product availability
This helps ensure that recommended products are actually available for fulfillment.
Eliminating Common Retail Frustrations
One of the primary goals of the new architecture is to solve long-standing operational problems that affect customer experiences.
Common Challenges Addressed
- Inventory mismatches
- Out-of-stock surprises during checkout
- Delayed fulfillment updates
- Fragmented customer records
- Disconnected support systems
Many retailers currently struggle with synchronization between frontend shopping experiences and backend inventory systems.
Under the new framework, inventory validation occurs before recommendations are displayed, reducing the likelihood of failed transactions.
Unified Customer Experience Across Channels
Traditional commerce systems often force customers to repeatedly provide information across different touchpoints.
The SAP-Google Cloud architecture creates a persistent customer context that follows users throughout their journey.
Key Advantages
✔ Consistent customer profiles
✔ Shared interaction history
✔ Faster issue resolution
✔ Improved personalization
✔ Reduced friction during transactions
Support teams gain access to unified customer records, allowing them to resolve issues more efficiently.
BigQuery and SAP Business Data Cloud Enable Real-Time Insights
The partnership leverages SAP Business Data Cloud Connect for Google BigQuery to create a bidirectional data-sharing framework.
A significant feature of the architecture is its zero-copy data model, which allows systems to access information without creating duplicate datasets.
Benefits of Zero-Copy Data Integration
| Advantage | Outcome |
|---|---|
| Reduced Storage Costs | Lower infrastructure expenses |
| Faster Data Access | Improved responsiveness |
| Lower Latency | Better customer experiences |
| Strong Governance | Enhanced security and compliance |
This approach helps enterprises maintain control of their data while enabling AI-driven decision-making.
External and Internal Data Combined
The architecture merges multiple data sources to improve decision-making.
Google BigQuery Contributes
- Geographic data
- Weather information
- Advertising engagement metrics
- Location intelligence
SAP Customer Experience Provides
- Customer profiles
- Purchase history
- Service interactions
- Consent-based engagement records
Combining these datasets enables highly personalized marketing and commerce experiences.
Multi-Agent Marketing Automation
Another major component of the partnership is SAP Engagement Cloud’s autonomous multi-agent marketing framework.
The system allows AI agents to:
- Analyze audiences
- Create customer segments
- Generate campaign content
- Optimize messaging
- Measure performance
Marketing teams can define business objectives while AI agents handle execution.
This reduces manual workload and accelerates campaign deployment.
Gemini Models Drive Personalized Content Creation
Google Gemini models, including the latest advanced variants, are responsible for generating marketing content.
The AI can create:
- Personalized text messages
- Localized campaigns
- Dynamic visuals
- Audience-specific promotions
- Real-time content variations
As customers interact with campaigns, the models continuously refine future communications based on engagement patterns.
Rich Communication Services Enhance Customer Engagement
The deployment also incorporates Google Rich Communication Services (RCS).
RCS allows businesses to move beyond traditional SMS by delivering:
- Interactive messages
- Product carousels
- Rich media content
- Enhanced customer interactions
Combined with AI-driven personalization, the technology enables more engaging customer communications.
Inventory Synchronization Becomes Automatic
A critical operational improvement is real-time inventory synchronization.
Before recommending products, the Shopping Assistant verifies:
- Stock availability
- Warehouse capacity
- Fulfillment feasibility
This minimizes situations where customers discover products are unavailable after adding them to their cart.
For retailers, this reduces customer dissatisfaction and improves conversion rates.
AI Agents Handle End-to-End Transactions
The architecture supports autonomous transaction execution.
Consumers can express purchasing intent through:
- Search engines
- AI chat interfaces
- Voice assistants
AI agents then navigate commerce systems, complete purchases and update customer records automatically.
This creates a more seamless buying experience while preserving retailer ownership of customer relationships.
Continuous Learning Improves Performance
The system is designed to learn from every interaction.
After each customer engagement, AI agents evaluate:
- Campaign effectiveness
- Conversion rates
- Customer responses
- Product performance
These insights are used to improve future recommendations and communications without requiring manual adjustments.
Industry Impact
The SAP-Google Cloud collaboration reflects a broader shift toward AI-native enterprise systems.
Organizations increasingly seek platforms that can:
- Automate routine tasks
- Improve personalization
- Reduce operational inefficiencies
- Enhance customer satisfaction
- Accelerate revenue growth
Agentic commerce is expected to become a key technology trend as businesses move beyond basic AI chatbots toward fully autonomous workflows.
Outlook
SAP and Google Cloud’s agentic commerce architecture represents a significant evolution in how enterprises manage customer engagement and digital commerce. By combining AI agents, real-time data integration, autonomous marketing capabilities and intelligent commerce workflows, the platform aims to create more connected and efficient retail experiences.
As businesses continue investing in artificial intelligence and digital transformation, solutions that bridge customer data, commerce operations and AI-driven decision-making are likely to play an increasingly important role in the future of enterprise technology.
Source: Bext Reporting and Company Announcements
