Agentic AI in Healthcare: Automating Clinical and Administrative Workflows

Healthcare is at a pivotal crossroads. The industry faces mounting administrative burdens, fragmented data systems, and a growing demand for better patient and provider experiences—all within a landscape defined by strict regulatory oversight. Enter agentic AI: a new generation of autonomous, goal-driven systems that are transforming healthcare operations by automating complex workflows, orchestrating clinical processes, and supporting decision-making for clinicians. This page explores how agentic AI is reshaping healthcare, the unique challenges it addresses, and practical roadmaps for leaders ready to embrace this next evolution.

What Is Agentic AI—and Why Does It Matter in Healthcare?

Agentic AI refers to systems composed of multiple collaborating AI agents that can perceive context, make decisions, and execute multi-step tasks with minimal human intervention. Unlike traditional automation or generative AI—which typically require a human to act on outputs—agentic AI can:

This leap in capability means agentic AI can move beyond isolated use cases to orchestrate end-to-end healthcare processes, delivering measurable value for patients, providers, and payers alike.

Transforming Healthcare Operations: Key Use Cases

1. Automating Patient Intake and Claims Processing

Administrative complexity is a major pain point in healthcare. Agentic AI can automate patient intake by extracting information from unstructured documents, verifying insurance eligibility, and initiating claims—all while ensuring compliance with privacy regulations. For payers and providers, AI agents can process prior authorizations, validate medical necessity, and auto-fill forms, reducing administrative costs by up to 50% and accelerating patient onboarding and claims resolution.

2. Orchestrating Clinical Workflows and Decision Support

Agentic AI is increasingly supporting clinicians by summarizing patient histories, flagging potential risks, and coordinating care across departments. For example, an AI agent can monitor EHR data, identify patients at risk of readmission, and trigger follow-up actions automatically. In clinical trials, agents can register participants, ensure post-discharge care, and generate concise summaries for progress notes and referrals, freeing up clinicians to focus on patient care.

3. Supporting Regulatory Compliance and Auditability

Healthcare is one of the most regulated industries. Agentic AI can enforce policy rules, ensure data privacy, and provide audit trails for all actions taken. Techniques such as federated learning and blockchain-based audit trails help maintain both privacy and accountability, making it easier to demonstrate compliance with regulations like HIPAA.

Overcoming Unique Healthcare Challenges

EHR Interoperability

Healthcare data is often locked in disparate EHR systems. Agentic AI must bridge these silos, requiring robust integration with standards like FHIR and HL7. Success depends on clean, well-governed, and unified data—without it, AI-driven decisions risk being incomplete or inaccurate.

Regulatory and Ethical Oversight

AI agents must be designed to operate within strict ethical, legal, and policy boundaries. This includes enforcing data privacy, access controls, and auditability at every step. Human-in-the-loop frameworks are essential: while AI can automate routine decisions, clinicians and administrators must retain oversight for high-stakes actions, ensuring accountability and trust.

Change Management and Workforce Upskilling

The shift to agentic AI requires upskilling the workforce and redesigning processes. Clinicians and staff need training to collaborate with AI, focusing on oversight, quality control, and creative problem-solving. Transparent communication about how AI agents make decisions is critical to building trust among employees and patients.

Roadmap for Healthcare Leaders: From Pilot to Enterprise-Scale Transformation

Adopting agentic AI is a journey, not a one-time project. Successful organizations follow a pragmatic, phased approach:

  1. Prioritize Data Interoperability: Invest in EHR integration and data standardization. Map out data flows and integration points across legacy and modern systems.
  2. Start with High-Value, Low-Risk Use Cases: Pilot agentic AI in administrative automation (e.g., claims or intake processes) to demonstrate ROI and minimize risk.
  3. Implement Human Oversight and Governance: Design workflows with clear escalation paths, audit trails, and compliance guardrails. Use human-in-the-loop frameworks for critical decisions.
  4. Expand to Clinical Workflows: Gradually introduce agentic AI for care coordination and decision support, with strong compliance and audit trails.
  5. Upskill the Workforce: Invest in training employees to work alongside AI agents, emphasizing oversight and continuous improvement.

Impact: Better Outcomes, Greater Efficiency

Early deployments of agentic AI in healthcare have shown dramatic results:

The Publicis Sapient Advantage

With decades of digital transformation expertise and a proven track record in AI integration, Publicis Sapient partners with healthcare organizations to design, build, and scale agentic AI solutions tailored to industry-specific needs. Our proprietary platforms accelerate system integration and workflow automation, while our human-centered approach ensures that technology augments—not replaces—human expertise.

By focusing on integration, data governance, and change management, we help clients unlock the full potential of agentic AI—turning operational pressure into a catalyst for transformation. The result: smarter operations, seamless compliance, and better patient and provider experiences.

Ready to put agentic AI to work in your healthcare organization? Let’s connect.