The promise of artificial intelligence in healthcare has been a topic of great interest for years. While there have been glimpses of its potential through pilot programs, the healthcare industry is now on the cusp of large-scale deployments. However, there are several significant issues that need to be addressed before this can become a reality. Michael Meucci, the president and CEO of Arcadia, a health data platform company, is actively working on these challenges every day.

Acting on AI Abundance via Workflow Integration

Although pilot programs have demonstrated the potential of AI, true integration into daily workflows remains a rarity. In 2025, scaling successful AI applications will be a top priority. For AI to truly reshape healthcare, it must seamlessly become a part of care team workflows, transitioning from isolated systems to integrated, actionable tools at the point of care.By embedding AI in workflows, healthcare organizations can make a significant leap. Instead of being passive, like ambient listening or automated note-taking, AI can become an active decision support system that clinicians can trust and rely on. Its effectiveness hinges on its ability to support, not interrupt, clinical workflows. Integrating AI into real-time decision-making processes means creating systems where clinicians don't have to step out of their routines or rely on additional tools. Instead, they should have AI-driven insights available directly within their current interfaces and processes, such as the electronic health record. AI should serve as a silent partner, augmenting the abilities of clinical teams without demanding additional steps.For healthcare leaders, it is clear that they need to prioritize investments that enhance workflow integration over isolated AI functionalities. Building infrastructure that facilitates AI's real-time availability and directly feeds into clinical operations will yield sustainable gains. As these systems mature, they will lead to an era of scaled AI deployments, making AI a critical, reliable resource within healthcare delivery.

The Holistic Patient View as the Foundation for AI Application

In 2025, a true holistic patient view will be the cornerstone of AI applications. This requires a robust data infrastructure that harmonizes various data sources, such as clinical, claims data, and social determinants of health data. By doing so, AI can draw insights that support patient-centric care regardless of who interacts with the patient.A comprehensive and longitudinal patient view enhances the value of AI. It provides a reliable foundation of patient data that anyone across the enterprise can trust and leverage. For example, in an AI-driven call center, staff can view not only a patient's insurance benefits but also relevant health information, like open care gaps. This enables agents to answer questions and act with empathy and precision, such as nudging a patient about a screening.The holistic approach means that whether a patient is interacting with clinical staff, support personnel, or even financial services, they receive informed support tailored to their unique health journey. To make this vision a reality, healthcare leaders must prioritize data standardization and invest in systems that promote scalable access to real-time data. With these investments, healthcare organizations can empower every employee to act as a knowledgeable touchpoint in the patient's care journey, enhancing the patient experience through proactive, patient-centered care management.

Reducing Push-Pull Tension in the AI Lifecycle

Healthcare organizations often face a push-pull tension between the drive to adopt AI systems and internal resistance due to regulatory, ethical, and logistical concerns. This tension reflects the broader industry conflict of advancing AI while encountering roadblocks that slow down deployment.To overcome this in 2025, healthcare leaders must adopt strategies that fuel AI innovation while streamlining governance, compliance, and risk management. AI should be established as a core component of their operations without creating additional hurdles. The acceleration of AI should be purposeful, targeting high-impact tasks that can be automated to free up human resources for higher-value work.Healthcare executives should start by identifying low-value, time-consuming tasks that AI can take over, such as data entry or basic patient queries. Delegating these tasks to AI enables clinicians and their staff to focus on complex, patient-facing interactions. Strategically automating repetitive functions will help organizations improve productivity and reinvest the gains in expanding the reach and effectiveness of AI systems across the enterprise.