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Invite colleaguesData governance in the age of artificial intelligence: Challenges, best practices and regulatory compliance
Abstract
The growing use of artificial intelligence (AI) across businesses has created serious issues concerning data governance and privacy. As AI technologies rely significantly on massive datasets to learn, adapt and make choices, enterprises must provide strong data governance to protect data integrity, provide security and ensure compliance. Data governance encompasses the policies, procedures and standards that guarantee data are accurate, accessible and properly used throughout their life cycle. Data governance frameworks are becoming important in the context of AI, as AI systems handle and analyse vast amounts of data, frequently containing sensitive or personal information. This research paper examines the importance of data governance in the age of AI, stressing both the benefits and problems it provides. Effective data governance frameworks can assist firms in making better decisions, ensuring regulatory compliance and protecting user privacy. Traditional governance systems face substantial challenges from issues such as data bias, data quality and the complexity of managing AI-driven datasets. To reduce these dangers, best practices in data governance are highlighted, such as data classification, metadata management and the introduction of AI-specific governance standards. As AI technologies advance, the significance of adaptable and transparent data governance frameworks cannot be overemphasised. This study adds to our understanding of how corporations should reconcile the rapid advances in AI with the importance of strong data governance and privacy regulations.
The full article is available to subscribers to the journal.
Author's Biography
Animesh Kumar Sharma is a research scholar at Mittal School of Business at the Lovely Professional University. He is also Manager — Marketing and Corporate Communication with Vatika Business Centres Private Limited (a Vatika Group Company). His research interests include digital marketing, social media marketing, search engine marketing, artificial intelligence, machine learning, data analytics and the applications of technology in business.
Rahul Sharma is a professor of marketing with over 14 years of experience in academia. He has a PhD in marketing. Dr Sharma’s research interests include consumer behaviour, business analytics and digital marketing. In addition to his research, he is involved in various faculty development programmes.
Citation
Sharma, Animesh Kumar and Sharma, Rahul (2025, March 1). Data governance in the age of artificial intelligence: Challenges, best practices and regulatory compliance. In the Applied Marketing Analytics: The Peer-Reviewed Journal, Volume 10, Issue 4. https://doi.org/10.69554/XWHM1191.Publications LLP