Integrating AI and Data-Driven Techniques to Strengthen Security Governance in Multinational Organizations

Abstract

As generative AI transforms industries, the role of data security governance (DSG) has become pivotal in maintaining compliance, security, and trust. This paper explores trends and strategies for integrating AI and data-driven techniques into DSG frameworks to address sensitive data protection, global compliance, and operational efficiency. By leveraging AI for real-time governance, security automation, and federated data management, multinational organizations can ensure scalability, resilience, and adaptability in their governance strategies. The increasing sophistication of cyber threats poses significant challenges to multinational organizations, which operate complex and distributed infrastructures across diverse regulatory landscapes. Traditional security governance frameworks often lack the agility and precision required to counter these evolving threats. This research explores the integration of Artificial Intelligence (AI) and data-driven techniques to enhance security governance in multinational organizations, providing a proactive, scalable, and adaptive approach to mitigating risks.
The proposed framework leverages AI models, such as machine learning algorithms and natural language processing (NLP), to analyze vast datasets, identify vulnerabilities, and predict potential threats in real time. By incorporating data-driven techniques, the framework enables continuous monitoring, anomaly detection, and automated response mechanisms, significantly reducing response times and minimizing operational disruptions. A key feature of the framework is its ability to adapt to diverse regulatory requirements, ensuring compliance across multiple jurisdictions while maintaining organizational agility. This research emphasizes the importance of AI-enabled DSG solutions to safeguard against risks such as data leakage, regulatory violations, and infrastructure inefficiencies while enabling agile decision-making and innovation.