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Introduction: AI in SAP Enterprise Architecture - the rise
AI is playing an increasingly important role in the business world. Companies need to make their processes more efficient and cope with enormous amounts of data (Singla et al., 2024). Many SAP customers are therefore asking themselves which AI technology should best be used when in order to achieve the greatest possible benefit.
SAP offers a variety of AI tools and solutions to help companies optimize their business processes. These include SAP Joule, Embedded AI and the SAP AI Foundation. Another important element is SAP Datasphere, which serves as a central data consolidation layer and enables the integration of SAP and non-SAP data sources. In this blog, we will show you how you can use these technologies in a targeted manner to implement a future-proof and innovative SAP Enterprise Architecture.
What is SAP Enterprise Architecture in the context of AI?
The task of an SAP Enterprise Architect is to align a company's IT architecture in such a way that it optimally supports the strategic business objectives (Scarbrough et al., 2020; LeanIX, n.d.). This includes integrating new technologies such as AI to improve processes and increase business value.
However, the implementation of AI presents companies with challenges: Data must be consolidated, AI models must be trained and integrated into existing systems. This is where the role of the SAP Enterprise Architect comes into play, who maintains an overview of the various AI technologies and plans and manages their use sensibly.
SAP Joule: The AI co-pilot for efficient business processes
SAP Joule is an AI-supported co-pilot that helps companies to automate business processes and make them more efficient. Joule was developed specifically for SAP applications and integrates seamlessly into existing SAP systems. With Joule, companies can optimize their workflows, save time and minimize human error.
Some of the most important areas of application for SAP Joule are
1. Navigation: Joule simplifies navigation within SAP systems. Instead of knowing complicated transaction codes or menu paths, users can give Joule instructions in natural language
2. Transaction: Joule can help with the execution of transactions. Users can give Joule instructions to complete specific tasks.
3. Information: Joule can retrieve information from various SAP systems and data sources and present it in an understandable form. Instead of creating complex reports or searching in tables, users can ask Joule questions
4. Analysis: Joule can help analyze data and provide insights. Users can ask Joule to analyze specific data or identify trends
Benefits of SAP Joule:
- Time savings through automation of routine tasks.
- Improved decision making through data-based insights.
- Seamless integration into existing SAP systems without costly customization.
Companies that use SAP Joule benefit from greater efficiency and can better focus their resources on strategic tasks.
Embedded AI: Integrated AI functions in SAP applications
Embedded AI refers to the AI functions integrated directly into SAP applications. These solutions are specifically designed to improve existing business processes without the need to develop separate AI models or implement additional platforms. Embedded AI is integrated into many SAP products and enables companies to make AI-supported decisions directly within their daily processes (SAP, 2024).
Examples of embedded AI in the SAP landscape:
1. SAP S/4HANA: AI-supported financial planning and analysis, automatic variance detection in reports.
2. SAP SuccessFactors: Intelligent recommendations for applicant profiles and personnel development.
3. SAP Ariba: Optimized supplier evaluations and automated price analyses.
Advantages of embedded AI:
- Fast implementation: No separate AI infrastructure required.
- Process optimization: AI supports users directly in operational business.
- High user-friendliness: AI functions are integrated into familiar user interfaces.
With embedded AI, companies can gradually and pragmatically improve their business processes without having to make major changes to their IT landscape.
SAP AI Foundation: Scalable AI solutions for individual requirements
In contrast to the standardized AI functions of Embedded AI, the SAP AI Foundation enables companies to develop their own, highly specialized AI solutions and integrate them seamlessly into their existing SAP environment. These customized models can be tailored precisely to the individual requirements of each company.
Core functions of the SAP AI Foundation:
1. Machine Learning Operations (MLOps): Tools for developing, deploying and monitoring AI models.
2. Integration into SAP environments: Support for connecting to various SAP systems such as SAP S/4HANA.
3. Scalability: support for large data volumes and complex models that can be executed in the cloud or on-premise.
Application examples for the SAP AI Foundation:
- Predictive models for inventory management and demand planning.
- Customer-specific chatbots for customer service.
- Image and text analysis for the automation of quality controls.
The role of SAP Datasphere in data consolidation
In hybrid architectures where SAP and third-party solutions work together, SAP Datasphere forms a central layer to bundle data streams and make them available for AI models, for example by enabling the execution of Python scripts directly on the virtualized data, eliminating the need for data replication. This facilitates the development of AI applications based on large and diverse data sets
Functions of SAP Datasphere:
- Data integration: linking SAP and non-SAP data sources.
- Data virtualization: Access to data without physically moving it.
- Data quality and governance: Ensuring consistent and high-quality data for AI processes.
By connecting all relevant data sources and providing up-to-date, consistent and reliable data in real time, SAP Datasphere forms the basis for successful AI projects. This enables the optimal use of AI technologies from SAP and third-party providers.
Advantages of SAP Datasphere:
- Real-time data access for quick decisions.
- Integration of data islands for a uniform view of company data.
- Support for hybrid scenarios with cloud and on-premise data sources.
When which AI technology should be used?
Choosing the right AI technology depends heavily on a company's individual requirements and goals. Here is an overview of when SAP Joule, Embedded AI or the SAP AI Foundation are best suited:
1. SAP Joule:
When: For automating routine tasks and supporting users with intelligent recommendations.
Examples: Financial accounting, invoice processing, customer support.
2. Embedded AI:
When: For the optimization of standard processes within existing SAP applications.
applications.
Examples: HR management with SuccessFactors, inventory management with S/4HANA.
3. SAP AI Foundation:
When: For individual AI developments and complex models that have to fulfill specific
requirements must be met.
Examples: Predictive analytics, customer-specific chatbots, quality control with
image analysis.
Companies should first analyze their business processes and data landscape to decide which AI solution offers the greatest added value. A structured approach ensures that AI projects are implemented successfully.
Benefits for companies through intelligent SAP Enterprise Architecture
The integration of AI into SAP Enterprise Architecture offers companies numerous benefits, including
1. Increased efficiency: routine tasks can be automated, allowing employees to focus on strategic tasks.
2. Better decision-making: AI provides real-time data-based insights, leading to more informed decisions
3. Cost reduction: operational costs can be reduced through automation and optimized processes
4. Improved customer experience: AI-supported services and support improve interaction with customers.
AI is changing the rules of the game. In order to remain competitive, companies must adapt their business models to the new requirements and use AI in a targeted manner. Global economic growth through AI is estimated at up to 4.4 trillion US dollars per year (McKinsey&Company, 2023).
Tips for the successful use of AI in SAP architecture
Here are some recommendations for companies looking to integrate AI into their SAP landscape:
1. Start small, scale big: Start with pilot projects and expand gradually.
2. Develop a data strategy: Build a clear data strategy for the consolidation and use of data.
3. Choose the right AI solution: Decide whether SAP Joule, Embedded AI or the AI Foundation is best suited.
4. Involve employees: Conduct training and workshops for employees to create acceptance and understanding of AI.
5. Regularly monitor success: continuously monitor and optimize AI projects.
SAP workshops, such as the SAP Business AI JumpStart, show you how to identify the right AI solutions for your company and integrate them into your SAP landscape. Talk to your Account Executive to find out more.
Conclusion: AI as a driver for modern SAP enterprise architecture
AI is an indispensable component of a modern SAP enterprise architecture. With solutions such as SAP Joule, Embedded AI and the SAP AI Foundation, companies can automate their processes, make data-based decisions and increase their efficiency. SAP Datasphere provides the necessary basis for a consolidated and reliable database. Companies that invest in AI and a future-proof architecture now will secure long-term competitive advantages and be ready for the digital future.
FAQs
1. What is SAP Joule and how does it support companies?
SAP Joule is an AI-powered co-pilot that automates routine tasks and provides users with intelligent recommendations to make business processes more efficient.
2. What is the difference between Embedded AI and SAP AI Foundation?
Embedded AI offers predefined AI functions directly in SAP applications, while the SAP AI Foundation enables the development of individual, scalable AI models.
3. Why is SAP Datasphere important for AI applications?
SAP Datasphere consolidates data from various sources and makes it available for AI models in real time, which is essential for reliable analysis and automation.
4. What challenges are there when introducing AI in SAP systems?
Challenges include data quality, skills shortages, change management and compliance with data protection regulations.
5. How do I start an AI project in the SAP architecture?
Start with a pilot project, develop a clear data strategy, choose the right AI solution and involve employees at an early stage. Contact the manufacturers involved at an early stage to identify the right technology.
Common thread of this blog series:
- Introduction
- Tasks of an Enterprise Architect
- Success Factors for Digital Transformation Projects
- Help of an Enterprise-Architecture-Framework
- Steps and Tips
- Artificial Intelligence Meets Enterprise Architecture
Bibliography:
LeanIX. (o.J.). SAP-Architekt. Retrieved from https://www.leanix.net/de/wiki/tech-transformation/sap-architect
McKinsey & Company. (2023). The Economic Potential of Generative AI. Retrieved from https://www.mckinsey.com/featured-insights/mckinsey-explainers/what-is-generative-ai
SAP. (n.d.). AI Catalog – SAP Discovery Center. Retrieved from https://discovery-center.cloud.sap/ai-catalog/
Scarbrough, M., et al. (2020). Enterprise Architecture with SAP: Planning, Management, and Transformation. Rheinwerk Verlag.
Singla, A., Sukharevsky, A., Yee, L. & Chui, M. (2024, 30. Mai). The state of AI in early 2024: Gen AI adoption spikes and starts to generate value. McKinsey & Company. https://www.mckinsey.com/capabilities/quantumblack/our-insights/the-state-of-ai
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