Rehumanizing global health care with agentic AI

2026-06-02 · Source: Artificial intelligence – MIT Technology Review · Field: Health & Wellbeing — Healthcare Systems & Policy, Medical Devices & Health Technology, Artificial Intelligence & Machine Learning · Depth: Intermediate, medium

Summary

Agentic AI is rapidly being adopted in global healthcare to address increasing strain, chronic underinvestment, and a projected 11 million worker shortfall by 2030. KPMG reports 68% of providers have integrated AI agents to automate back-office processes, collaborate with medical teams, and triage patients, reducing clinician cognitive load. Unlike prior digital solutions, agentic AI handles nuanced scenarios, makes autonomous decisions, and retrieves expert information. Hospital for Special Surgery (HSS) processes 1,100 insurance claims monthly, reducing appeal times from 45 to 5 minutes and boosting success rates from 65% to 100%. HSS also deploys a 24/7 patient-facing AI scheduling and triage service with Ema Unlimited, booking appointments based on patient condition, location, and insurance. Safeguards include human escalation for complex cases, auditable decisions, and secure data. This technology is viewed as a general-purpose solution requiring a unified data strategy and interoperability for system-level change.

Key takeaway

For healthcare administrators facing workforce shortages and operational inefficiencies, agentic AI presents a transformative solution. Your organization can significantly reduce administrative burdens and enhance patient access by deploying AI agents for tasks like insurance claims and 24/7 scheduling. To maximize value and ensure safety, prioritize establishing a unified data strategy, fostering interoperability, and implementing strong governance with human-in-the-loop safeguards for all AI agent deployments. This approach will free clinicians for high-value patient care.

Key insights

Agentic AI rehumanizes healthcare by automating non-clinical tasks, freeing clinicians for complex, specialized patient care.

Principles

• Agentic AI excels at nuanced, complex scenarios and autonomous decision-making.
• Treat agentic AI as a general-purpose technology, integrating it enterprise-wide.
• A unified data strategy and interoperability are critical for agentic AI value.

Method

Deploy AI agents for backend processes and patient-facing services, ensuring human oversight and data security.

In practice

• Automate insurance claims to reduce processing time and boost appeal success.
• Implement 24/7 conversational AI for patient scheduling and triage.
• Create an AI lab and subcommittee to democratize access and ensure rigorous scrutiny.

Topics

• Agentic AI
• Healthcare Technology
• Digital Transformation
• Patient Triage
• Workflow Automation
• Data Interoperability
• AI Governance

Best for: Executive, AI Product Manager, Product Manager, Director of AI/ML, AI Architect, Consultant

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Editorial summary, takeaway, and curation by AIssential. Original article published by Artificial intelligence – MIT Technology Review.