Abstract

The integration of artificial intelligence (AI) into IT infrastructure has revolutionized organizational operations while simultaneously introducing complex compliance challenges that threaten data privacy, security, and regulatory adherence. This study examines the multifaceted compliance obstacles organizations encounter when deploying AI-driven IT systems, with particular emphasis on healthcare and financial sectors where regulatory requirements are most stringent. Through a comprehensive analysis of existing frameworks and empirical evidence from 45 organizations across multiple jurisdictions, this research identifies critical gaps in current governance models and proposes an integrated framework for compliance mitigation. The findings reveal that 73% of organizations struggle with data privacy compliance, 68% face challenges in algorithmic transparency, and 61% report difficulties in cross-border regulatory adherence. The proposed framework incorporates risk-based governance, continuous monitoring mechanisms, and adaptive compliance protocols specifically designed for AI-driven environments. This research contributes to both academic discourse and practical implementation by providing actionable strategies for organizations navigating the complex intersection of AI innovation and regulatory compliance. The study concludes that successful AI adoption requires proactive governance structures that balance technological advancement with robust compliance mechanisms.

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