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Integrate AI into SAP S/4HANA with Intelligent Scenario Lifecycle Management (ISLM)

Introduction

In today’s rapidly evolving digital landscape, Generative AI is transforming how enterprises innovate, automate, and deliver business value . To successfully embed Generative AI within SAP S/4HANA, organizations need more than access to large language models. They require a structured, scalable, and governed framework to integrate, operate, and manage AI use cases across their landscape.

Over the past year, these Generative AI capabilities are now enabled through ISLM, helping customers and partners move from experimentation to productive usage.

ISLM supports integration with the Orchestration Service on SAP AI Core, enabling advanced Generative AI capabilities such as document grounding, content filtering, and data masking. Additional features like input and output translation and a Prompt Shield filter help protect against prompt injection attacks, strengthening security. New API enhancements further improve grounding quality through larger chunk sizes and application-specific document chunking. Together, these capabilities enable standardized, flexible, and enterprise-ready GenAI integration and reinforcing ISLM as the central framework for governing and scaling Generative AI across SAP landscapes.

The following modules within the orchestration service are supported by ISLM : 1. Data Masking – Protects sensitive information by masking or removing confidential data. 2. Input Filtering – Validates and sanitizes incoming data before it is processed by the LLM. 3. Output Filtering – Reviews and filters the LLM-generated output to ensure compliance and relevance. 4. Grounding – Aligns model outputs with enterprise data or domain-specific knowledge to improve response accuracy. 5. Input Translation - Helps translate LLM input into a specified language in which the model may perform better, for example English. 6. Output Translation - Translates LLM responses into your preferred language. 7. Prompt Shield to prevent prompt injection attacks

What You'll Build

Use case

In this scenario, two fictional sports brands like Company Alpha and Company Beta - maintain different return policies with varying eligibility rules, timelines, refund conditions, and exceptions. The Intelligent Scenario automatically extracts and presents a summary of key information—including return criteria, validity timelines, refund processes etc. This reduces the manual effort of support teams by eliminating the need to read lengthy documents, reduces ambiguity and helps in quickly responding to policy related queries.

Customer support teams frequently handle queries such as: - Is this item still eligible for return?”
- Are customized products refundable?”
- How long will the refund take?”
Manually reviewing policy documents is time-consuming and can lead to inconsistent responses.

Using ISLM with orchestration: - Policy documents are uploaded for document grounding.
- User queries are processed through the orchestration workflow.
- The LLM extracts relevant clauses and generates structured responses.

Business Value

  • Reduces manual effort
  • Speeds up response time
  • Ensures consistent policy interpretation
  • Enables automated decision support within business processes

What You'll Learn

End to End implementation of AI in business application in S/4HANA using ISLM.