This page provides a structured overview of the official syllabus for the SAP Certified - SAP Generative AI Developer certification exam. The SAP C_AIG certification evaluates applied knowledge and implementation understanding within the SAP AI Core environment. Candidates preparing for this certification are expected to understand configuration concepts, integrated business processes, and the reasoning patterns required to make implementation decisions within real SAP environments.
The syllabus outline below summarizes the major competency domains associated with the SAP Generative AI Developer certification and reflects the topics typically covered in the official SAP learning journey. Reviewing these areas helps candidates understand the knowledge domains, exam structure, and preparation scope that guide study for the SAP C_AIG certification exam. Modern SAP certification exams emphasize scenario-based reasoning, decision-making, and system behavior interpretation rather than isolated topic knowledge.
SAP C_AIG Certification Exam Summary
| Exam Name | SAP Certified - SAP Generative AI Developer |
| Exam Code | C_AIG » SAP Generative AI Developer Certification Practice Exam |
| Certification Level | Associate |
| Exam Format | System Based Assessment |
| Exam Duration | 120 minutes |
| Passing Score | 100% |
| Exam Price | $578 (USD) |
| Product | SAP AI Core |
| Certification Validity | 12 months (mandatory yearly renewals) |
| Official Exam Registration | SAP Learning Certification Portal |
| Sample Questions | SAP C_AIG Certification Sample Questions |
SAP C_AIG Learning Journey and Preparation Resources
SAP provides structured learning journeys through the SAP Learning platform that guide candidates through recommended courses, hands-on exercises, and supporting materials for each certification. The official learning journey for the C_AIG certification outlines the topics, system capabilities, and implementation practices expected from professionals preparing for the SAP Certified - SAP Generative AI Developer certification. Candidates can review the official SAP C_AIG learning journey to explore the complete training path recommended by SAP.
| Type | Title | Description |
|---|---|---|
| Course | Discovering SAP Business AI |
This course provides an understanding of how SAP Business AI delivers real-world business value by helping organizations automate processes, make smarter decisions, and innovate faster. SL_BAI101
|
| Course | Navigating Large Language Models fundamentals and techniques for your use case |
This course introduces you to the fundamentals of Large Language Models (LLMs) and their practical use in business scenarios. You’ll learn how LLMs work, their strengths and limitations, and how to apply them responsibly within SAP environments. The course emphasizes real-world techniques for integrating, optimizing, and evaluating LLM-powered solutions to solve enterprise challenges. AIG01
|
| Course | Discovering SAP's Generative AI Hub |
This course introduces you to SAP’s generative AI hub, the central platform for secure and scalable enterprise AI. You will learn how the hub enables access to advanced language models, supports prompt management, and orchestrates intelligent workflows. The focus is on practical tools and interfaces that help you build, deploy, and govern AI solutions for your business. AIG00
|
| Course | Solve your business problems using prompts and LLMs in SAP Generative AI Hub |
This course guides you through solving real business problems using prompts and Large Language Models in SAP’s generative AI hub. You will learn how to design, refine, and manage prompts, leverage the Prompt Registry and Templates, and integrate LLMs into enterprise workflows using SAP Cloud SDK for AI. The course emphasizes practical techniques for prompt engineering, evaluation, and model selection to build reliable, scalable AI solutions. AIG02
|
| Course | Using Advanced AI Techniques with SAP's Generative AI Hub |
This course introduces you to the grounding technique in SAP’s generative AI hub, showing how to connect Large Language Models with your organization’s trusted data for accurate, context-aware responses. You will learn the fundamentals of document grounding, vector embeddings, and the SAP HANA vector engine, and see how these tools can be used to solve real business problems. The course emphasizes practical steps for building, configuring, and deploying grounded AI solutions that enhance reliability and business value. AIG03
|
Core Skills Measured in the SAP C_AIG Exam
The SAP C_AIG certification measures whether candidates can apply development-oriented skills to real implementation situations in SAP AI Core and the broader SAP Generative AI Hub environment. In practice, this means more than recognizing terms such as prompt engineering, workflow orchestration, or grounding. Candidates are expected to understand how prompts, models, templates, orchestration flows, and enterprise data work together, and how those choices affect system behavior. The SAP Certified - SAP Generative AI Developer certification also evaluates platform-level judgment. Candidates need to interpret technical scenarios, choose an implementation approach that fits the requirement, and recognize why an alternative action may be weaker because it does not align with workflow logic, model behavior, governance expectations, or enterprise data usage. The focus remains on applied reasoning, execution decisions, and reliable solution design.
Core Knowledge Areas Covered
The SAP C_AIG certification covers a set of connected knowledge domains rather than isolated feature topics. One major area is SAP Business AI and enterprise AI value context, which helps candidates understand where generative AI fits within SAP environments and why solution choices must support business use cases. Another area is Large Language Model behavior, including capabilities, limitations, evaluation, risk awareness, and responsible use in enterprise settings. The syllabus also covers platform architecture and operational capabilities within SAP’s generative AI hub, including model access, orchestration services, prompt tooling, and integration with SAP AI Core and AI Launchpad. Beyond that, the SAP C_AIG exam includes prompt design and optimization, model selection, workflow execution, grounding methods, vector-based knowledge handling, and solution evaluation. Together, these domains support the exam’s emphasis on implementation reasoning, system interpretation, and technically sound decision-making.
Understanding the SAP C_AIG Certification Scope
The SAP C_AIG exam is a System-Based Assessment, so the certification scope is defined by what candidates can do with knowledge, not by how many facts they can recall. The SAP C_AIG certification expects candidates to make applied implementation decisions in realistic SAP environments where prompts, orchestration flows, models, and grounded enterprise data must work together. Correct answers depend on understanding what the system is doing, what the requirement demands, and which action best fits that context. This means the SAP Certified - SAP Generative AI Developer certification evaluates reasoning across multiple interacting domains. A scenario may require candidates to interpret workflow behavior, artifact usage, model choice, or grounding design at the same time. Success therefore depends on understanding dependencies and system behavior, not on treating the syllabus as a static topic list. The exam is designed to reflect practical technical work in SAP AI Core and SAP’s generative AI hub.
Recommended SAP Learning Path
SAP’s learning journey for the SAP C_AIG exam follows a clear progression from foundational understanding to applied implementation. It begins with the business context of SAP Business AI and then builds into Large Language Model fundamentals, including strengths, limitations, enterprise fit, and responsible use. This creates the conceptual base needed before candidates move into the product-specific capabilities of SAP’s generative AI hub. From there, the path becomes more execution-oriented. Candidates progress into prompt development, template and registry management, orchestration workflows, and SAP Cloud SDK for AI usage, then continue into more advanced grounding techniques using enterprise data. The hands-on practice component is important because it reinforces how these topics come together in SAP AI Launchpad. For the SAP C_AIG certification, the learning path is designed to move from understanding concepts to applying them in realistic development scenarios.
Preparation Guidance for the SAP C_AIG Exam
Preparation for the SAP C_AIG certification should begin with structured coverage of the official SAP learning journey and its related course sequence. Candidates should first build topic-level understanding in SAP Business AI concepts, Large Language Model fundamentals, platform architecture, and generative AI hub capabilities before moving into more detailed areas such as prompt engineering, orchestration, grounding, and model evaluation. This creates the foundation needed for higher-quality implementation decisions later in preparation. After that, preparation should shift toward applied practice. Candidates should work through scenarios that require interpretation of workflow behavior, model and prompt choices, and enterprise data grounding so they can develop consultant-style decision-making ability. Hands-on work in SAP AI Launchpad or similar guided exercises is especially useful because it helps connect concepts to system behavior. The strongest preparation for the SAP C_AIG exam combines foundational study, scenario-based practice, and validation-focused review so that candidates understand why an implementation choice works and why other options may not.
Preparing for the SAP Generative AI Developer
Candidates preparing for the SAP SAP Certified - SAP Generative AI Developer exam can also explore structured preparation resources, including the SAP C_AIG practice exam platform, the sample SAP C_AIG questions, and the SAP C_AIG exam FAQs. These resources help candidates understand exam expectations, develop scenario-based reasoning, and build the decision-making and validation skills required for modern SAP certification exams.
