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AI-Powered Test Case Generation for Regulatory Compliance: Leveraging Generative AI in SAP and Salesforce Environments

Author

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  • Vijay Kumar Kola

    (Osmania university, India)

Abstract

AI-powered test case generation represents a significant advancement in regulatory compliance testing for enterprise systems, particularly in highly regulated industries like healthcare and finance. This innovation addresses critical challenges in the traditional compliance testing process, which is characterized by labor-intensive manual efforts, high error rates, and substantial documentation requirements. The integration of generative artificial intelligence with established testing frameworks enables organizations to dramatically reduce test creation time while simultaneously improving requirement coverage across SAP and Salesforce environments. Through automated requirement analysis, sophisticated test case generation techniques, and risk-based prioritization algorithms, organizations can achieve comprehensive compliance with regulations such as SOX and GxP guidelines while significantly reducing operational costs. The technical implementation leverages specialized connectors to SAP modules and Salesforce processes, integrating with existing governance frameworks and automation tools to deliver end-to-end traceability. Continuous learning systems further enhance testing quality through historical data analysis, dynamic updating mechanisms, and intelligent optimization algorithms. The resulting business impact includes substantial improvements in operational efficiency, enhanced compliance coverage, increased adaptability to regulatory changes, and streamlined audit processes, demonstrating exceptional return on investment for early adopters across multiple industry sectors.

Suggested Citation

  • Vijay Kumar Kola, 2025. "AI-Powered Test Case Generation for Regulatory Compliance: Leveraging Generative AI in SAP and Salesforce Environments," Journal of Computer Science and Technology Studies, Al-Kindi Center for Research and Development, vol. 7(3), pages 554-560, April.
  • Handle: RePEc:alk:jcsts0:v:7:y:2025:i:3:id:9402
    DOI: 10.32996/jcsts.2025.7.3.63
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