This paper explores the implementation of Artificial Intelligence (AI), especially generative AI, in the pharmaceutical industry amid ongoing digital transformation (DX). AI technologies are being applied more and more across drug development, manufacturing, quality assurance, and supply chain management. These technologies offer improved efficiency and decision-making capabilities. However, these benefits come with challenges related to technical feasibility, ethics, and regulatory compliance. This paper reviews international regulatory initiatives, including FDA, WHO, and ISPE (GAMP 5 Second Edition) guidelines, and highlights key areas such as risk management, explainability, data quality, and model monitoring. It also discusses practical considerations such as data preprocessing, AI model validation, continuous monitoring, and model drift. Furthermore, the paper emphasizes the importance of human-centered design and responsible AI use, with ultimate accountability remaining with human decision-makers. This paper presents strategies for overcoming implementation barriers, such as PoC-driven phased adoption, workforce training, and interdepartmental collaboration. Finally, the paper outlines actionable steps for practitioners to reliably and sustainably integrate AI in compliance with GxP requirements, aiming to guide the pharmaceutical sector toward the responsible and effective utilization of AI.
