SAP Expands Business AI Capabilities with Q4 2025 Release

SAP introduced new models, sovereign cloud offerings, product updates, and partnerships in the fourth quarter of 2025. The updates are aimed at helping customers derive greater value from AI while addressing barriers such as integration complexity, regulatory compliance, AI sovereignty, and data quality, Philipp Herzig, CTO of SAP SE, said in a blog post.

With these releases, SAP continues to embed AI into its enterprise portfolio to support data-driven operations while simplifying the underlying data landscape. The company positioned the latest updates as part of a broader effort to remove adoption barriers and provide customers with AI capabilities grounded in business context.

A central focus is enabling organizations to use AI against structured enterprise data without requiring multiple specialized models, while maintaining compliance and infrastructure control.

The release includes the SAP-RPT-1 forecasting model, the EU AI Cloud, expanded data-sharing capabilities with Snowflake through SAP Business Data Cloud, and broader availability of AI agents and skills embedded across SAP applications.

New AI Models, Sovereign Cloud, and Data Integration Updates

As part of the Q4 2025 release, SAP introduced SAP-RPT-1, an AI model designed to forecast business data stored in tables by predicting the next value in a row. SAP-RPT-1-small and SAP-RPT-1-large are available through the Generative AI Hub.

SAP also launched the EU AI Cloud, a sovereign cloud built to keep data within the European Union. Customers can deploy it in SAP data centers, on approved European infrastructure, or as a fully managed environment in their own operations.

“Our goal is for customers to realize value with AI solutions,” wrote SAP CTO Philipp Herzig, adding that SAP is focused on removing barriers such as integration complexity, regulatory requirements, AI sovereignty, and data quality.

SAP is also expanding enterprise data integration through SAP Business Data Cloud with a new partnership with Snowflake. The integration supports bidirectional data sharing without duplication, enabling real-time access to combined SAP and third-party data while maintaining business context.

SAP Snowflake is expected to reach general availability in the first quarter of 2026, with SAP Business Data Cloud Connect for Snowflake scheduled for the first half of the year.

AI Agents Move Deeper into Operational Workflows

SAP is extending Joule across core business applications, positioning the assistant closer to day-to-day operational workflows. The quarter also introduced reciprocal integration with Microsoft 365 Copilot, intended to create a more consistent user experience across productivity and enterprise systems.

Through SAP’s Generative AI Hub, customers can access models from Mistral, OpenAI, Gemini, and Anthropic based on specific use cases.

Many of the updates focus on automating routine tasks and improving decision support within existing processes rather than introducing standalone tools.

In supply chain operations, updates to SAP Integrated Business Planning translate complex optimization, inventory, and forecasting outputs into natural-language summaries.

A new Production Planning and Operations agent checks manufacturing prerequisites, identifies material shortages, and recommends alternatives.

For HR teams, the Performance Preparation agent gathers relevant data ahead of manager-employee discussions and proposes talking points. Skills inference from resumes is designed to help organizations better match employees to internal opportunities.

Finance-related agents target process-heavy activities such as accruals management, trade classification for cross-border shipments, and cash-flow monitoring.

Joule also supports governance and risk-related tasks, including master data and settlement analysis.

Agent Development Expands Across IT and Business Functions

For IT teams, Agent Builder in Joule Studio is now generally available, allowing organizations to create custom agents for multi-step processes. SAP LeanIX provides a centralized location to manage these agents, while foundation models such as SAP-RPT-1 and SAP-ABAP-1 support structured data forecasting and ABAP code generation.

In spend management and customer-facing functions, new agents assist with travel booking recommendations, receipt analysis, procurement requests through SAP Ariba, and statement-of-work creation in SAP Fieldglass. Marketing teams can generate reports in SAP Emarsys using prompts, and service teams can use AI-generated summaries to respond to billing inquiries.

The blog post included a disclaimer noting that projected business benefits are estimates based on SAP benchmarks, customer case studies, and research, and that actual results may vary.

What This Means for SAPinsiders

Forecasting models are becoming enterprise-native. SAP-RPT-1 reflects a move toward AI optimized for structured business data rather than generalized models. This approach aligns forecasting more closely with transactional systems and operational planning processes.

Sovereign cloud is shaping AI deployment strategies. The EU AI Cloud highlights growing demand for data residency and infrastructure control. Regulatory pressures are increasingly influencing where and how enterprise AI runs.

Unified data platforms are central to AI execution. The SAP Business Data Cloud and Snowflake integration underscores the importance of real-time access to semantically rich data. AI effectiveness is increasingly tied to consolidated enterprise data environments.