Generative AI in Healthcare: How Agentic Tools Are Cutting Clinical Burden Without Replacing Doctors

At Children’s Hospital of Orange County (CHOC Children’s), agentic and generative AI tools are already transforming how clinicians interact with patient data. Chart reviews that once took an hour or more now take minutes — and the lessons from their deployment apply far beyond healthcare.

Dr. Steven Martel, VP and Chief Health Information Officer at CHOC Children’s, believes the technology represents a rare opportunity to reverse decades of clinician burnout caused by overburdened electronic health records. But he’s equally clear-eyed about the risks: AI should augment clinical judgment, not replace it.

“Leaders who believe that the tools simply need to be ‘turned on’ and success will occur will be disappointed,” Dr. Martel said. Successful deployment requires understanding the AI model’s training data, iterating through trial and error, and building organizational tolerance for measured risk balanced with appropriate governance.

Key Takeaways:

• Agentic AI at CHOC Children’s cuts complex chart reviews from 60+ minutes to just minutes
• Autonomous clinical decision-making should be avoided — the human-in-the-loop framework is non-negotiable
• Leaders must assess whether an AI tool’s training data actually fits their organization’s specific population
• Treat data as an asset and build a flexible data platform before expecting AI tools to deliver consistent value

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