The future of healthcare supply chains may be written in code, as artificial intelligence is emerging as a powerful ally in solving one of the industry’s most persistent problems: balancing supply with demand while cutting waste. A new study published in the International Journal of Advanced Research, Ideas and Innovations in Technology (IJARIIT) shows that AI-driven systems are already reshaping how hospitals, pharmaceutical companies, and clinics manage essential drugs and medical supplies, offering not just efficiency but also resilience in times of crisis.
At the centre of the research is a challenge that has long plagued healthcare systems. Hospitals across the world face shortages of life-saving medicines on one hand and mountains of expired stock on the other. The financial impact is severe.
Uganda once lost more than $550,000 to expired medications in a single year, while Switzerland reported losses of about $436 million annually. In Vienna, the Sickness Fund estimated $8.8 million worth of drugs went to waste, and in the United States, the figure exceeds $1 billion every year. The researchers argue that artificial intelligence could break this cycle by predicting demand with far greater accuracy than traditional inventory methods.
The study surveyed a sample of 598 healthcare professionals in the United States, including administrators, consultants, suppliers, and logistics managers. Predictive analytics, machine learning, and robotics process automation were identified as the most widely applied AI tools in inventory systems. These technologies not only flagged potential shortages before they occurred but also ensured stock levels were optimised to prevent costly overstocking. Respondents pointed to improved forecasting, reduced operational costs, and stronger supply chain visibility as the most significant benefits of AI. More than 500 participants said they would recommend AI-driven inventory systems to other healthcare organisations. The authors note that while the total survey sample was 598, individual questions recorded smaller response numbers, suggesting some participants skipped certain items.
Despite these advantages, adoption has been uneven. Only 5.4 per cent of respondents reported complete integration of AI into their inventory management, while nearly a quarter admitted they had not adopted it at all. The barriers are familiar: data integration challenges, high costs, and organisational resistance to change. The researchers suggest that investing in reliable data systems, partnering with AI vendors, and introducing structured change management programs could help organisations overcome these obstacles. Training staff and running pilot projects before rolling out full-scale implementation were also recommended as practical steps to smooth the transition.
The study also looks ahead at emerging possibilities. Technologies such as deep learning, reinforcement learning, and the Internet of Things could make it possible to monitor everything from vaccine shipments to temperature-sensitive medicines in real time. For countries with fragile healthcare infrastructures, these advances could be transformative. Rwanda has already demonstrated how AI can reduce vaccine spoilage and improve distribution efficiency, setting an example for others to follow.
The findings are clear. Artificial intelligence in healthcare supply chains is not just about saving money; it is about saving lives.
By reducing waste, ensuring timely access to medicines, and strengthening resilience against disruptions such as pandemics, AI has the potential to become the backbone of sustainable healthcare delivery. The organisations that choose to adopt these technologies now will not only gain an operational advantage but also be better prepared to face the healthcare challenges of tomorrow. The study notes a minor inconsistency in its machine learning model reporting, but the overall conclusion is decisive: artificial intelligence is a critical enabler of a more resilient global healthcare system.
