This article was first published in the forum, The Edge Malaysia Weekly, from 15 December 2025 to 21 December 2025.
Artificial intelligence (AI) is no longer a futuristic vision. We are actively reshaping industries around the world. In Malaysia, the healthcare sector is undergoing a dramatic transformation, with the AI market value expected to surge from USD 10 million in 2022 to USD 220 million by 2030, reflecting a compound annual growth rate of 45.42%. This rapid growth highlights the potential of AI to improve diagnostic accuracy, streamline workflows, and reduce operational costs. However, while AI has been widely adopted in the medical field, its integration into pharmacy operations remains relatively slow.
The core of pharmacy practice is ensuring that patients receive the right medication at the right dose and time while preventing medication-related errors. With increasing workloads, aging populations, and increasing patient volumes, pharmacists are often stretched to their limits. AI offers a promising solution by automating administrative and repetitive tasks, allowing pharmacists to focus on providing quality patient care and enhancing medication management.
International research provides compelling examples of the impact of AI on pharmacy operations. In France, a 2020 study of Lumio Medication, an AI-driven decision support system, demonstrated increased accuracy and efficiency in detecting prescription errors. Over a two-week period, the system flagged 74% of prescriptions requiring pharmacist intervention, and further evaluation confirmed that the remaining 26% of missed issues did not pose a significant risk.
Similarly, a study in Spain introduced a machine learning model that enabled community pharmacists to screen for early signs of mild cognitive impairment, successfully identifying potential cases in 17.4% of 728 participants. In the US, the AI-powered FindAir mobile app for asthma management extends pharmacists' role to remote patient monitoring by tracking inhaler usage, detecting inappropriate practices and providing real-time feedback.
AI is revolutionizing fields such as radiology, where deep learning algorithms detect abnormalities such as cancerous tumors with high accuracy. Similarly, AI-powered clinical decision support systems help physicians make evidence-based treatment decisions by analyzing genomic and environmental data. In contrast, AI in pharmacy remains primarily focused on streamlining workflows, highlighting the need for greater integration into patient-centered care.
In December 2024, Malaysia launched a National AI Office to shape the policy and regulatory framework, with the aim of becoming a regional AI development hub. The secretariat will serve as a centralized strategic planning, research and regulatory oversight body for the AI sector, and plans to implement seven key initiatives in its first year, including an AI code of ethics, a regulatory framework, and a five-year action plan to 2030.
The Malaysian government recognizes the potential of AI in healthcare. Prime Minister Datuk Seri Anwar Ibrahim stressed that AI can improve the efficiency of the health system and reduce cost waste. Research suggests that AI could reduce healthcare costs by 10% to 30%.
The integration of AI in pharmacy has the potential to transform drug prescribing, dispensing, management, and monitoring, addressing challenges such as increasing patient volumes, complex regimens, and limited medical resources in Malaysian hospitals. By analyzing vast amounts of patient data and clinical guidelines, AI can recommend evidence-based drug treatments, optimize dosing, and predict side effects to increase both efficacy and safety.
The Ministry of Health is actively researching the role of AI in healthcare, with a pilot project on AI-powered lung cancer detection underway at the National Cancer Institute and Cyberjaya, Kajang and Putrajaya hospitals. Lung cancer, the leading cause of cancer-related deaths in Malaysia, is often diagnosed at a later stage when treatment costs are high and treatment options are limited. Targeted screening powered by AI could enable earlier detection and potentially more effective and affordable treatment options.
AI also improves inventory management by analyzing patient demographics, disease trends, and prescription data to predict drug demand. For example, during flu season, AI-driven systems could predict spikes in the need for antiviral drugs and better stock them. Additionally, in hospital settings, AI improves the safety and accuracy of parenteral nutrition and chemotherapy drug administration by automating calculations, monitoring infusion rates, and analyzing patient responses to reduce human error.
Beyond hospitals, AI is driving efficiency and cost savings in the pharmaceutical industry, accelerating drug discovery by analyzing large data sets to identify potential candidates and predicting success rates before expensive clinical trials. Companies like Benevolent AI in London are already leveraging AI to speed up drug development. Virtual clinical trials and AI-powered simulations can further refine drug formulations, reduce cost and time, and make medicines more affordable. McKinsey estimates that AI has the potential to generate between US$60 billion (RM250 billion) and US$110 billion annually for pharmaceutical companies.
In countries where chronic diseases such as diabetes and hypertension are prevalent, AI-powered medication adherence monitoring can help pharmacists provide personalized interventions to improve medication adherence and ultimately improve long-term health outcomes.
Nevertheless, integrating AI into pharmacy operations poses several significant challenges. Many hospitals and clinics lack critical infrastructure, such as electronic health records, required for modern digital solutions. This shortfall is exacerbated by disparate hospital and community pharmacy systems, which prevents seamless data sharing and complicates the integration of AI tools.
Additionally, the sector’s reliance on traditional methods of medication management and pharmacists’ limited AI literacy further impede the transition to digital solutions. To overcome these skills gaps, it is essential to implement comprehensive training programs and continuing professional development initiatives that provide pharmacists with the necessary technical expertise.
Additionally, pharmacy AI systems must adhere to strict healthcare regulations to ensure patient safety and data security. This raises important questions about accountability. For example, if an AI system issues an incorrect recommendation and harms a patient, the question of liability remains open. Clear governance guidelines established by policymakers and healthcare regulators are essential to address these concerns and build trust in AI-driven solutions.
Additionally, the cost of implementing AI technology can be prohibitive, especially for small, independent community pharmacies. In this context, government incentives, subsidies, or public-private partnerships can play a key role in bridging the digital divide and make AI solutions accessible to all sectors of the pharmacy industry.
A collaborative approach is essential for Malaysia to maximize the benefits of AI in pharmacy operations. Government agencies, pharmacy associations, and technology developers must work together to overcome existing challenges. By investing in infrastructure, increasing AI literacy among healthcare professionals, and establishing clear regulatory guidelines, Malaysia can pave the way to a future where AI empowers pharmacists and improves patient care.
The path to AI integration in Malaysian pharmacy operations may be full of obstacles, but the potential benefits are undeniable. By embracing AI, pharmacists can move from traditional drug dispensers to a central role in personalized, data-driven healthcare. The future of pharmacy is bright and it is time for Malaysia to embrace this new era with open arms.
David Chang is a researcher at BranX-ON Marketing. Lorraine Hu is a pharmacist.
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