10 things to know about AI and digital transformation in the U.S. healthcare supply chain.
The pandemic exposed just how fragile healthcare supply chains can be. From sudden shortages of critical supplies to overwhelmed distribution networks, providers and vendors realized they needed more transparency, collaboration and smarter systems.
Enter AI and digital transformation – a wave of technology that promises not just efficiency, but the ability to orchestrate entire supply chains while keeping humans in control.
Here’s what industry leader Cody Fisher, President of Concordance Innovations (which houses Surgence), sees as some key things to understand in the evolving world of healthcare supply chain management:
No. 1: Organizations are leaning in – but at scale, it’s still tricky
Healthcare vendors have historically guarded product information and inventory data, sharing it only when necessary. “The industry has made significant progress in recent years in becoming more willing to share information and data,” Fisher said. This includes upstream constraints, product positions and cross-references – all critical for planning and operations.
Yet sharing data with thousands of individual customers remains challenging. Fisher said, “Well, if I’m a vendor, I may be more open to sharing it, but if I’m sharing it with my providers, that means I have to share it a thousand different times.” Each provider has unique systems and workflows, making manual distribution inefficient and error-prone.
“The organizations now are realizing that sharing the data is only a step in the journey,” Fisher added. “As soon as the data is shared across this blurred line between the vendor and provider, there is little knowledge of what the provider did with that data.” Efficient, scalable solutions are essential to move beyond piecemeal efforts.
No. 2: Collaborative workspace beats data sharing
Real transformation occurs when providers and vendors use the same digital workspace, Fisher said. “We’re bringing the technologies together in a shared workspace, including the shared data. Now, when a customer is making a decision, vendors and customers are making it together.”
Shared workspaces prevent miscommunication and operational inefficiencies. Fisher emphasized the broader goal: “We’re really trying to help the supplier community operate the supply chain that is in between them and their customers … bringing the provider closer to the supplier.”
No. 3: Proactive risk alerts are a game changer
AI-driven platforms now provide real-time alerts on potential supply risks, allowing providers and distributors to act before disruptions occur. “It’s looking at proactive alerts to supply risk,” Fisher said. By analyzing both vendor and provider data, systems can identify items at risk and prioritize actions to prevent shortages or delays.
“This proactive approach replaces reactive problem-solving,” Fisher noted. “We’re working together to collaborate and solve that … we’re helping organizations move away from the chaos from supply constraints to predict the product risks that need attention.”
No. 4: Data alignment underpins smooth operations
Consistency across systems – from product codes and units of measure to pricing and contract terms – is crucial. Misalignments can result in errors, delays or financial impact.
Platforms that ensure alignment in real time reduce errors and allow confident operations. “We’re bringing that data into a shared workspace to ensure organizations aren’t just maintaining their own data. But also, as a supplier, I’m helping my provider maintain my data in their system,” Fisher said.
“Most of the data in our supply chain is dynamic. Organizations are adding items, removing items, changing descriptions, changing units of measure, but it is imperative trading partners are managing the data together,” he said.
No. 5: AI keeps data clean and actionable
AI plays a vital role in maintaining data quality. “AI can simply just help at the data layer. Organizations fall into the myth that I can’t automate until my data is clean, but the truth is AI and automation can help ensure your data is clean at the foundational level,” Fisher said.
“It makes it less about data management as a project. We can actively run that kind of data health all the time,” he said. This frees teams to focus on higher-value tasks like optimizing decisions and operations. “While you’re running your business, how do we increase the health of your data and make it as optimal as it can be?”
No. 6: AI moves transactions to workflow
Providers and distributors process tens of thousands of orders daily. The right AI tools prioritize which transactions need attention, where is there risk and how do I solve my challenge,” Fisher said. “We’re really automating the workflow, bringing clarity to tens of thousands of transactions that happen on any given day,” he added.
No. 7: Conversational AI enhances human capacity
Generative AI agents act as if each person has a team of virtual experts embedded in platforms. “One agent can make it feel as if you have a team of 20 people,” Fisher said. They help navigate data, locate inventory and answer operational questions in seconds.
“When you send a question to an agent, it’s coming back to you in seconds,” he said, compared with minutes or hours via email. “We need to learn to manage expectations of agents like people; while they aren’t always correct, neither are teams delivering answers – one happens in seconds and the other happens in minutes, hours or days.”
No. 8: Change occurs when pain exceeds comfort
Organizations tend to adopt technology fastest when the cost of staying the same outweighs the effort to change. “The organizations that have to might not do it perfectly, but they are the organizations moving the fastest and making the most progress,” Fisher said. “The organizations that want to innovate, but don’t feel they have to change, are trickier. The reasons for not changing are usually pretty simple. They either don’t want to, or they don’t feel the urgency yet.”
No. 9: Security and sovereignty are still top priorities
As organizations adopt AI and share data, cybersecurity and risk continue to be critical. “Picking the right technology and making sure your partners can structure technology in alignment with your security standards is a non-negotiable,” Fisher said.
“The organization’s best data is always their own first. Everything else is an insight that can be categorized and prioritized,” he added.
No. 10: Humans remain essential
The future blends automation with human oversight. “Humans in the loop are important. There are patients and clinicians on the other end,” Fisher said. AI handles orchestration, data analysis and routine workflows, while humans remain responsible for judgment and safety.
“AI automation and digital transformation around data are really going to enable organizations to grow at a scale, to do a volume of work that we never have really been able to fathom,” he said.
The future is now
Digital transformation and AI are no longer futuristic concepts. They are active, strategic tools reshaping the world and more specifically healthcare supply chains today. By combining automation, collaboration, and human expertise, providers and vendors can not only survive disruptions, but thrive with unprecedented efficiency.
As Fisher put it, “We carry the badge of responsibility to position organizations to operate the best they can.”