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Experts are reporting that healthcare providers will face several significant operational challenges in 2026, including rising costs and workforce shortages. To overcome the challenges, some providers will look to deploy artificial intelligence in ways that empower greater levels of efficiency.
“AI has already proven it has the power to streamline workflows and fast-track data analytics,” says Chris Hutchins, Founder and CEO of Hutchins Data Strategy Consulting. “Imagine how the capabilities of AI could aid healthcare professionals if properly applied. AI could be the solution the health system needs to move from crisis to credibility.”
Hutchins is a nationally recognized leader in healthcare analytics and AI strategy who has over 30 years of experience helping hospitals and healthcare organizations leverage medical data and technology to improve patient care. As the Founder and CEO of Hutchins Data Strategy Consultants, he partners with organizations to unlock the full value of their data through ethical, scalable strategies. Hutchins combines deep technical expertise with a human-centered approach, ensuring AI systems and other technology solutions serve patients, providers, and administrators alike.
“AI technologies have the potential to close the care gaps that are eroding trust in the US healthcare system,” Hutchins says. “And 2026 promises to be the year they play a transformative role in healthcare delivery.”
Artificial intelligence will continue to fill gaps in the healthcare system
AI has already made inroads in the healthcare sector as an automation tool, helping in areas that involve structured, repeatable workflows. As 2026 unfolds, the use of AI automations will continue to expand most rapidly in areas where cost pressures and staffing constraints are most pronounced.
“Functions like prior authorization, claims management, scheduling, documentation, and contact center triage are especially well suited for AI tools,” Hutchins says. “Overall, providers will be looking to use AI to strengthen operations in those areas that are essential to the financial and operational health of the organization.”
The adoption of AI tools will also most likely move beyond administrative functions, such as the harmonization of electronic health records, and into the clinical space. Recent reports show that a number of AI tools, including those that leverage generative AI to help communicate with patients, are entering the exam room.
“Clinical integration is taking shape, but the approach will remain measured,” Hutchins says. “There is a growing emphasis on embedded tools that operate inside the clinician’s existing workflow. AI will become more common in the clinical environment, but it will do so as a supportive resource rather than a decision-maker. The goal is not to build digital doctors, but to make human care more sustainable and more informed.”
Emerging capabilities will boost the benefits of AI in healthcare
Key advances in the application of AI have created promising solutions for some of the most pressing issues in the healthcare industry. One of those solutions — ambient AI — is poised to play a central role in how healthcare is delivered in 2026.
“Ambient documentation, along with multimodal assistant tools, is becoming more capable,” Hutchins says. “They convert real-time conversations, historical health data, labs, and medical images into structured clinical documentation, order sets, and patient instructions. When done right, they reduce the administrative burden on clinicians and give time back to patient care. But the speed of adoption has outpaced governance in some cases. Recent litigation around consent practices, particularly when AI auto-generates documentation from recorded conversations, is a reminder that the ‘how’ matters as much as the ‘what.’”
Orchestration layers will also play a larger role in healthcare AI in 2026, enabling providers to coordinate inputs from models, guidelines, benefits information, and medical history to surface a unified care plan within existing systems. Better orchestration enables healthcare clinicians to move from data gathering to decision-making more efficiently.
“Tools like ambient AI and orchestration layers allow AI to become part of the operational foundation rather than a disconnected experiment,” Hutchins explains. “They help transform the industry from a landscape of scattered pilots to one of governed, aligned, and observable impact. Ambient AI captures the data. Orchestration layers make it actionable.”
Fostering cultural change will be a key challenge in AI adoption
For AI integration to optimally transform health outcomes, healthcare leaders must commit to transforming the culture within their organizations. AI models, despite their improvements, still have their limitations. Doctors and other healthcare professionals who rely on AI must be aware of those limitations.
“The greatest risks are not technical failures,” Hutchins warns. “They are operational missteps that stem from deploying AI in the wrong place or without proper oversight. When clinicians are asked to trust AI outputs but do not understand the limitations caused by automation bias, there is a risk of over-reliance. These risks will not be solved by regulation alone. They require culture change, technical stewardship, and operational accountability at the local level.”
Recent research underscores these concerns. Studies evaluating AI scribes report hallucination rates of 1-3%, with 44% classified as “major” errors, meaning they could affect diagnosis or treatment if left uncorrected. Fabrications account for 43% of hallucinations, followed by negations at 30% (where the AI contradicts what was actually said). These errors appear most frequently in the Plan section of clinical notes (21%) — the very section that contains direct instructions for patient care.
These are not edge cases. They are predictable patterns that require governance structures designed to catch them.
AI applications in healthcare will move into the integration phase
The past few years of AI development have involved heavy experimentation in the field of healthcare, with countless dollars spent pursuing the creation of innovative medical devices and other new AI solutions. In 2026, experimentation with AI will take a backseat to its integration, with organizations seeking healthcare applications that fit into their workflows, are transparent in purpose, and can be monitored and improved over time.
“The most successful deployments of AI programs will help clinicians and staff work more effectively without removing their ability to question, adjust, or override,” Hutchins says. “AI’s viability in 2026 and beyond will depend on whether care teams see it as a tool that protects their time, supports their decisions, and strengthens their connection to the patient.”
