Introducing SAP Business Data Cloud
Outlining Finance Use Cases in SAP Business Data Cloud

Supporting Business AI

Objective

After completing this lesson, you will be able to describe how BDC provides a trusted data foundation to power AI applications

Introduction

Selina has now successfully established SAP Business Data Cloud at RaiLona Inc., creating a unified data foundation that integrates information from across the organization. Now she faces her next challenge: to unlock SAP Business AI's full potential provided through SAP Business Data Cloud.

In this lesson, you'll discover how SAP Business Data Cloud works as a Key component to support SAP Business AI and understand how it seamlessly integrates with the underlying data architecture to deliver actionable AI insights.

SAP Business Data Cloud supports SAP Business AI

Support the Flywheel Effect

SAP BDC is the backbone of AI by providing a single source of trusted data from across the entire enterprise.

SAP BDC plays a key role in the flywheel effect. The flywheel builds momentum from continuous rotation across three layers: applications + data + AI to drive innovation, boost productivity and ensure sustainable growth. SAP BDC provides the data layer in the flywheel.

Diagram illustrating the flywheel effect in SAP Business Data Cloud, showing a continuous cycle across three interconnected layers: Applications, Data, and AI. The cycle begins with source applications providing data to SAP BDC, which generates data products. These data products train AI agents and support SAP Joule. AI-generated insights are then re-consumed by source applications to optimize business processes, creating continuous rotation that builds momentum and generates increasing value with each cycle.

The cycle begins when source applications provide the data that is used to generate data products in SAP BDC. The data products are then used to train AI agents and to support SAP's co-pilot, Joule. The insights generated by AI are then re-consumed by the source applications to optimize business processes and outcomes. This cycle does not stop, and with each rotation, higher value is generated.

Provide SAP Joule with Enterprise-wide Data

Diagram showing five use cases for SAP Business Data Cloud in AI development. The visual displays five cards arranged horizontally: Joule (highlighted with a purple border on the left), AI Agents, Embedded AI, Knowledge Graph, and AI Engineering. Each card contains a brief description of its purpose in the AI ecosystem.

Joule is the co-pilot that supports the business user by returning answers to questions that have been asked using natural language. Joule uses data products from SAP BDC plus it refers to the SAP Knowledge Graph to ground the results.

Diagram showing four types of Joule use cases through mobile interface mockups. From left to right: Informational (Tell me how… - displaying explanatory text about creating calculated dimensions), Navigational (Show me where… - showing employee position details with a visual illustration and approval request), Transactional (Do this task… - presenting a script creation interface for switching story charts between YTD and current month with key problem details listed), and Analytical (Provide me insights… - displaying a horizontal bar chart showing top 3 product sales data in USD with values around 86.46). Each mockup demonstrates conversational AI interactions for different business user needs.

Joule is a key interface for the business user as they increasingly move towards conversational interactions to complete their tasks. Joule can be used in a variety of ways such as:

  • Informational - help me to do something
  • Navigation - help me to find locate data or apps
  • Transactional - help to to create something
  • Analytical - help me to understand something

Joule also plays a key role in orchestrating AI agents. For example, a business user's request through Joule can trigger multiple AI agents to begin working performing various tasks in the system. Joule ensures that the AI agents work together to provide the optimal outcome.

In many of these interactions with Joule, access to high-quality, trusted, enterprise-wide data is needed. That is where SAP BDC plays an important role by providing data products that include business data and associated semantics.

Support AI Agents

Diagram showing five use cases for SAP Business Data Cloud in AI development. The visual displays five cards arranged horizontally: Joule, AI Agents (highlighted with a purple border), Embedded AI, Knowledge Graph, and AI Engineering. The AI Agents card describes increasing efficiency with specialized AI agents to perform tasks autonomously across enterprises.

AI agents carry out tasks in the system either triggered by human interaction using Joule, or triggered by other agents.

When agents work together the power of AI is exponentially increased.

Diagram illustrating Joule orchestrating different types of AI agents across end-to-end processes. At the top, a purple banner shows Joule as the new super worker coordinating agents, with bidirectional arrows connecting to Analytics agents in the center, flanked by CX agents, Supply chain agents, HR agents, Spend agents, and Finance agents. Below are four example agent types listed: Story Creation Agent, Coding Agent, Analytical Insights Agent, and Planning Agent, each represented with an icon in white rounded rectangular boxes.

There are many different types of AI agents that work autonomously to achieve a desired outcome.

But regardless of their task, most AI agents need access to high quality business data to support their actions. SAP BDC provides the data from across the enterprise that the AI agents require to make the best decisions.

SAP BDC provides the data the powers agentic AI.

Infusing AI in Analytics and Planning

Diagram showing five use cases for SAP Business Data Cloud in AI development. The visual displays five cards arranged horizontally: Joule, AI Agents, Embedded AI (highlighted with a purple border in the center), Knowledge Graph, and AI Engineering. The Embedded AI card describes accelerating planning and analytics workflows by benefiting from infused AI features and capabilities.

Analytical applications embed AI to provide insights so that the business user can work more effectively.

Screenshot of an SAP analytics dashboard showing overdue purchase order items with embedded AI capabilities. The left side displays a bar chart comparing open PO net value and number of overdue items by supplier across different calendar years (2025). On the right side, a Report Summary panel generated by SAP Business AI provides key insights including concentrated supplier risks and chronic overdue items, along with highlights and anomalies section identifying the worst performing supplier. A blue disclaimer banner at the top notes that AI-generated content may contain inaccuracies and should be verified before using.

For example, AI can summarize complex dashboards and highlight key insights that might otherwise be missed.

SAP BDC provides embedded AI with the essential business data and meta data it needs to generate these insights.

Developing Powerful Knowledge Graphs

Diagram showing five use cases for SAP Business Data Cloud in AI development. The visual displays five cards arranged horizontally: Joule, AI Agents, Embedded AI, Knowledge Graph (highlighted with a purple border), and AI Engineering. The Knowledge Graph card describes understanding data and their relationships and transforming them into business knowledge.

A knowledge graph captures business data and its meta data to build intelligence that is used to ground results generated from AI.

Network diagram illustrates a knowledge graph structure with interconnected business entities. On the left, a purple Joule icon connects to a light blue network of nodes and relationships. On the right side, five key business entities are highlighted in blue boxes: Customer (at the top), Sales Order, Invoice, Product, and Location. These entities are connected through labeled relationships such as placed by, created by, and delivered to, demonstrating how the knowledge graph forms connections between business data to generate facts and support AI-driven insights.

A knowledge graph connects the business entities to form relationships and generate facts. A knowledge graph learns from the data it is provided with. Joule and AI agents can check facts in the knowledge graph as they generate results, to ensure they are grounded in reality and avoid hallucinations.

SAP BDC data products support the development of knowledge graphs to provide context-rich, factual data.

Support AI Engineering

Diagram showing five use cases for SAP Business Data Cloud in AI development. The visual displays five cards arranged horizontally: Joule, AI Agents, Embedded AI, Knowledge Graph, and AI Engineering (highlighted with a purple border on the right). The AI Engineering card describes gaining new insights by applying data science and building AI/ML models with SAP Business Data Cloud.

SAP BDC plays a key role in AI engineering.

AI engineering is the development of machine learning and AI models by a data scientist.

Layered architecture diagram showing AI engineering capabilities in SAP Business Data Cloud. At the top, Intelligent Applications sits above the Business Data Fabric layer, which contains two components: Data engineering and AI/ML and AI operating system. Below are ten capability boxes arranged in two rows: the top row includes Zero Copy Data Sharing, Unity Catalog, Pro-code Environment, Collaborative Notebook Experience, and Serverless Databricks SQL; the bottom row features Top Frontier AI Model, Built-in Tabular Models, Orchestration, AI Model Training, and AI Model Serving. A dark blue banner at the bottom states Gain new insights by applying data science and building AI/ML models with SAP Business Data Cloud.

SAP BDC provides tooling and run-times for the data scientist. They can choose to use tools and run-times from SAP Databricks, SAP Snowflake or SAP Foundation AI to develop models. The tooling includes a pro-code development environment and ready to use algorithms and models.

SAP BDC data products can be shared with SAP Databricks, SAP Snowflake and SAP AI Foundation for the development of AI/ML models. New data products can be generated from the results of machine learning and AI.

Summary

In this lesson, you learned how SAP BDC supports Business AI. You learned that:

  • SAP BDC is the backbone of AI by providing a single source of trusted data from across the entire enterprise.

  • SAP BDC provides Joule with high-quality, trusted, enterprise-wide data to help provide accurate answers to users' questions and requests.

  • SAP BDC provides the data to power agentic AI.

  • SAP BDC provides embedded AI with the essential data it needs to generate powerful insights.

  • SAP BDC data products support the development of knowledge graphs to provide context-rich factual data.

  • SAP BDC provides tooling for the data scientist to develop models.

Learning

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