AI in healthcare has reached a critical inflection point. Across the industry, organizations are investing heavily in artificial intelligence, believing it will revolutionize patient care, reduce administrative burdens and boost efficiency. Yet, despite billions in spending, the returns have been underwhelming. A recent MIT report found that while enterprises are investing between $30 and $40 billion in generative AI, more than 95% are seeing no measurable ROI. In healthcare, where every minute and every data point matters, this paradox raises a crucial question: why?
The problem begins with hype outpacing reality. Too often, AI projects are launched with excitement around generative capabilities but little attention to practical integration. The results are workflow bottlenecks, friction, and misalignment. When projects are driven by technology rather than the user, they solve the wrong problems in the wrong ways. Because clinicians and staff are already stretched thin, even the best-intentioned AI deployment can erode trust if it disrupts established workflows.
The real challenge isn’t developing the technology—it’s embedding it meaningfully. Consider an organization that built a GenAI-based solution to help call center auditors analyze and understand member interactions. The solution included an impressive dashboard of insights, but the auditors rarely used it because they had to log into a separate tool, outside their normal workflow. A rollout that appeared successful on paper failed in practice because it added friction instead of reducing it. AI must meet users where they are, not where developers assume they’ll go.
Healthcare organizations that get AI right take a different approach. They integrate solutions alongside core systems rather than building stand-alone tools. Consider another organization that developed an AI-based solution to accelerate prior authorization reviews. The AI ingested data from prior authorization requests, accompanying electronic health record information, analyzed member information, and presented a case summary for approval—all within the clinician’s existing environment. This use case succeeded not because it was technologically sophisticated, but because it fit seamlessly into the decision-making process.
This principle—intelligence that works in the background—is at the heart of the next evolution in healthcare AI. One example is Nia™, NextGen Healthcare’s intelligent orchestrator agent designed to transform how providers and staff interact with the EHR. Through natural voice or text, Nia interprets intent and seamlessly coordinates a network of specialized AI agents, each with its own domain expertise. These agents autonomously execute tasks across clinical, financial, and operational workflows, from retrieving patient insights and summarizing encounters to managing schedules, verifying coverage, and streamlining documentation. By enabling proactive, hands-free interaction and intelligent delegation, Nia redefines the EHR experience—freeing providers and staff to focus on what matters most: delivering exceptional patient care.
Healthcare leaders can avoid the 95% failure trap by viewing AI implementation through the lens of workflow design, measurement, and governance. Projects should begin with a clear problem statement—rooted in user needs—and a measurable outcome framework. Teams must define the appropriate success metrics, maintain integrations with existing systems, and consider change management. Strategic frameworks like opportunity scoring, which evaluate potential impact and implementation friction, can help organizations prioritize use cases with real potential for ROI.
Finally, success depends on balance: the right combination of people, processes, and technology. Governance committees that include clinical informatics experts, data scientists, and frontline users ensure alignment between vision and reality. Only when healthcare organizations approach AI as a long-term partnership between innovation and execution—not a quick experiment—can they move from pilot projects to scalable, sustainable success.
The path forward isn’t about deploying more AI. It’s about deploying AI that matters—solutions that solve real problems, reduce friction, and strengthen trust across the care continuum. When AI becomes invisible, integrated, and indispensable to the daily workflow, healthcare will finally start seeing the returns it’s been promised all along.
To learn more about how NextGen Healthcare is reimagining the patient, provider, and staff experience, visit nextgen.com. For a demo of NextGen Healthcare’s AI capabilities, click here.
