The integration of artificial intelligence (AI) into pharmacy governance offers transformative potential to strengthen compliance, enhance risk detection, and reinforce ethical safeguards in healthcare systems. This paper examines how AI-driven tools ranging from automated compliance audits to predictive analytics for fraud detection can be harnessed to improve regulatory oversight in pharmacy practice. Drawing on governance and risk management theories, the study synthesizes existing literature on AI applications in healthcare, evaluates alignment with international frameworks such as ISO/IEC 38500, COSO-ERM, and the WHO Good Governance for Medicines, and proposes a conceptual AI-Integrated Pharmacy Governance Framework. The model emphasizes compliance monitoring, risk governance, and ethical accountability to address emerging challenges such as patient data privacy and transparency. By advancing a structured governance model, this paper highlights AI’s capacity to balance innovation with regulatory rigor, offering pathways toward more accountable, efficient, and trustworthy pharmacy systems.
Abdelmonem, R., Lasheen, P., Hanafi, A., & Magdy, A. (2025). A Comprehensive Review of Improvements in Clinical Pharmacy: Integration of AI, Pharmacovigilance, Telepharmacy, Legalization, and Multidisciplinary Collaboration for Enhanced Healthcare Delivery. Journal of Pharmaceutical Sciences and Drug Manufacturing-Misr University for Science and Technology, 2(1), 89-99.
Ahire, Y. S., Patil, J. H., Chordiya, H. N., Deore, R. A., & Bairagi, V. A. (2024). Advanced applications of artificial intelligence in pharmacovigilance: Current trends and future perspectives. J Pharm Res, 23(1), 23-33.
Ajmal, C. S., Yerram, S., Abishek, V., Nizam, V. M., Aglave, G., Patnam, J. D., ... & Srivastava, S. (2025). Innovative approaches in regulatory affairs: leveraging artificial intelligence and machine learning for efficient compliance and decision-making. The AAPS Journal, 27(1), 22.
Al Juffali, L., Al-Aqeel, S., Knapp, P., Mearns, K., Family, H., & Watson, M. (2019). Using the human factors framework to understand the origins of medication safety problems
Bader, L. R., McGrath, S., Rouse, M. J., & Anderson, C. (2017). A conceptual framework toward identifying and analyzing challenges to the advancement of pharmacy. Research in Social and Administrative Pharmacy, 13(2), 321-331.
Bahangulu, J. K., & Berko, L. O. (2025). Algorithmic bias, data ethics, and governance: Ensuring fairness, transparency and compliance in AI-powered business analytics applications. World Journal of Advanced Research and Reviews, 25(2), 1746-1763.
Bais, S. K., & Rathod, P. R. (2024). Quality Risk Management in Pharmaceutical Industry.
Barbieri, M. A., Battini, V., Carnovale, C., Cocco, M., Papoutsi, D. G., Heckmann, N. S., ... & Sessa, M. (2025). Artificial intelligence in pharmacovigilance signal management: a review of tools, implementations, research, and regulatory landscape. Expert Opinion on Drug Safety.
Castellanos, W. S. (2020). Impact of the information technology (IT) governance on business-IT alignment (Doctoral dissertation, Pontificia Universidad Catolica del Peru.
Chianumba, E. C., Ikhalea, N., Mustapha, A. Y., Forkuo, A. Y., & Osamika, D. (2024). Enhancing corporate governance and pharmaceutical services through data analytics and regulatory compliance. International Journal of Advanced Multidisciplinary Research and Studies, 4(6), 1613-1619.
COSO. (2017). Enterprise risk management: Integrating with strategy and performance. Committee of Sponsoring Organizations of the Treadway Commission.
Creswell, J. W., & Creswell, J. D. (2018). Research design: Qualitative, quantitative, and mixed methods approaches (5th ed.). SAGE Publications.
Davenport, T., & Kalakota, R. (2019). The potential for artificial intelligence in healthcare. Future Healthcare Journal, 6(2), 94–98.
Floridi, L., & Cowls, J. (2019). A unified framework of five principles for AI in society. Harvard Data Science Review, 1(1).
Glaser, M., & Littlebury, R. (2024). Governance of artificial intelligence and machine learning in pharmacovigilance: what works today and what more is needed?. Therapeutic Advances in Drug Safety, 15, 20420986241293303.
Gude, S., & Gude, Y. S. (2024). The synergy of artificial intelligence and machine learning in revolutionizing pharmaceutical regulatory affairs. Translational and Regulatory Sciences, 6(2), 37-45.
Guidance, W. H. O. (2021). Ethics and governance of artificial intelligence for health. World Health Organization.
Hakimi, M., Amiri, G. A., & Shamsi, S. E. (2024). Artificial Intelligence and Public Health: Addressing Pharmacy Practice Challenges and Policy Issues. British Journal of Pharmacy and Pharmaceutical Sciences, 1(1), 09-21.
Hasan, H. E., Jaber, D., Khabour, O. F., & Alzoubi, K. H. (2024). Ethical considerations and concerns in the implementation of AI in pharmacy practice: a cross-sectional study. BMC Medical Ethics, 25(1), 55.
International Organization for Standardization. (2015). ISO/IEC 38500: Information technology – Governance of IT for the organization. ISO.
ISO/IEC. (2015). ISO/IEC 38500: Information technology – Governance of IT for the organization. International Organization for Standardization.
Jagun, C. (2018). Strategies for Compliance with Government Regulation in a Pharmaceutical Company (Doctoral dissertation, Walden University).
Jaibhagvan, J. (2025). Pharmacovigilance in the Digital Age: Using Big Data and Artificial Intelligence to Improve Drug Safety. Scholar's Digest: Journal of Pharmacology, 1(1), 170-186.
Jiang, F. (2017). Artificial intelligence in healthcare: Past, present and future. Stroke and Vascular Neurology, 2(4), 230–243.
Kodali, S. (2019). Utilizing AI for Real-Time Pharmacovigilance: Developing Machine Learning Models for Automated Adverse Event Detection, Risk Assessment, and Regulatory Compliance Monitoring. Journal of Artificial Intelligence & Machine Learning Studies, 3, 39-78.
Langaro, M. (2020). Innovative regulatory framework in community pharmacy.
Majekodunmi, E. A. (2025). Strengthening Drug Safety and Public Health Surveillance in the United States: The Role of Artificial Intelligence in Pharmacovigilance. Available at SSRN 5181179.
Majekodunmi, E. A. (2025). Strengthening Drug Safety and Public Health Surveillance in the United States: The Role of Artificial Intelligence in Pharmacovigilance. Available at SSRN 5181179.
Melo, M. S. D. (2024). Trends and criticalities in quality assessment in the pharmaceutical industry: the practical case of Bluepharma Pharmaceutical Industry, SA (Master's thesis). https://baes.uc.pt/handle/10316/119031
Nagar, A., Gobburu, J., & Chakravarty, A. (2025). Artificial intelligence in pharmacovigilance: advancing drug safety monitoring and regulatory integration. Therapeutic Advances in Drug Safety, 16, 20420986251361435.
Orozco, D. (2019). A systems theory of compliance law. U. Pa. J. Bus. L., 22, 244.
Pasas-Farmer, S., & Jain, R. (2025). From discovery to delivery: Governance of AI in the pharmaceutical industry. Green Analytical Chemistry, 13, 100268.
Potter, K., & KARL, L. (2023). Machine Learning in Drug Safety Monitoring: Enhancing Pharmacovigilance Efforts.
Ravali, R. S., Auguskani, J. P. L., Reddy, L. K. V., Narapureddy, B. R., Chellathurai, A., & Mavaluru, D. (2023). Pioneering ethical boundaries: Empowering ai governance for the future of pharmaceutical and nursing sectors. Lat Am J Pharm, 42(3), 695-701.
Reddy, S., & Sharma, B. (2020). Artificial intelligence in healthcare: Past, present and future. Journal of Oral and Maxillofacial Pathology, 24(1), 12–16.
Saha, K., & Okmen, N. (2025). Artificial Intelligence in Pharmacovigilance: Leadership for Ethical AI Integration and Human-AI Collaboration in the Pharmaceutical Industry.
Saha, K., & Okmen, N. (2025). Artificial Intelligence in Pharmacovigilance: Leadership for Ethical AI Integration and Human-AI Collaboration in the Pharmaceutical Industry.
Shamim, M. A., Shamim, M. A., Arora, P., & Dwivedi, P. (2024). Artificial intelligence and big data for pharmacovigilance and patient safety. Journal of Medicine, Surgery, and Public Health, 3, 100139.
Shukla, D., Bhatt, S., Gupta, D., & Verma, S. (2024). Role of artifical intelligence in pharmacovigilance. Journal of Drug Discovery and Health Sciences, 1(04), 230-238.
Singhal, A., Neveditsin, N., Tanveer, H., & Mago, V. (2024). Toward fairness, accountability, transparency, and ethics in AI for social media and health care: scoping review. JMIR Medical Informatics, 12(1), e50048.
Szalonka, K., D?browska, A., Jab?o?ski, M., Drozd, M., Fandrejewska, A., Sta?czyk, E., & ?ak, K. (2025). E-Pharmaceutical Care and E-Health Operational Frameworks. CRC Press.
World Health Organization. (2014). Good governance for medicines: Model framework. WHO.
Zetzsche, D. A., Buckley, R. P., Arner, D. W., & Barberis, J. (2020). Artificial intelligence in finance: Putting the human in the loop. Journal of Banking Regulation, 21(4), 299–313.
Yusuf, S. N. B. S., Zakaria, Y. B., Mohamed, I. S. B., & Mia, M. M. (2025). AI-Driven Compliance and Risk Governance in Pharmacy Practice. International Journal of Academic Research in Business and Social Sciences, 15(9), 1520–1536.
Copyright: © 2025 The Author(s)
Published by Knowledge Words Publications (www.kwpublications.com)
This article is published under the Creative Commons Attribution (CC BY 4.0) license. Anyone may reproduce, distribute, translate and create derivative works of this article (for both commercial and non-commercial purposes), subject to full attribution to the original publication and authors. The full terms of this license may be seen at: http://creativecommons.org/licences/by/4.0/legalcode