Data Governance in the Age of Big Data and AI

Abstract

Big Data and Artificial Intelligence (AI) are growing by the hour and have transformed the worth and threat of online information. With organizations becoming more reliant on datadriven insight, proper data governance has evolved into a strategic business process, as it allows to ensure the quality of data, its security, ethical treatment, and alignment with regulatory demands. This paper reviews the dynamic data governance models in light of big, heterogeneous and rapidly moving datasets, as well as the distinct issues posed by AI systems. It also describes the overlap of the policy, technology and ethics issue areas, notably how AI can help and complicate governance by automating, predictively analyzing and making decisions via algorithms. Some of the key aspects to consider are data quality in heterogeneous settings, mitigating biases that possibly can be enhanced by AI models, and ensuring transparency in the process of decision making that is automated. Such regulatory environments as GDPR, CCPA, etc, and even newer approaches towards regulation addressing AI are examined to determine their influence on the governance practices. Metadata management and data lineage tracking and strong access controls are also discussed as key building blocks of accountability and trust in the study. Based on the cases within the industry and recent outputs of scholars, the paper suggests a model of the adaptive governance that incorporates the continuous review, collaboration with stakeholders, and the ethical oversight. The characteristics of the model include proactive risk management and the integration of governance principles into AI leading to direct commitments to AI creation and application processes. We can now see next generation data governance in the world of Big Data and AI requiring a transition of compliance-centered approaches with rules set in stone to more fluid systems of context-sensitive situational strategies balancing innovation with liability. Companies which manage to implement such frameworks will be in a better position to realize the transformative power of AI and protect the faith that stakeholders place in them as well as withstand the shifting dynamic legal and ethical requirements.