There is strong industry optimism about AI’s potential to transform healthcare operations this year, though some areas are more ripe for near-term impact than others. Many experts believe that the clinical supply chain is primed for widespread adoption, and a McKinsey and Company report predicts AI will begin powering real-time inventory, predictive replenishment and procurement automation.
In short, this isn’t just another “innovation year” for the healthcare supply chain. The industry will experience a notable shift that will move operations from reactive to predictive — and from operational support to clinical enabler.
This is good news given the fallout from persistent supply shortages along with renewed tariff uncertainty and ongoing margin compression. In this environment, incremental improvements and better dashboards will not overcome the immense pressures placed on supply chain professionals. And the shortcomings can produce negative impacts to patient care, clinical outcomes and operational margin.
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The real value of AI will be its ability to compress the cycle from question to insight to action on the clinical front. Large language model (LLM) infrastructures designed for analyzing massive volumes of data will begin returning precise, actionable insights in near real-time to supply chain professionals.
Supply chain professionals can expect agentic AI solutions to begin influencing everything from demand planning and inventory optimization to purchasing timing, transaction processing and payment. In addition, many professionals believe AI can help accelerate and improve contracting timelines. Those processes have historically been painstakingly slow and manual.
The question is where will healthcare see the greatest value? Outlined below are five use cases that define the greatest ROI for leveraging agentic AI for clinical supply chain operations in the coming year.
- Turning clinical spend intelligence into cost savings
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Health system CFOs are no longer satisfied with isolated savings wins, especially when it comes to supply chain, which is one of the largest controllable expense areas of operations. The C-suite is looking to leaders to identify sustainable cost efficiencies that are auditable and hardwired into workflows.
This is where AI agents can deliver by continuously monitoring performance and recommending targeted, compliant interventions. In addition, these tools can holistically unify cost, quality outcomes and reimbursement into one actionable view — a significant step forward as many healthcare cost initiatives stall when the focus can’t translate into physician- and procedure-level execution. Sustainable performance requires aligning financial impact with clinical reality and embedding it into daily operations.
- Operating room efficiencies
Considered one of healthcare’s most persistent waste zones, the operating room (OR) is a tremendous ROI opportunity for AI. When health systems can get ahead of procedure and preference card management specifically, they can cut unnecessary supply use and align inventory with what is consumed, rather than just supplies historically listed.
AI agents can help move preference card management from occasional “cleanup” initiatives to continuous optimization by flagging pick-list variances in real time, comparing physician preference patterns, identifying standardization opportunities and automatically routing recommendations through appropriate channels.
- Surgical site infection reduction
More health systems will elevate infection prevention strategies and leverage AI to support higher-level clinical and operational programs. This move is understandable since the financial consequences associated with readmissions, penalties and extended length of stay are too large to manage with retrospective reporting alone.
AI agents can reduce surgical site infections by shifting prevention strategies from reactive to proactive, real-time risk management. Consider the impact of having the following data available in real-time:
- Identification of high-risk patients before surgery
- Proper antibiotic timing and selection
- Ongoing monitoring of sterile field and OR traffic patterns
- Post-discharge surveillance
By integrating clinical, operational and supply data, AI also detects product-related risks and variation in practice patterns.
- Greater ROI for robotic -assisted surgery programs
Robotic surgery is growing fast, but making the economics work for these expensive investments isn’t simple. There are many factors to consider from upfront capital cost and service contracts to case volume, surgeon ramp-up time and ever-changing reimbursement.
AI agents can bring the full financial and clinical picture into one place. In 2026, as margin pressure increases, hospitals won’t be able to justify robotic programs on hype alone. The winners will be the ones who connect the dots to supply use, outcomes operating room efficiency and payer reimbursement to optimize programs and deliver ROI.
- Management of purchased services
Often characterized as the “hidden spend” of healthcare, purchased services are notoriously difficult to manage. In many healthcare organizations, associated invoices lack standardization, while contracts are scattered across departments. In addition, categorization is labor-intensive and often a non-starter for resource-strapped healthcare organizations.
AI agents can help supply chain leaders get control of all these disparate issues and eliminate manual classification. Purchased services will be a prime domain for AI agents because the work is repetitive, data is semi-structured and workflows (classification, variance detection, contract compliance) can be automated with human oversight.
Overcoming pitfalls to AI deployment
AI is only as good as the data available to it. Unfortunately, data remains one of the greatest challenges to its adoption in the healthcare supply chain. An October 2025 Experian survey found that 41% of healthcare decision makers cited data accuracy as a barrier to AI adoption, pointing to inaccurate item masters, misaligned contract data and inconsistent standards.
Like many areas across healthcare departments and operations, supply chain suffers from lack of a common language, making data normalization and comparison difficult. Frequent product number changes and inconsistent naming conventions only add complexity. That’s why 2026 is shaping up to be the year data moves from a supporting role to the operational foundation of execution, as AI, automation and interoperability become deeply embedded in supply chain operations.
Healthcare organizations have historically managed data in silos. For example, supply chain owns procurement and contract data, while clinical teams manage EHR and outcomes data. For AI to truly impact transformation, each function must take ownership for data accuracy through shared governance that enables agentic AI to deliver optimal value. When supply chain professionals trust that the aggregation of clinical, financial and supply chain data are meaningful, tremendous opportunities exist for identifying meaningful outliers, such as variations in cost, quality or total case expense.
The year of supply chain disruption
This year marks a turning point with clinical supply chain and AI. Mounting financial pressure, ongoing supply chain risk and the rise of mature agentic architectures are converging to make AI agents a practical necessity. The conversation will move beyond “Do we have AI?” to “Is our AI actively running and improving the business?”
Photo: Dilok Klaisataporn, Getty Images
John Wright is Chief Operating Officer at Advantus Health Partners, a health care solutions company that makes supply chain easier for its clients through streamlined supply chain management, organizational purchasing, operations and cost-savings efficiencies. With more than 25 years of experience as a health care operator, John is recognized for his strong track record of maximizing efficiencies and reducing costs. At Advantus Health Partners, John is responsible for the overall success of the supply chain, including production planning, inventory management, integrated logistics and consulting services that provide customized solutions to complex challenges faced in health care. Previously, John was vice president of supply chain and support services operations at Intermountain Healthcare. John holds a bachelor’s degree in biology and a master’s in business administration from Virginia Tech and has served as a Sergeant in the Virginia Army National Guard.
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