C_BCBAI_2509 Practice Exams and Study Guide
SAP C_BCBAI_2509 Exam Specifications
- Exam Code:
- C_BCBAI_2509
- Exam Name:
- SAP Certified Associate - Positioning SAP Business AI Solutions as part of SAP Business Suite
- Provider:
- SAP
- Time:
- 60 min
- Passing Percentage:
- 67%
- Version:
- 6.1
Question Types
- 8 Single Select
- 22 Multi Select
30 Questions with Answers
- PDF Printable (Q & A)
- 3 Months
Key Features to Key Benefits
Real Exam-like Questions and Answers (30 total)
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Topics Covered
- Positioning SAP Business AI
- Exploring Joule Agents
SAP Certified Associate - Positioning SAP Business AI Solutions as part of SAP Business Suite Topics for Real-World Roles
The SAP Certified Associate exam focuses on identifying high-value AI use cases across core processes, defining data requirements and governance with privacy and quality considerations, and architecting integrations that embed AI into SAP applications and analytics platforms. Practically you will build and deploy AI-enabled automation and decision-support features within workflows including exception handling, monitor production models for performance and drift and manage versioning, apply responsible AI practices such as bias mitigation and explainability, establish ROI metrics to quantify business impact, ensure security and access controls for AI-enabled features, and lead change with governance, training, and cross-team communications.
Role‑Aligned Topics
- Identify high-value AI use cases across core business processes and map them to measurable outcomes.
- Define data requirements, governance, quality, and privacy considerations for AI initiatives within the suite.
- Design architecture for integrating AI capabilities with key business applications and analytics platforms.
- Build and deploy AI-enabled automation and decision-support features within workflows, including exception handling.
- Monitor production AI models for performance, drift, and reliability; manage versioning and lifecycle.
- Apply responsible AI practices such as bias mitigation, explainability, and auditability in decisions.
- Establish metrics, track ROI, and quantify business impact to guide ongoing AI investments.
- Ensure security, access controls, and data protection for AI-enabled features across the landscape.
- Manage change and stakeholder adoption, including training, governance, and communications across teams.
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