Authors:
Manoj Parasa

Addresses:
Department of Information Technology Services, Ernst and Young, Dallas, Texas, United States of America.

Abstract:

The accelerating complexity of global labour regulations has rendered traditional compliance processes inadequate for multinational enterprises. This study proposes an intelligent compliance automation framework within SAP SuccessFactors that integrates rule-based controls with AI-driven predictive monitoring to ensure proactive adherence to labour laws. Using a mixed-methods design that combines configuration analysis, expert interviews, and multi-region simulation, the framework leverages the SAP Business Rules Engine, Integration Centre, and AI Core to automate policy validation, detect anomalies, and forecast compliance risks. Quantitative evaluation demonstrated a 42% reduction in policy violations and 73% prediction accuracy in identifying high-risk employment events. Qualitative insights from HRIT and compliance leaders emphasised the framework’s role in shifting compliance from reactive auditing toward strategic governance. Comparative assessment with Oracle HCM and Workday modules confirmed SAP’s superior flexibility in dynamic rule management while underscoring the value of interoperability for multinational audit ecosystems. The research contributes to a replicable, intelligence-driven compliance model that combines human oversight with algorithmic precision, offering both theoretical and practical guidance for next-generation digital labour governance.

Keywords: AI-Driven Monitoring; AI-Powered Policy Enforcement; Business Rules Engine; Comparative HCM Platforms; Policy Validation; Digital Workforce Governance; Predictive Monitoring.

Received on: 08/02/2025, Revised on: 10/05/2025, Accepted on: 09/08/2025, Published on: 23/11/2025

DOI: 10.69888/FTSTPL.2025.000506

FMDB Transactions on Sustainable Technoprise Letters, 2025 Vol. 3 No. 4, Pages: 211-220

• Views : 16
• Downloads : 5

Download PDF