How Healthcare Leaders Are Using AI to Transform Operations, Billing, and Patient Experience with Ben Seals

Episode Summary:

In this episode of AI Decisions You Have to Defend, hosted by Nicola Onassis, we sit down with Ben Seals, Chief Executive Officer at Thomas Eye Group, to explore how healthcare organizations are implementing AI and automation across billing, clinical documentation, patient communication, and staff training. Drawing on his experience leading healthcare operations, Ben shares real-world examples of projects that delivered significant improvements and others that did not meet expectations. He explains how organizations can identify the right opportunities for automation, measure results, and understand where human involvement remains essential.

Ben discusses how AI-powered automation transformed his organization's back-office billing operations by reducing repetitive tasks and improving efficiency. By starting with clearly defined workflows, such as prior authorizations and claims processing, his organization increased its capacity from supporting 7 providers to more than 30. The team now processes nearly 3,500 claims per day, with automation handling approximately 80% to 85% of the work. He explains why the best starting point for AI is often a routine process with a limited number of decision points, while more complex situations should remain under human review.

The conversation also explores the challenges of using AI for clinical documentation and voice-based patient communication. Ben explains why AI transcription alone is not enough when physicians need accurate, structured documentation tailored to their individual preferences. He also shares how patient trust and comfort influence the adoption of voice AI, particularly when patients prefer speaking with a live representative. Beyond technology, Ben highlights how AI is changing workforce responsibilities, shifting employees from completing repetitive tasks to managing workflows, identifying defects, and evaluating automated outputs. His central message for business leaders is that AI cannot fix a broken process. Successful implementation requires process engineering, employee training, human oversight, and a clear understanding of where AI can genuinely create value.

Key Takeaways:

• Start with well-defined processes: Identify repetitive tasks with clear workflows and predictable outcomes before introducing AI and automation.
• Automate the right decisions: Processes requiring approximately 3 to 7 decision points can be good starting points, while more complex decisions should be reviewed by people.
• Measure operational improvements: AI automation helped the organization scale from 7 to more than 30 providers while processing nearly 3,500 claims daily.
• Recognize the limitations of AI documentation: Transcription capabilities have improved, but generating accurate, structured clinical documentation that meets individual physician preferences remains challenging.
• Keep patients at the center: Voice AI can improve access and support multilingual communication, but patients should still have the option to speak with a live representative.
• Prepare employees for changing roles: As automation takes over repetitive tasks, employees need to develop skills in workflow management, quality control, and identifying process defects.
• Build human oversight into AI systems: Employees need the expertise and curiosity to recognize inaccurate outputs, question results, and improve automated processes.
• Fix processes before adding AI: Technology layered onto inefficient workflows can make operations more expensive rather than more effective.
• Invest in employee adoption: Successful AI implementation requires training, building confidence, and helping employees understand how to use the technology effectively.

Connect with Ben Seals:

• LinkedIn: linkedin.com/in/benseals
• Company: Thomas Eye Group

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"AI Decisions You Have to Defend explores the real decisions behind artificial intelligence, what works, what doesn't, and what leaders learn when putting AI into practice in the real world."