Cognitive Governance for Web-Scale Systems: Hybrid AI Models for Privacy, Integrity, and Transparency in Full-Stack Applications
DOI:
https://doi.org/10.63282/3050-9416.IJAIBDCMS-V3I4P110Keywords:
Cognitive Governance, Hybrid AI Privacy Framework, Web-Scale Application Architecture, Data Privacy Engineering, Full-Stack Integrity Intelligence, Transparent Analytics Systems, AI-Driven Compliance Frameworks, Intelligent Policy EnforcementAbstract
Web-scale application architecture amplifies the challenges of enforcing privacy, integrity, and transparency across heterogeneous data sources, microservices, and user-facing interfaces. Traditional governance approaches, built on manual reviews and static rule sets, are no longer sufficient to manage dynamic risks, evolving regulations, and high-velocity data flows. The present paper introduces a Cognitive Governance paradigm that integrates a Hybrid AI Privacy Framework into the full-stack application paths directly, making the policy reasoning, data privacy engineering, and data runtime monitoring unified. These policies and models are interpreted, anomalies are identified, and integrity is checked to form complete-stack integrity intelligence to assess context in relation to data sensitivity, user role, jurisdiction, and behavioral indicators. The governance decisions can be accessed, masking, blocking, escalation using intelligent policy enforcement services implemented at API gateways, service meshes and data platforms. The transparent analytics systems help to reveal the decision traces, explanations, and lineage to the developers, auditors and regulators making governance not an after-the-fact audit capability but an operational plane of control. Describe the building blocks of architecture, privacy preserving mechanisms and integrity protection necessary to achieve Cognitive Governance in web scale environment and justify practical considerations of evaluation, such as feasibility, deployment trade-offs, and constraints. The result is a blueprint for AI-driven compliance frameworks that are adaptive, explainable, and resilient, supporting trustworthy full-stack applications in cloud-native, highly regulated, and data-intensive settings
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