Hospitals Struggle to Scale AI Despite Successful Pilots

Artificial intelligence (AI) has the potential to transform healthcare by improving patient outcomes, streamlining operations, and enhancing decision-making. However, a recent survey conducted by Carta Healthcare reveals that while many healthcare organizations have successfully piloted AI initiatives, scaling these efforts remains a significant challenge.

Brent Dover, CEO of Carta Healthcare, explains that 71% of healthcare organizations reporting measurable value from AI are still not expanding those initiatives at the pace needed for enterprise-wide adoption. "The most useful thing about this finding is what it rules out," he says. "The pilots proved that AI can deliver value. What stalls is everything that comes after the proof."

Pilot projects often succeed because they are intentionally narrow, with a committed champion, a clearly defined workflow, and concentrated organizational attention. However, when organizations attempt to scale these projects across departments, those favorable conditions tend to evaporate. "Success in a controlled setting tells you the model is capable," Dover explains. "It does not tell you the organization is ready to operationalize it."

Operational Challenges Beyond AI

Health systems face numerous operational challenges that can hinder the expansion of AI initiatives. These include competing priorities, budget pressures, inconsistent workflows, and unclear accountability. According to the survey, electronic health record (EHR) integration has overtaken trust as the leading barrier to AI adoption.

EHR integration is a critical factor because it ensures that AI systems can access and utilize patient data effectively. However, integrating AI with existing EHRs requires significant technical expertise and resources. "EHRs are the backbone of clinical operations," says Dover. "If AI cannot seamlessly integrate with these systems, its potential benefits will be limited."

the survey highlights a shift in leadership ownership. More clinical leaders are now taking ownership of AI strategy, recognizing that technology alone is not enough to drive successful implementation. "Clinical leaders understand the importance of aligning AI initiatives with organizational goals and workflows," Dover notes.

The role of human oversight remains crucial in healthcare AI applications. Kevin Kennedy, a medical professional, emphasizes that clinical decisions carry real consequences, so every AI-supported call needs a human in the loop and a full trail showing how it was reached. "In healthcare, 'the AI recommended it' is not an answer anyone can act on without scrutiny," he says.

What Comes Next

To overcome these challenges and achieve scalable AI integration, healthcare organizations must address both technological and organizational barriers. This involves fostering a culture of collaboration between IT and clinical teams, ensuring that AI initiatives are aligned with broader strategic goals, and providing the necessary resources for successful implementation.

Dover suggests that hospitals can start by conducting thorough assessments of their current workflows and identifying areas where AI can add the most value. "It's essential to have a clear understanding of what you want to achieve with AI," he says. "This will help you prioritize initiatives and allocate resources effectively."

organizations should focus on building robust data governance frameworks to ensure that patient data is used ethically and securely. This includes implementing transparent processes for data collection, storage, and analysis, as well as establishing clear guidelines for AI decision-making.

As the healthcare industry continues to explore the potential of AI, it's important to balance innovation with practical implementation. By addressing the operational challenges that hinder scalability, hospitals can unlock the full potential of AI to improve patient care and drive better outcomes.

Ultimately, the success of AI in healthcare will depend on a collaborative effort between technology providers, clinical leaders, and organizational stakeholders. "AI has the power to transform healthcare, but it requires a concerted effort from all parties involved," Dover concludes. "Only then can we ensure that these promising technologies become a seamless part of everyday clinical practice."