Agentic AI in Healthcare: Transforming Medical Workflows with Autonomous Systems
Agentic AI enables healthcare systems to automate complex tasks and workflows, though its success hinges on proper oversight and strategic implementation.
Agentic artificial intelligence (AI) is poised to revolutionize healthcare by autonomously handling complex tasks, from clinical decision-making to administrative workflows. Unlike traditional AI, agentic systems can reason, solve multistep problems, and execute follow-up actions with minimal human intervention.
The Rise of Agentic AI
While less than 1% of enterprise software included agentic AI in 2024, Gartner predicts usage will surge to 33% by 2028. Market.us estimates the global market could reach $200 billion by 2034.
"Agentic AI will change the way we work in ways that parallel how different work became with the arrival of the internet," says Amanda Saunders, NVIDIA's director of generative AI software marketing.
How Agentic AI Differs from Generative AI
While generative AI produces content based on prompts, agentic AI:
- Acts proactively across multiple data sources
- Makes decisions about next steps
- Automates entire workflows
For example, after surgery:
- Generative AI drafts post-op instructions
- Agentic AI delivers them via patient portals
- Monitors compliance and schedules follow-ups
Healthcare Applications
Key use cases include:
- Drug Discovery: Screening billions of compounds
- Clinical Trials: Identifying eligible patients
- Insurance Appeals: Automating denial challenges
- Virtual Assistants: Providing real-time patient monitoring
"Agentic AI builds on generative AI, taking simple responses further with the ability to consider options, go back and redo steps," Saunders notes.
Implementation Challenges
With 40% of hospital costs being administrative (per AHA), the potential is enormous. However, experts warn:
- Requires rigorous data governance
- Must prevent access to confidential information
- Still considered narrow AI (not human-level intelligence)
Major platforms integrating agentic AI include:
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About the Author
Dr. Lisa Kim
AI Ethics Researcher
Leading expert in AI ethics and responsible AI development with 13 years of research experience. Former member of Microsoft AI Ethics Committee, now provides consulting for multiple international AI governance organizations. Regularly contributes AI ethics articles to top-tier journals like Nature and Science.