How healthcare leaders can evaluate AI opportunities, manage risk, ask smarter questions, and prepare their organizations for what's next. Artificial intelligence is rapidly becoming part of nearly every conversation in healthcare, but many executives are still asking the same question: What do I actually need to understand to make good business decisions? On this episode of The Dish on Health IT, Brian Dwyer, Business Strategist at Point-of-Care Partners, is joined by Sam Schifman, Principal Engineer for AI at Red Hat and Consultant at Point-of-Care Partners, and Kendra Obrist, Senior Consultant and Payer Interoperability Subject Matter Expert at Point-of-Care Partners, for a practical discussion about how healthcare leaders can evaluate AI opportunities without needing to become technical experts. Together, they explore where AI is delivering measurable value today, why many initiatives struggle to achieve expected outcomes, how to evaluate vendors and risk, what emerging policy and governance trends mean for healthcare organizations, and why strong data quality and interoperability remain essential to AI success.
Artificial intelligence is rapidly becoming part of nearly every conversation in healthcare, but many executives are still asking the same question: What do I actually need to understand to make good business decisions? On this episode of The Dish on Health IT, Brian Dwyer, Business Strategist at Point-of-Care Partners, is joined by Sam Schifman, Principal Engineer for AI at Red Hat and Consultant at Point-of-Care Partners, and Kendra Obrist, Senior Consultant and Payer Interoperability Subject Matter Expert at Point-of-Care Partners, for a practical discussion about how healthcare leaders can evaluate AI opportunities without needing to become technical experts. Together, they explore where AI is delivering measurable value today, why many initiatives struggle to achieve expected outcomes, how to evaluate vendors and risk, what emerging policy and governance trends mean for healthcare organizations, and why strong data quality and interoperability remain essential to AI success.
The conversation begins by unpacking what people actually mean when they say they're "using AI." Sam explains the differences between predictive AI, generative AI, conversational AI, and the rapidly emerging world of agentic AI, while Kendra encourages listeners not to get caught up in the terminology. Instead, she emphasizes starting with the business problem that needs to be solved and then determining whether AI is the right tool for the job.
Brian then asks where AI is creating meaningful value today. Kendra highlights opportunities across administrative workflows, including documentation, member and provider engagement, claims, prior authorization, and other operational processes where reducing friction can improve efficiency and the user experience. Sam builds on that discussion by encouraging organizations to evaluate AI initiatives based on business outcomes and measurable success metrics rather than technical benchmarks, while recognizing that every AI implementation introduces its own set of risks and tradeoffs.
The discussion shifts to why technically impressive AI projects often fail to produce meaningful business results. Kendra explains that organizations can become captivated by polished demonstrations without fully considering governance, data quality, workflow redesign, adoption, and organizational change management. Sam reinforces the importance of understanding AI's inherent uncertainty, establishing appropriate human oversight, and preparing employees for new ways of working as AI becomes integrated into everyday operations.
Brian next explores how much AI healthcare executives actually need to understand. Rather than suggesting leaders become AI specialists, Sam encourages executives to develop enough knowledge to ask informed questions and avoid treating AI as an incomprehensible "black box." Kendra complements that advice by encouraging leaders to personally experiment with AI tools so they can better understand both their strengths and limitations before making strategic decisions.
As organizations increasingly evaluate AI-enabled products, the panel discusses the questions healthcare leaders should ask prospective vendors. Beyond understanding how an AI solution works, they explore governance, transparency, auditability, accountability, data requirements, quality assurance, and vendor responsibility when AI produces unexpected results. Sam also introduces the concept of AI sovereignty, encouraging organizations to think carefully about long-term dependence on foundational AI models and the flexibility they'll need as technology and regulations continue to evolve.
The conversation also examines the rapidly changing policy landscape surrounding AI. Kendra explains how federal agencies are currently taking a sector-specific approach to oversight while states continue introducing their own transparency, bias, and human review requirements. Together, they discuss the operational challenges this evolving patchwork of regulations creates for healthcare organizations operating across multiple states and why adaptability will become increasingly important.
Looking ahead, Brian asks what developments deserve executives' attention and which trends may be receiving more attention than they warrant. Sam discusses why organizations should avoid assuming generative AI is always the right answer, highlighting continued opportunities for predictive AI, machine learning, and even traditional software approaches when they better fit the problem. Kendra shares why agentic AI and coordinated teams of AI agents may fundamentally reshape how work is performed across healthcare organizations.
The episode concludes with each guest sharing one final takeaway for healthcare leaders. Sam encourages organizations to begin thinking strategically about AI sovereignty, security, and organizational flexibility as AI becomes increasingly embedded in core business operations. Kendra leaves listeners with a broader perspective, comparing AI's impact on knowledge work to the Industrial Revolution's impact on physical labor, and encourages leaders to embrace the technology thoughtfully rather than waiting until they feel they have all the answers.
This episode offers practical guidance for healthcare executives who want to make informed AI decisions, ask better questions of vendors and internal teams, and develop an AI strategy grounded in business value rather than technology for technology's sake.
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