Ericsson accelerates its enterprise AI transformation by utilizing SAP Business Data Cloud and business data fabric capabilities. As a result, they are building an intelligent and autonomous enterprise system.
It illustrates the transition of telecom behemoths from legacy business analytics to full-fledged AI operations. These new operations are based on quality business data assets.
SAP Business Data Cloud Powers Ericsson’s AI Transformation
SAP Business Data Cloud underpins Ericsson’s enterprise AI strategy. It uses business data fabric technology to consolidate diverse data sources from across its enterprise systems and cloud infrastructure. In this way, they are integrated into a single data ecosystem. This ecosystem can then be tapped into by AI algorithms and models.
SAP’s business data fabric technology unifies all transactional, analytical and multi-model data environments into one platform. It accomplishes this with SAP HANA Cloud technology, the company says.
The architecture provides context for enterprise AI systems in terms of the relationships between suppliers, customers, internal operations and network infrastructure. Additionally, it ensures governance and regulatory compliance.
As Ericsson’s chief information officer, Malin Persson, highlighted, compute and data can be present in different environments. Meanwhile, business context management happens at SAP Business Data Cloud level to allow faster AI deployments and scaling.
Joule AI Agents and Autonomous Enterprise Operations
One of SAP’s major strategic initiatives for its ecosystem includes deploying Joule AI agents across the business processes. These AI systems will provide automated support in managing and organizing data. They will also conduct business analytics, make strategic decisions, and assist with planning through conversational AI experiences.
Ericsson could leverage this technology to automate and enhance many business activities such as:
- AI-based supply chain optimization
- Network infrastructure planning
- Predictive maintenance and analytics
- Operational decision-making
- Automated workflows
With its experience in deploying AI-enabled supply chain transformation initiatives in collaboration with SAP technologies, Ericsson has already used this technology to make operations more efficient. In addition, it has made them more robust.
The Emergence of Business Data Fabric in Enterprise AI
One of the biggest trends in enterprise AI in recent years is business data fabrics. Traditionally, enterprise companies stored all their data in centralized warehouses. Now, modern enterprises prefer building a business data fabric that connects all dispersed data sources but preserves their business context and governance.
SAP’s latest integrations with Snowflake, Amazon Athena, Google BigQuery, and Microsoft Fabric are proof of this trend.
According to industry analysts, business data fabrics are vital for running modern AI models. This is due to their need for accurate, contextual, and always-up-to-date enterprise data.
AI-Driven 6G Networks at Ericsson
Besides business operations, Ericsson’s enterprise AI strategy also aligns with its ambition to build AI-native 6G network infrastructure. The company has already referred to the future telecommunications infrastructure as an intelligent fabric. In this vision, AI becomes ubiquitous for network architecture and management.
As more and more enterprises adopt AI and as they deploy billions of connected devices with autonomous AI agents and digital twins, AI-powered networks may become imperative for their operations.
In that regard, a combination of SAP’s business data fabric capabilities and Ericsson’s ambitions to build AI native infrastructure can put both companies at the forefront of enterprise innovation.
Why Does It Matter?
The partnership between Ericsson and SAP demonstrates the following trends in enterprise AI:
- AI requires business data layers
- AI enables autonomous enterprise operations
- Business data fabrics replace legacy systems
- AI governance and semantics matter
- Cloud ecosystems are necessary for scaling
As corporations compete in implementing generative and agentic AI solutions, scalable business data fabrics may become key in the future of enterprise AI success.
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