Healthcare has plenty of data. The real challenge is making it work together

An estimated 97 percent of data produced by hospitals goes unused. Yet the constraint holding many health systems back isn't a shortage of information—it's the opposite. Hospitals generate extraordinary amounts of data every day, with too little reaching the right clinician, in the right workflow, at the right moment.

In conversations with clinicians and health system leaders, I hear a consistent concern: technology may be advancing quickly, but the daily experience of delivering care feels fragmented. We have piloted the tools, built the platforms and expanded the infrastructure. What we have not yet done, at scale, is connect them.

The next era of healthcare artificial intelligence (AI) will not be defined by the organization with the most algorithms. It will be shaped by how effectively intelligence connects across the patient's journey. The opportunity now is how we orchestrate the people, data and technology involved in care instead of adding another isolated capability.

Why isn't more data improving care?

A single imaging exam can produce thousands of images, and a patient in intensive care can generate continuous streams of monitoring data. Each data point can be important to a clinician’s decision. But information becomes more useful when it is connected to the appropriate clinical context, workflow and patient at the right time.

That is where many healthcare systems and clinicians can struggle. Care teams work across systems that are not designed to communicate. A radiologist works in one workflow, a cardiologist in another, a care coordinator tries to bridge both, and an administrator looks for the operational picture across all of them. The result isn't just inefficiency—it's friction, for clinicians, health systems and patients alike.

Consider a patient moving from an initial scan to diagnosis, treatment planning and follow-up. Each step may involve a different specialty, device, software environment and clinical team. The opportunity is not simply to apply AI at each individual step but to help carry the relevant context forward so that each team can work from a more complete picture.

What is care orchestration?

Interoperability allows systems to exchange information. Integration brings technology together. Care orchestration goes further: moving the right information, task or action to the right person at the appropriate point in the care journey.

It connects people, data, devices, diagnostics, software and workflows so care teams can act with fuller context. A point solution can support a single moment. Orchestration connects the moments.

Deloitte's 2026 Global Health Care Outlook found that only about 30 percent of health systems report running generative AI at scale and just 2 percent have deployed it across the enterprise. The opportunity to really see the transformative power of AI to improve care orchestration is vast—to scale within clinical workflows where care actually happens.

Start with the clinical workflow, not the hype of any new technology

What leaders increasingly ask is not whether another AI application exists. They ask whether it will work within their infrastructure, earn clinicians’ trust and help simplify the way care is delivered.

The most effective strategy starts with practical questions:

• Where is healthcare harder than it needs to be?
• Where are clinicians spending time on repetitive tasks?
• Where is information hard to find?
• Which systems can be connected to more seamlessly share information?
• Where is patient care delayed?

AI should be used where it addresses a clearly defined clinical, operational or patient need, not simply because it is available.

And clinicians agree the need is real. While only 30 percent of health systems have reported running generative AI at scale, Doximity's 2026 State of AI in Medicine Report, drawing on more than 3,100 U.S. physicians found that over 90 percent are already using AI or are interested in doing so. When AI fits into the way clinicians work, it can earn its place. When it adds complexity, it risks becoming one more tool to manage.

Why care orchestration is human, enhanced by AI

This is why care orchestration is fundamentally a human idea. AI can help enable it, but the goal is not to place technology at the center of care. The goal is to help people work with greater clarity, context and coordination.

The questions that matter are human ones:

• How can AI help clinicians spend less time on administrative tasks and more time caring for patients?
• How can AI help care teams see, diagnose and treat what matters most, sooner?
• How can AI create a more connected experience for patients?

Across healthcare, we are already seeing examples of AI designed to support diagnostic processes, extend access across care settings and simplify parts of the patient experience. When developed with clinicians and implemented responsibly, AI should support, not replace, clinical judgment and experience.

The measure of progress is whether technology helps care teams work together more effectively, not simply take over tasks.

Trust will ultimately determine which technologies scale. Clinicians need confidence that tools are designed for real clinical use. Health systems need confidence that they can be implemented responsibly within complex operational and technology environments. Patients need confidence that their care keeps the human connection at its center.

Trust depends on governance, transparency, interoperability and careful implementation—with partnership across everyone who delivers care.

From more technology to better-connected care

At GE HealthCare, our perspective is shaped by working across many of the clinical technologies and workflows that contribute to a patient’s journey. That breadth reinforces a simple lesson: no single device, application or algorithm can create connected care on its own.

The greater opportunity is to help bring together medical technologies, diagnostics, AI, cloud software and clinical workflows so relevant information can move more effectively across the care journey.

Healthcare does not need AI for AI's sake. It needs AI grounded in solving real clinical challenges—AI that connects the data, devices and workflows already shaping the patient's journey.

The industry has spent years asking what AI can do. The more important question now is what healthcare needs AI to help solve. The leaders who shape healthcare’s next chapter will not ask about AI adoption but ask whether AI can be responsibly connected to the people, systems and decisions that define care. That is how AI moves from an impressive capability to critical infrastructure—and how healthcare moves from more technology to better-coordinated care.