Bridging Compliance and Accountability: Governance, Privacy, and Observability Challenges in Cloud and AI Ecosystems
DOI:
https://doi.org/10.61424/dbec0x61Keywords:
Cloud Governance, AI Accountability, Privacy-Aware Observability, Regulatory Compliance, Risk ManagementAbstract
Cloud computing and AI (artificial intelligence) are rapidly growing and have added highly complex challenges in areas of compliance, privacy, transparency, and accountability. This review addresses the governance, privacy protection and observability integration within cloud native and AI powered ecosystems, highlighting the technical and organizational measures needed to create trustworthy digital environments. Shared responsibility models are discussed for cloud service architectures, privacy management practices, continuous risk assessment, and evidence based compliance. The focus is on observability technologies like metrics, logs, distributed tracing, and profiling, that help with monitoring systems, investigating incidents, and optimizing performance. In addition, the use of standard instrumentation, audit logging, data provenance, and automation of policy enforcement to improve accountability is explored. In addition, the review covers issues with data silos, too much data telemetry, data processing expenses, third party requirements, and new privacy risks arising from AI. Various regulatory and governance models, such as the NIST AI Risk Management Framework, ISO/IEC 42001, ISO/IEC 27701 and the General Data Protection Regulation, are taken into account when it comes to privacy management, security assurance and responsible AI deployment. New paradigms like policy as code, continuous monitoring of compliance and automatic generation of evidence can help to enhance governance efficiency and preparation for audit. However, it is important to have clear responsibility, design for privacy, human oversight, and ongoing assessment of technical controls to implement effectively. This comprehensive approach can enhance transparency, operational resilience, regulatory compliance, and trust in the growing cloud and AI landscape.
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