SAP has introduced a network of role-aware AI assistants designed to act as a coordinating layer across various enterprise functions, moving away from the concept of AI as a standalone tool. These assistants, integrated within the Joule platform, are tailored for specific business roles, utilizing libraries of specialized agents to automate workflows and orchestrate responses across different departments.
This initiative positions the SAP Business Suite as a central platform where AI, data, and applications converge to create what the company terms “self-reinforcing intelligence.” The architecture separates the coordination of tasks from their execution. Role-aware assistants manage a collection of specialized Joule Agents, allowing users to concentrate on decision-making rather than the minutiae of task management. This approach aims to provide a more integrated and efficient way for businesses to handle the complexities of modern operations, particularly in a volatile economic environment.
Coordinating Specialized Agents
The core of SAP’s new AI strategy lies in the interaction between Joule assistants and a growing library of specialized agents. Each assistant is designed to partner with users in specific business roles, such as a People Manager or a Financial Planner, by configuring and orchestrating these agents. For instance, the People Manager Assistant can coordinate with a People Intelligence Agent to identify and resolve issues like compensation anomalies, drawing on data from across the SAP Business Suite to support performance management workflows.
In the financial sector, a Financial Planning Assistant might work with a Cash Management Agent to optimize cash flow and improve interest yields. These assistants can operate both within individual lines of business and across multiple enterprise functions to address complex requirements that span different departments. The architecture is designed to be flexible, allowing agents to be reconfigured and redeployed based on the specific needs of each role. This eliminates the need for users to manually coordinate multiple AI tools, with the assistants handling the orchestration of agents for specific jobs.
Function-Specific Tools
The Joule Agents themselves are function-specific tools designed to execute workflows within particular domains like human resources, finance, and supply chain management. These agents have access to business-critical context from SAP applications, including transactional data and operational information that general-purpose AI models typically lack. This deep integration with enterprise data allows the agents to perform specialized tasks, such as compensation analysis or cash flow optimization, with a high degree of accuracy and relevance. The assistants then coordinate these agents, orchestrating responses across multiple functions when a task requires input from different parts of the business.
Unlocking Enterprise Data for AI
A key component of this new AI ecosystem is the SAP Business Data Cloud Connect, which links the SAP Business Data Cloud with partner platforms such as Databricks and Google Cloud. This system facilitates a bidirectional flow of data products across organizational boundaries, addressing a common constraint in enterprise AI where data is often siloed in individual systems. The technology utilizes zero-copy sharing, which means data remains within SAP systems while becoming accessible to customers’ existing data platforms. This approach maintains the business context of the data without the need for duplication or complex data loading pipelines.
For AI applications, this provides access to business-ready data products that retain their semantic meaning and the relationships present in the operational systems. Databricks and Google Cloud are the first partners to be enabled for SAP BDC Connect, with plans for additional partnerships in the future. This extended capability allows customers to use their data products for analytics and AI training without the need to extract and transform data from their SAP systems, streamlining the process of developing and deploying AI models.
Strategic Partnerships and Timeline
The development of the SAP Business Data Cloud has been a strategic process. In February 2025, SAP announced the Business Data Cloud and SAP Databricks as a data service within it. By October 2025, the company launched SAP Business Data Cloud Connect, enabling bidirectional data sharing with partner platforms. The initial partnerships with Databricks and Google Cloud are a significant step in creating a more open and interconnected data ecosystem for enterprise AI.
A New Architecture for Enterprise AI
SAP’s role-based AI architecture represents a departure from general-purpose AI models. By connecting assistants to libraries of specialized agents, SAP provides AI capabilities that can execute function-specific workflows with a high degree of precision. These agents leverage the transactional data and operational information within SAP applications to inform their outputs, a level of context that is often missing from more generic AI solutions. The assistants then act as a coordinating layer, managing these agents and orchestrating responses across multiple functions as needed.
This architecture positions AI as a layer that sits between users and their enterprise applications, managing the complexity of multi-step workflows across different departments. Muhammad Alam, a member of the Executive Board of SAP SE and head of SAP Product & Engineering, stated that these developments demonstrate the power of the SAP Business Suite, where AI, data, and applications come together to “propel smarter decisions, faster execution and scalable transformation.”
Implications for Business Operations
The introduction of role-based AI assistants has significant implications for how businesses operate. By automating and orchestrating complex workflows, these assistants can free up employees to focus on more strategic and high-value activities. The ability to draw on data from across the enterprise allows for more informed decision-making, while the specialized nature of the Joule Agents ensures that the AI’s outputs are relevant and actionable. This approach has the potential to improve efficiency, reduce errors, and enhance overall business performance.
For example, in supply chain management, an assistant could coordinate agents to analyze demand forecasts, check inventory levels, and even initiate purchase orders, all while keeping relevant stakeholders informed. In human resources, an assistant could help with talent acquisition by identifying suitable candidates, scheduling interviews, and managing the onboarding process. The cross-functional capabilities of the assistants mean they can handle complex processes that have traditionally required manual intervention and coordination between different departments.
Future of Integrated AI
The launch of these role-based AI assistants and the supporting data infrastructure marks a significant step towards a more integrated and intelligent enterprise. As the library of Joule Agents continues to grow, the capabilities of the assistants will expand, covering an ever-wider range of business functions. The open nature of the SAP Business Data Cloud Connect also suggests a future where a broader ecosystem of partners and developers can contribute to this AI-driven vision of the enterprise.
The success of this approach will depend on several factors, including the ease of use of the assistants, the robustness of the underlying AI models, and the willingness of businesses to adopt this new way of working. However, by focusing on the practical application of AI to solve real-world business problems, SAP has laid a strong foundation for the future of enterprise AI.
