Drug shortages have surged to their highest levels in decades. In early 2024, U.S. pharmacies reported more than 323 active shortages, spanning essential generics, injectables, and even critical cancer therapies. These numbers echo findings from the American Society of Health-System Pharmacists, which tracks persistent disruptions that ripple through hospitals, pharmacies, and ultimately to patients in urgent need of care.
While the pandemic made those cracks impossible to ignore, the reality is that supply chains face ongoing pressure from manufacturing issues, quality lapses, and shifting demand. These challenges don’t require a global emergency to surface. They are built into the way medicines move from development to delivery.
The challenge is not just one of logistics. Pharmaceutical supply chains are inherently complex, with thousands of suppliers, strict regulatory constraints, and delicate production processes that leave little room for error. The question now is whether advanced technologies like artificial intelligence can deliver the visibility, foresight, and agility these critical lifelines urgently require.
The Root Causes of Fragility
Pharmaceutical supply chains share many of the same vulnerabilities as other industries, but the stakes are far higher. Geopolitical risks such as tariffs, trade disputes, and sanctions can abruptly limit access to active pharmaceutical ingredients, many of which come from a small number of regions. Consolidation adds brittleness, as overreliance on single suppliers or limited production facilities leaves little room for error. Upstream uncertainty, including shortages of raw materials beyond pharma’s direct control, cascades downstream into drug shortages.
Even the regulatory safeguards designed to protect patients can create process inflexibility that slows recovery when disruptions occur. For these reasons, leaders in the sector are rethinking how to remap and strengthen their supply chains. Unlike in other global industries, however, the consequences are measured not only in financial losses but in patient lives.
Where AI Can Help Today
AI is often discussed in broad, futuristic terms, but its most immediate applications in pharma supply chains are practical and tactical. In fact, it is not about one breakthrough application, but an “all-of-the-above” approach, embedding AI into every step of the chain.
- Demand forecasting. AI models trained on prescribing patterns, epidemiological data, and market dynamics can improve predictions of where and when demand will spike.
- Inventory optimization. Machine learning can identify hidden inefficiencies in stockpiling and distribution, helping companies keep critical drugs available without overburdening warehouses.
- Production planning. AI-driven simulations can reduce bottlenecks in manufacturing and identify optimal production schedules under tight constraints.
- Logistics and distribution. AI agents can route shipments around emerging disruptions, from port closures to extreme weather events.
- Predictive maintenance. Monitoring data from production facilities can flag potential failures before they halt manufacturing lines.
The value lies not in a single fix, but in weaving AI across each link in the chain to create cumulative resilience.
Upstream Risk: Monitoring the Materials That Matter
Pharma’s fragility often begins upstream, with shortages of APIs or raw materials. Here, AI’s ability to monitor diverse data streams, from commodity markets to weather forecasts to geopolitical news, becomes essential. For example, climate-related disruptions have already impacted crops used in drug manufacturing, while geopolitical tensions threaten API imports. AI platforms that aggregate and analyze these signals can help companies anticipate risks, diversify sourcing strategies, and respond before shortages hit patients.
This mirrors what is already happening in other sectors. In raw materials and agriculture, startups are using AI to track everything from soil conditions to shipping bottlenecks. Pharma companies are beginning to follow suit, recognizing that supply security begins long before a finished drug reaches a pharmacy shelf.
Real-World Use Cases
While AI in pharma supply chains is still evolving, adjacent healthcare sectors are already putting it to work. One large U.S. healthcare system we’ve had the opportunity to work with recently deployed AI to strengthen its cardiology supply chain. The system manages a vast array of medical instruments and consumables. Early results showed improved resilience with the ability to adapt and reallocate supplies quickly when disruptions occurred. For organizations where each day of shortage can compromise patient outcomes, these gains are significant. These examples point to a broader lesson. AI is not only about preventing shortages; it is about building agility into systems that have traditionally been rigid and reactive.
Barriers to Adoption
Despite the promise, several barriers slow AI adoption in pharma supply chains:
- Cultural inertia. Supply chain teams often rely on decades of institutional knowledge. Convincing experienced professionals to trust AI-driven recommendations requires careful change management.
- Process change. Embedding AI often means rethinking workflows, not simply adding new tools. That level of change can meet internal resistance.
- Regulatory caution. Any innovation in pharma must navigate stringent oversight, which can delay or complicate implementation.
- Fragmented ecosystems. With dozens of stakeholders, including manufacturers, distributors, regulators, and providers, aligning data and incentives remains a challenge.
In many cases, the barrier is not technology itself but the willingness to adapt processes and mindsets to new tools. However, looking ahead, AI’s influence on pharma supply chains will grow in both scope and subtlety. In the near term, most improvements will be cumulative: better forecasts here, smarter routing there, more adaptive sourcing strategies across the board.
Longer term, AI is poised to knit together secondary and tertiary suppliers, creating end-to-end visibility across entire global networks. This will not always be obvious to patients or even executives. Much of it will happen behind the scenes, as models quietly optimize decisions that once depended on manual spreadsheets or gut instinct.
Beyond AI: Innovation in Patient Communication
It is also important to recognize that supply chain resilience is not only about preventing shortages but managing them transparently when they occur. Patients and providers need clear communication when disruptions are unavoidable. One healthcare provider we studied paired AI-driven supply insights with improved patient engagement tools. When certain cardiology supplies were delayed, the system proactively communicated to administrators and patients, reducing confusion and maintaining trust.
This layer of communication is often overlooked but critical. Even the most sophisticated AI cannot eliminate all shortages, but it can help healthcare systems prepare, respond, and communicate in ways that protect the patient experience.
From Fragility to Resilience
The fragility of pharmaceutical supply chains is not a new problem, but the current wave of drug shortages underscores its urgency. AI is not a silver bullet, but it represents the most practical set of tools available to shore up these lifelines.
By embedding intelligence into demand forecasting, production planning, and upstream risk monitoring, pharma can move from reactive firefighting to proactive resilience. The next three to five years will be decisive: companies that invest now in AI-driven visibility and flexibility will be those best positioned to withstand the next disruption, and ensure that patients are not left waiting when care cannot wait.
About Erik Terjesen
Erik Terjesen is Managing Director at Silicon Foundry, the Kearney-owned innovation advisory firm that helps global corporate executives navigate new technologies and market shifts, discover and engage with key emerging leaders, and unlock high-impact customer, partnership, investment, co-creation, and acquisition opportunities. Members include a diverse set of the world’s leading corporations across a wide range of industries, from entertainment to retail, telecom to transportation, oil & gas to mining, chemicals to cosmetics, life sciences, economic development organizations, and more.
