SAP Expands AI and Data Capabilities to Empower Developers and Accelerate Enterprise Innovation

Global enterprise software leader SAP  SE has introduced a comprehensive range of AI-powered enhancements to its SAP Build solution, alongside new data integration capabilities and intelligent automation features powered by Joule Agents. These innovations are designed to help developers move from idea to impact with unprecedented speed and efficiency, while transforming how enterprises harness data and artificial intelligence.

As AI continues to reshape industries and the nature of work, SAP also announced a major global skills initiative—a pledge to equip 12 million people worldwide with AI-ready skills by 2030. The initiative will expand hands-on training and certification programs, including partnerships with online learning platforms such as Coursera, ensuring professionals are prepared for the demands of an AI-driven economy.

The new capabilities within SAP Build, SAP’s flagship enterprise development and automation platform, provide developers with greater flexibility to build, extend, and automate using their preferred tools and frameworks. Developers using platforms such as Cursor, Claude Code, Cline, Windsurf, or Visual Studio Code can now integrate SAP Build through new Model Context Protocol Servers and extensions. SAP also announced upcoming integrations between Joule Studio agents and n8n agents, allowing intelligent agents to collaborate seamlessly across workflows.

Developers can now use Joule Studio’s agent-building capabilities to extend SAP’s ready-to-use agents or create new ones that act autonomously based on live business data and changing conditions. This enables organizations to automate complex processes and respond intelligently to evolving operational demands.

In the data domain, SAP has expanded its Business Data Cloud ecosystem to give developers more control and connectivity. A new SAP Snowflake solution extension and SAP Business Data Cloud Connect partnership with Snowflake were announced, complementing existing integrations with Databricks and Google Cloud. These developments enable users to choose the most suitable compute and storage options for each AI and data workload while maintaining governance and interoperability.

Additionally, a new data product studio allows developers to transform raw datasets into ready-to-use “data products” optimized for analytics, AI, and application development. Enhancements to the SAP HANA Cloud knowledge graph engine further allow for automatic generation of knowledge graphs that map relationships across data models, unlocking deeper insights into how data interconnects across business systems.

To extend AI autonomy and decision-making, SAP launched its first enterprise relational foundation model, known as SAP-RPT-1 (Relational Pre-trained Transformer). Unlike traditional language models that predict text, SAP-RPT-1 predicts business outcomes such as delivery delays, payment risks, or order completions. The model is now available in a free developer playground for experimentation.

Meanwhile, new AI assistants in Joule are designed to orchestrate multiple agents across departments and applications, bringing intelligence and automation to workflows in finance, supply chain, HR, and beyond. SAP also introduced new agents for technical users, such as those focused on business process analysis, to identify inefficiencies and uncover opportunities for optimization.

Through these innovations, SAP continues to position itself at the forefront of the enterprise AI revolution, empowering developers and businesses alike to harness the full potential of data, automation, and machine intelligence—while ensuring that people everywhere are equipped with the skills to thrive in the digital future.