Three reasons academic medical centers are embracing a buy-and-build platform AI approach

Academic medical centers (AMCs) have long been early adopters of technology, using it to solve problems across care, research, and education. But too often, that tech becomes a patchwork of point solutions that don’t scale, don’t communicate effectively, and can’t keep pace with operational complexity.

That’s why leading AMCs are embracing platform thinking with an integrated, AI‑powered approach.

The buy-and-build platform approach

When it comes to AI-powered tools, AMCs feel they must face a tradeoff: build internally to maintain control, or buy off-the-shelf and risk being boxed in. Neither option alone is ideal.

A buy-and-build platform model offers a third, and better, path. It combines the speed of pre-built, EHR-integrated workflows with the flexibility to tailor and expand them using intuitive, low-code tools. For AMCs navigating operational complexity, regulatory pressure, and stretched IT teams, that balance is critical.

Here’s how a buy-and-build model delivers value for AMCs:

It gives teams control without starting from scratch

AMCs often develop their own internal solutions to meet highly specific needs; however, building from the ground up can be resource-intensive and time-consuming. A buy-and-build platform offers the best of both worlds: it brings pre-built, proven AI Agents and components that can be rapidly deployed, while still allowing teams to customize and build on top of them using intuitive tools. 

This approach empowers innovation teams, IT teams, and operational leaders to adapt workflows for subspecialties, research protocols, or campus-specific nuances, without having to engineer an AI model from scratch. Whether it’s automating research participant onboarding or customizing a scheduling flow for a multi-campus practice, AMCs gain agility without sacrificing precision. 

It accelerates value across the enterprise

In large academic systems, implementation delays and data integration complexity can stall AI initiatives. Using a platform built for healthcare, with deep integration into major EHRs such as Epic and Oracle, accelerates the time to value. A buy-and-build platform should come with preconfigured APIs, connectors, and AI Agents that can be deployed across thousands of sites to solve real-world scale challenges. 

This means AMCs can directly automate scheduling, registration, referrals, care coordination, and revenue cycle management, without waiting a year for IT to build the necessary infrastructure. For AMCs balancing operational excellence with complex compliance and governance needs, this platform approach ensures faster results with enterprise-grade rigor. 

It future-proofs against workforce and innovation pressure

Like much of the healthcare industry, AMCs face urgent workforce shortages and growing administrative burdens. But, on top of that, AMCs are also hubs of innovation, expected to experiment with emerging technologies and lead by example. A buy-and-build platform democratizes AI development, enabling internal teams to create, iterate, and scale AI-powered workflows across diverse service lines without needing to bulk out IT teams when funds for hiring are scarce.

Rather than deploying yet another siloed vendor or building bespoke models that don’t make it to implementation, a unified healthcare AI platform allows AMCs to operationalize innovation across departments and partners. Teams can prototype an AI workflow, gather feedback from clinicians, refine it in real time, and share it system-wide. 

This flexibility not only helps AMCs adapt faster to change, but it also becomes a force multiplier for staff productivity and fulfilling wider academic missions. 

Buy-and-build is the future of healthcare

The Medical University of South Carolina (MUSC Health) faced rising costs and burnout from manual processes across intake, scheduling, collections, and care gap outreach. To efficiently scale its operations without overwhelming staff, MUSC needed a solution that would automate repetitive tasks, drive revenue, and improve patient engagement, while being flexible enough to support diverse use cases across departments.

By choosing a buy-and-build platform approach, MUSC was able to deploy prebuilt AI Agents and customize its own workflows using a low-code interface. This strategy delivered rapid impact: over 5,000 administrative hours saved monthly, a 7.6% reduction in no-shows, and over $3.3M in annual value delivered. Automating multiple care gap workflows also enabled proactive outreach and screening for high-risk patients, demonstrating how a configurable platform can empower an academic medical center to scale smarter and deliver better care.

For AMCs navigating a complex web of clinical, educational, and operational realities, an AI platform is a strategic imperative. A buy-and-build platform approach allows leaders to scale fast, stay in control, and drive continuous innovation across their organizations.

In choosing this path, AMCs aren’t just modernizing operations. They’re defining the future of intelligent healthcare.