IMPLEMENTING ROBUST DATA GOVERNANCE FRAMEWORKS: THE ROLE OF AI/ML IN ENSURING DATA INTEGRITY AND COMPLIANCE
Keywords:
Artificial Intelligence (AI), Data Quality, Data Volume, Privacy, SecurityAbstract
Numerous industries are starting to incorporate artificial intelligence (AI) into their operations, including healthcare, finance, and transportation. It is critical to have a consistent supply of high-quality data available since artificial intelligence applications rely on analyzing large datasets. Contrarily, there are several difficulties associated with data consumption for AI purposes. Data quality, data volume, privacy and security, fairness and bias, interpretability and explainability, ethical considerations, and technical expertise are some of the obstacles that this study presents. This study offers a comprehensive evaluation and critical examination of the challenges that are associated with the utilization of data for artificial intelligence. This article's goals are to (1) examine how GxP firms' computer validation system services are evolving and (2) highlight the substantial role that AI and ML play in improving these services. The use of AI and ML holds great potential for improving validation processes, increasing efficiency, and guaranteeing compliance. This is especially noteworthy in light of the growing complexity of GxP environments and the expanding volume of data. Using artificial intelligence and machine learning in computer validation system services for GxP sectors is the subject of this study, which offers insights into the benefits, problems, and best practices related with its utilization.
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Copyright (c) 2022 Sudeesh Goriparthi (Author)
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