From reactive to predictive: How AI is reshaping pharmaceutical distribution

Throughout the healthcare ecosystem, organizations are making significant investments in AI-powered capabilities. Those capabilities are addressing some of the industry’s most pressing questions:

1. How can distributors identify supply issues before they become shortages?
2. How can products move through the network more efficiently?
3. How can timely, accurate information be more accessible when questions arise?
4. How can providers spend less time managing supply uncertainty and more time caring for patients?

The value of a distribution partnership increasingly depends on addressing each priority. AI helps tackle the first by connecting information that once existed in separate systems and uncovering patterns that are hard to detect manually. It addresses the second by improving forecasting and optimizing inventory positions in tandem with automation and advanced analytics. Earlier visibility supports the third by giving distributors greater leeway to communicate proactively with providers as conditions change.

The fourth reflects the cumulative impact of the first three. As providers and distributors share information about demand patterns and operational priorities, AI gets a more complete picture of the supply chain. Those insights help both parties anticipate change earlier, coordinate more effectively, and continuously improve service. The result is a supply chain that's more responsive and more predictable, putting providers in a better position to maintain continuity of care.

As AI becomes more embedded in healthcare operations, successful partnerships will depend on how well AI and people work together. Providers need distribution partners that pair advanced capabilities with practical human experience. They also need transparency into how AI is applied and accountability for the decisions that follow.

That starts with responsible use. AI models need reliable data, appropriate governance, and ongoing evaluation as supply conditions change. Human expertise remains essential to effectively incorporate it across workflows and interpret and act on the patterns and recommendations that AI surfaces. People understand context. Experienced professionals assess tradeoffs, manage exceptions, and make decisions that affect patients and providers. “The opportunity is understanding where AI creates the greatest value and where human expertise continues to make the difference,” says Ken Hardy, Cencora’s senior vice president of U.S. supply chain operations.

Trust also grows through experience. Providers want to see practical examples of how AI and technology-advanced distribution operations are improving service, supporting medication availability, and helping teams respond more quickly when conditions change. Those conversations also help distributors better understand provider priorities and identify opportunities where AI can reduce administrative burden or improve day-to-day operations. “When providers and distributors are working from the same information, they can respond to risk earlier and make better decisions together," notes Matt Sample, Cencora’s senior vice president of manufacturer, quality, and replenishment operations.

The most effective partnerships combine technology, data, and human expertise. Working together, distributors and providers can apply AI to solve operational challenges while keeping the focus on patient care.

With proven applications already in place across the healthcare supply chain, Cencora is moving beyond experimentation by investigating innovative ways for AI technology to improve supply chain resiliency and effectiveness. The focus is on advancing operations in ways that elevate the provider experience through better service, greater reliability, and faster responses. All of this work is governed by a responsible AI framework built specifically for regulated healthcare — because in this industry, trust isn't optional.

One current application increases supply chain resilience. AI-powered analytics can identify nascent supply risks by connecting information across manufacturers, suppliers, products, and distribution pathways. That broader view helps us recognize potential issues earlier. At Cencora, AI provides near-real-time visibility into potential disruptions, allowing our teams to coordinate responses sooner and communicate more proactively. 

Demand forecasting is another area where AI is already creating value. By combining historical demand patterns with current market signals, product-level data, and operational inputs, AI outputs help team members anticipate changes in demand before they affect providers. That supports better purchasing and inventory decisions, improving product availability while reducing the likelihood of unexpected disruptions.

AI is also helping Cencora deliver a more responsive customer experience. By surfacing relevant information more quickly and supporting self-service capabilities where appropriate, AI helps providers access answers faster while enabling customer-facing teams to resolve more complex issues. Experienced professionals continue to use operational expertise to handle exceptions, evaluate changing conditions, and determine the best course of action.

Together, these examples show how Cencora is embedding AI across the healthcare supply chain. By helping anticipate disruptions, improve medication availability, and create a more connected, responsive experience, AI enables providers to spend less time managing supply uncertainty and more time focused on patient care.

AI will continue to evolve, but its long-term value will depend on more than technology itself. It will be contingent upon the human intelligence and creativity behind the scenes with the vision for what’s possible and can execute.

 In the near term, AI can be applied across the healthcare supply chain to help teams work more productively and make better decisions earlier. These improvements can simplify day-to-day workflows and enable quicker responses as conditions change. Over time, AI may support more personalized customer experiences and new ways of serving providers.

Human expertise will remain essential because healthcare rarely presents perfect conditions. AI can identify patterns and recommend actions, but people apply context and judgment to make final decisions. They’re ultimately the ones who are accountable for the decisions that affect providers and patients.

As AI capabilities mature, the greatest opportunities will come from applying them across end-to-end workflows rather than individual tasks. That opens the door to closer collaboration between providers and distributors, from demand forecasting and inventory planning to issue resolution and service improvement.

Organizations don't have to evaluate AI on their own. Resources like the Community Oncology Alliance's AI Playbook (available here, registration required) provide practical guidance for identifying high-value use cases, establishing governance, and implementing AI responsibly. As providers and distributors continue to work together, these frameworks can help organizations apply AI in ways that improve operations and support for patient care.