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C_AIG_2404
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C AIG AI GenAI (C_AIG_2404)

The C_AIG_2404 certification teaches SAP professionals how to design, train, and deploy AI and generative AI solutions using SAP AI Core, Launchpad, and Generative AI Hub, emphasizing prompt engineering and performance monitoring.

180
Minutes
80
Questions
65
Passing Score
$250
Exam Cost

Who Should Take This

It is intended for SAP consultants, solution architects, and data scientists with at least two years of experience in SAP ERP or S/4HANA who want to expand their expertise into AI-driven automation and customer experience. Learners aim to certify their ability to implement SAP AI strategies, build ML models, and monitor AI performance across enterprise scenarios.

What's Covered

1 Domain 1: Sap Ai Strategy
2 Domain 2: Ml Model Training
3 Domain 3: Ai-Powered Automation Scenarios
4 Domain 4: Ai In Customer Experience
5 Domain 5: Ai Performance Monitoring

What's Included in AccelaStudy® AI

Adaptive Knowledge Graph
Practice Questions
Lesson Modules
Console Simulator Labs
Exam Tips & Strategy
20 Activity Formats

Course Outline

62 learning goals
1 Domain 1: Sap Ai Strategy
2 topics

Sap Ai Strategy

  • Identify the key components, configuration options, and standard process flows for SAP AI strategy and portfolio within the SAP ecosystem
  • Configure SAP AI strategy and portfolio settings including parameters, organizational assignments, and integration points for operational deployment
  • Analyze SAP AI strategy and portfolio effectiveness using standard metrics and recommend configuration improvements for optimization
  • Identify the key sap ai strategy components, terminology, and standard configuration options available in the SAP system
  • Configure sap ai strategy parameters including relevant settings, thresholds, and control indicators for production readiness

Ai Core Service Configuration

  • Identify the key components, configuration options, and standard process flows for AI Core service configuration within the SAP ecosystem
  • Configure AI Core service configuration settings including parameters, organizational assignments, and integration points for operational deployment
  • Analyze AI Core service configuration effectiveness using standard metrics and recommend configuration improvements for optimization
  • Identify the key components, configuration options, and standard process flows for AI Launchpad management within the SAP ecosystem
  • Configure AI Launchpad management settings including parameters, organizational assignments, and integration points for operational deployment
  • Analyze AI Launchpad management effectiveness using standard metrics and recommend configuration improvements for optimization
  • Configure monitoring and alerting for ai core service configuration processes using standard SAP tools and threshold-based notifications
  • Analyze ai core service configuration performance metrics and KPIs to identify bottlenecks, inefficiencies, and optimization opportunities
2 Domain 2: Ml Model Training
2 topics

Ml Model Training

  • Identify the key components, configuration options, and standard process flows for ML model training and deployment within the SAP ecosystem
  • Configure ML model training and deployment settings including parameters, organizational assignments, and integration points for operational deployment
  • Analyze ML model training and deployment effectiveness using standard metrics and recommend configuration improvements for optimization
  • Configure ml model training parameters including relevant settings, thresholds, and control indicators for production readiness
  • Assess the impact of ml model training changes on downstream processes, reporting accuracy, and cross-module integration

Generative Ai Hub Configuration

  • Identify the key components, configuration options, and standard process flows for generative AI hub configuration within the SAP ecosystem
  • Configure generative AI hub configuration settings including parameters, organizational assignments, and integration points for operational deployment
  • Analyze generative AI hub configuration effectiveness using standard metrics and recommend configuration improvements for optimization
  • Identify the key components, configuration options, and standard process flows for prompt engineering practices within the SAP ecosystem
  • Configure prompt engineering practices settings including parameters, organizational assignments, and integration points for operational deployment
  • Analyze prompt engineering practices effectiveness using standard metrics and recommend configuration improvements for optimization
  • Implement generative ai hub configuration data validation rules, consistency checks, and error handling procedures for data quality assurance
  • Identify the key generative ai hub configuration components, terminology, and standard configuration options available in the SAP system
3 Domain 3: Ai-Powered Automation Scenarios
2 topics

Ai-Powered Automation Scenarios

  • Identify the key components, configuration options, and standard process flows for AI-powered automation scenarios within the SAP ecosystem
  • Configure AI-powered automation scenarios settings including parameters, organizational assignments, and integration points for operational deployment
  • Analyze AI-powered automation scenarios effectiveness using standard metrics and recommend configuration improvements for optimization
  • Implement ai-powered automation scenarios workflows including approval routing, escalation rules, and notification settings for process automation
  • Name the integration points between ai-powered automation scenarios and other SAP modules including data flows and triggering events

Embedded Ai In S/4Hana

  • Identify the key components, configuration options, and standard process flows for embedded AI in S/4HANA within the SAP ecosystem
  • Configure embedded AI in S/4HANA settings including parameters, organizational assignments, and integration points for operational deployment
  • Analyze embedded AI in S/4HANA effectiveness using standard metrics and recommend configuration improvements for optimization
  • Identify the key components, configuration options, and standard process flows for AI in SuccessFactors within the SAP ecosystem
  • Configure AI in SuccessFactors settings including parameters, organizational assignments, and integration points for operational deployment
  • Analyze AI in SuccessFactors effectiveness using standard metrics and recommend configuration improvements for optimization
  • Evaluate embedded ai in s/4hana configuration decisions against business requirements and recommend improvements for process optimization
4 Domain 4: Ai In Customer Experience
2 topics

Ai In Customer Experience

  • Identify the key components, configuration options, and standard process flows for AI in Customer Experience within the SAP ecosystem
  • Configure AI in Customer Experience settings including parameters, organizational assignments, and integration points for operational deployment
  • Analyze AI in Customer Experience effectiveness using standard metrics and recommend configuration improvements for optimization
  • Analyze ai in customer experience performance metrics and KPIs to identify bottlenecks, inefficiencies, and optimization opportunities
  • Implement ai in customer experience workflows including approval routing, escalation rules, and notification settings for process automation

Responsible Ai Governance

  • Identify the key components, configuration options, and standard process flows for responsible AI governance within the SAP ecosystem
  • Configure responsible AI governance settings including parameters, organizational assignments, and integration points for operational deployment
  • Analyze responsible AI governance effectiveness using standard metrics and recommend configuration improvements for optimization
  • Identify the key components, configuration options, and standard process flows for AI model lifecycle management within the SAP ecosystem
  • Configure AI model lifecycle management settings including parameters, organizational assignments, and integration points for operational deployment
  • Analyze AI model lifecycle management effectiveness using standard metrics and recommend configuration improvements for optimization
  • List the standard responsible ai governance reports, monitoring tools, and diagnostic transactions available for operational oversight
5 Domain 5: Ai Performance Monitoring
2 topics

Ai Performance Monitoring

  • Identify the key components, configuration options, and standard process flows for AI performance monitoring within the SAP ecosystem
  • Configure AI performance monitoring settings including parameters, organizational assignments, and integration points for operational deployment
  • Analyze AI performance monitoring effectiveness using standard metrics and recommend configuration improvements for optimization
  • Describe the ai performance monitoring process flow including prerequisites, execution steps, and expected outcomes in S/4HANA
  • Configure monitoring and alerting for ai performance monitoring processes using standard SAP tools and threshold-based notifications

Data Preparation For Ai

  • Identify the key components, configuration options, and standard process flows for data preparation for AI within the SAP ecosystem
  • Configure data preparation for AI settings including parameters, organizational assignments, and integration points for operational deployment
  • Analyze data preparation for AI effectiveness using standard metrics and recommend configuration improvements for optimization
  • Identify the key components, configuration options, and standard process flows for AI integration and extensibility within the SAP ecosystem
  • Configure AI integration and extensibility settings including parameters, organizational assignments, and integration points for operational deployment
  • Analyze AI integration and extensibility effectiveness using standard metrics and recommend configuration improvements for optimization
  • Configure data preparation for ai output templates, communication channels, and distribution rules for stakeholder notification

Scope

Included Topics

  • All topics in SAP AI and Generative AI (C_AIG_2404).
  • Configuration, implementation, and analysis of SAP AI and Generative AI including SAP AI Core, AI Launchpad, generative AI hub, prompt engineering, and AI use cases across SAP.
  • Integration with other SAP modules and cross-functional processes.
  • Best practices, troubleshooting, analytics, and reporting.

Not Covered

  • Topics outside this certification scope.
  • ABAP programming.
  • Basis administration.
  • Deprecated functionality.

Official Exam Page

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