Citation:

Chirag Devendrakumar Parikh, 2025. "AI/ML Integration: Driving Efficiency While Meeting Compliance Demands", ESP Journal of Engineering & Technology Advancements  5(3): 198-201.

Abstract:

Artificial Intelligence (AI) and Machine Learning (ML) are rapidly transforming modern digital infrastructures by enabling automation, predictive analytics, resource optimization, and enhanced cybersecurity. Organizations increasingly rely on intelligent systems to improve operational efficiency, reduce costs, and strengthen resilience. However, the adoption of AI/ML also introduces significant regulatory and compliance challenges. Standards such as GDPR, HIPAA, PCI DSS, and ISO/IEC 27001 impose strict requirements related to privacy, security, transparency, and accountability. This paper examines key AI/ML applications that drive efficiency across enterprise environments, highlights compliance-driven risks, and proposes a governance-aware framework that enables responsible automation while maintaining regulatory alignment. The study demonstrates how compliance-aware AI integration can support sustainable, secure, and efficient next-generation digital systems.

References:

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Keywords:

Artificial Intelligence, Machine Learning, Compliance, Efficiency, Predictive Maintenance, Cybersecurity.