Healthcare is entering a new era where AI doesn’t just help, it orchestrates.
From predictive analytics to generative models and now agentic intelligence, each step has redefined how providers deliver care and manage operations. The latest shift toward agentic AI promises to transform care delivery and administrative functions by acting as an orchestrator between systems, workflows and data sources.
The shift from predictive to generative AI
Early applications of AI in healthcare focused on predictive analytics, with an emphasis on identifying high-risk patients, predicting disease progression, and optimizing resource allocation. These tools were valuable but largely complex to create and maintain, requiring human intervention to act on the information obtained.
Generative AI has introduced a new paradigm. Large Language Models (LLMs) enable organizations to work faster, supporting providers by generating clinical documentation, summarizing patient histories, and completing prior authorization requests. These use cases reduce administrative burden and improve efficiency, but generative AI has remained task-specific: it creates content but cannot coordinate complex workflows across systems. Generative AI alone cannot fully accomplish most tasks.
The rise of agentic AI
Agentic AI represents the next evolution: autonomous, goal-driven systems capable of orchestrating end-to-end workflows across multiple platforms. Unlike generative AI, which creates content, agentic AI executes and manages tasks across systems, acting as a true orchestrator rather than a passive coordinator, connecting EHRs, scheduling tools, payer portals, and patient engagement platforms to deliver seamless experiences for providers and patients.
Agentic AI connects disparate resources and can perform tasks unilaterally, moving beyond simple responses to proactively manage entire workflows from start to finish. This means less time navigating disparate systems and more time focusing on patient care.
How Agentic AI Creates a Seamless Supplier Experience
Today’s healthcare environment is fragmented: multiple platforms, disparate processes and conflicting communications. Agentic AI reduces friction by executing multi-step processes that traditionally require manual intervention.
1. Management of prior authorizations
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Current status: Providers spend hours gathering documentation, submitting forms, and following up with payers.
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Impact of agentic AI: Faster approvals and less back and forth. An AI agent can accurately determine whether prior authorization is required for a specific procedure, retrieve necessary clinical data from the EHR, complete payer-specific forms, submit requests, and monitor status. If additional documents are required, the agent can proactively alert suppliers.
2. Coordination of care across settings
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Current status: Discharge planning and tracking often requires care coordinators to contact patients multiple times via email or phone and manually schedule appointments.
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Impact of agentic AI: Streamlined continuity of care and reduced administrative costs. An agent can automatically schedule follow-up appointments, arrange home health services, update the patient portal, and send reminders to patients in a timely manner, all without provider intervention.
3. Clinical documentation and coding
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Current status: Providers dictate notes, which are then reviewed and coded manually.
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Impact of agentic AI: Improved compliance and a faster revenue cycle. An AI agent can listen during the meeting, generate structured documentation, apply precise coding and submit complaints, all in real time. The role of the coding team now shifts to reviewing, editing, and refining the coding of complex claims. Humans remain essential, but agentic AI elevates their role by shifting attention from routine tasks to higher-value decision-making.
Positive impact on patient experience
When providers are freed from administrative constraints, patients benefit from more attentive and personalized care. Agentic AI also directly improves patient engagement:
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Faster access to care: Automated scheduling and pre-authorization reduce delays.
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Improved communication: AI agents send timely updates, reminders and educational materials.
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Consistency between touchpoints: When data is shared and technology is standardized, patients experience a unified journey, regardless of the context of care.
Consider using AI to monitor patient wearable sensors. An agent that continuously monitors sensors can detect early signs of sepsis or heart failure, automatically alert clinicians, and even recommend changes to treatment plans, perhaps before the patient or provider even notices symptoms.
For access-related tasks, a multi-agent “navigator” can streamline the entire appointment lifecycle, verifying patient identity, checking availability, rescheduling and updating records directly in the EHR, without any manual intervention. From the patient’s perspective, this means fewer missed appointments, a faster scheduling process, and a personalized care journey in which AI helps them complete tasks specific to their needs rather than following a template.
What’s next
Despite these advantages, several obstacles remain. According to a recent Guidehouse survey, nearly 50% of healthcare executives say they face cybersecurity, data privacy, and financial barriers when implementing AI. More than 40% cited concerns about data quality, standardization, availability or governance.
Data access and quality of integration continue to be the primary barrier to a smooth transition to agentic AI, as many systems struggle with fragmented EHRs and inconsistent information exchange. Regulatory and ethical concerns are also important, as autonomous decision-making must be transparent, verifiable and aligned with clinical governance. Deployment costs are significant: from $50,000 for specialized agents to over $1 million for enterprise-wide systems. Clinicians also worry that excessive automation could erode patients’ trust or critical thinking.
The shift from predictive analytics to generative AI and now agentic intelligence marks a pivotal moment in healthcare innovation. Agentic AI is not just another technology upgrade: it is a paradigm shift that brings us closer to a future where healthcare is proactive, personalized and frictionless. Organizations looking to harness the full potential of AI should consider these best practices:
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Establish governance: Align use cases with strategic priorities and ensure transparency.
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Develop a roadmap: Write a plan of the capabilities you would like your organization to develop and update every 6 to 12 months to keep pace with rapid change.
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Establish partnerships: Collaborate with technology providers to create scalable and sustainable solutions.
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Consider creating an AI Center of Excellence (CoE): A cross-functional team dedicated to AI success can help your organization define its vision, talent, security, standards and KPIs.
Agentic AI is not a simple upgrade, it is a shift aimed at transforming fragmented processes into a unified, intelligent ecosystem. By acting as an orchestrator, it empowers providers, improves the patient experience, and lays the foundation for scalable, value-based care.