Data Governance for AI-Powered Pega Applications: Compliance, Privacy & Reliability
DOI:
https://doi.org/10.15662/IJARCST.2025.0801007Keywords:
AI Governance, Pega Customer Decision Hub, Data Privacy Compliance, Adaptive Decision Manager, Responsible AI, Model Drift Monitoring, Real-Time DecisioningAbstract
The rapid shift toward artificial intelligence (AI) in enterprise systems has transformed how organizations operate, make decisions, and deliver customer experiences. Pega, with its Customer Decision Hub (CDH), Case Management, and Intelligent Automation capabilities, has emerged as a dominant platform enabling real-time decisioning and adaptive intelligence across financial services, telecommunications, public sector, healthcare, and insurance. While AI-powered Pega systems deliver unprecedented personalization and operational efficiency, they also create profound challenges related to data governance, regulatory compliance, privacy protection, model accountability, and long-term reliability. Traditional data governance approaches - designed for static, relational, and rule-based systems - are insufficient for the dynamic, streaming, and learning-driven nature of modern Pega architectures.
This research proposes a multi-layered data governance framework tailored specifically to AI-driven Pega applications. The model addresses compliance with GDPR, CPRA, HIPAA, FFIEC, PCI-DSS, and emerging global AI regulations while supporting enterprise-grade privacy protections, ethical AI guidelines, real-time operational governance, and continuous monitoring of data lifecycle integrity. Through analytical narration, data tables, and four formal diagrams, the paper develops a unified governance blueprint that integrates Governance-by-Design, Real-Time Compliance Orchestration, Responsible AI Monitoring, and End-to-End Lifecycle Assurance. The result is a comprehensive governance model aligned to the evolving demands of enterprise-scale AI systems.
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