Podcast Summary: Tomorrow's Cure – "When Algorithms Meet Empathy: The Future of Patient-Centered AI"

Host: Kathy Werzer, Mayo Clinic
Guests: Dr. Anjali Bagra (Mayo Clinic, Professor of Medicine and Director of Enterprise Automation), Dr. Ravi Bapna (Curtis Carlson Chair in Business Analytics and Information Systems, University of Minnesota)
Date: February 18, 2026

Overview of the Episode

This episode of Tomorrow's Cure explores the rapidly evolving landscape of artificial intelligence (AI) and automation in healthcare, focusing on how these technologies can coexist with the essential human element in medicine. The conversation delves into practical examples, organizational challenges, responsibilities, and the future vision for truly patient-centered, ethical, and empathetic AI adoption. The hosts and guests discuss how to maximize the benefits of AI while ensuring trust, safety, equity, and human flourishing are not compromised.

Key Discussion Points & Insights

1. Societal Preparedness for Rapid AI Advancement

[02:06–03:34]

• Dr. Bapna: AI is a powerful, intangible general purpose technology, fundamentally different from previous innovations (like electricity or basic computing); it's misunderstood because it's not visible, and the pace of technological change is outstripping organizational ability to adapt.
• Quote:

  "These algorithms are lurking in the background... People don’t understand them necessarily, right. They can’t see them, they don’t have a relationship with them. And therefore it’s pretty much, I would say, misunderstood." – Dr. Ravi Bapna [02:25]

2. Readiness of Healthcare for AI & Automation

[03:34–07:01]

• Dr. Bagra: Healthcare is at a breaking point with rising costs and failed traditional fixes. Automation isn't about replacing people, but adding new tools for scalable solutions. Integration is already happening, especially in diagnostics (e.g., image analysis), but seamless processes and 'human in the loop' systems are essential.
• Quote:

  "These are not replacing people, but they are adding to our toolbox... to allow creating scalable solutions for problems that have been age old." – Dr. Anjali Bagra [04:09]

3. Amplifying (Not Displacing) Human Expertise

[07:01–11:14]

• Clinical Example: AI-powered ambient note-taking allows physicians to focus fully on patients during visits, rather than on documentation.
• Augmentation: Generative AI reduces analytics costs and helps leverage vast but underutilized healthcare data, supporting both clinical and research work.
• Quote:

  "Now I don’t do that anymore. I get my note generated automatically... I give my full attention to my patients when I’m in the room with them without being distracted." – Dr. Anjali Bagra [07:38]

4. High Failure Rates of AI Pilots: Challenges in Healthcare

[11:14–14:02]

• Core Issues: Pilots fail when technology, people, and processes aren’t aligned. It's not a top-down "plug-and-play" but requires ground-up problem-solving, workflow deconstruction, upskilling, and buy-in.
• Quote:

  "What we need to align is people and processes. We really need this triple aim to come together. It’s technology, people and process." – Dr. Anjali Bagra [11:32]

5. Building Trust & Transparency in AI Implementation

[14:02–18:46]

• Shared Responsibility: Trust and transparency are core cultural values in healthcare—everyone shares responsibility, and open discussion of both technology’s benefits and its potential pitfalls is necessary.
• Top Down & Bottom Up: Innovation has to happen at every level, with leadership demystifying AI potential, and all staff and patients involved in transparent, inclusive processes.
• Quote:

  "Trust and transparency is core. Now in terms of who is responsible... this is everybody’s responsibility." – Dr. Anjali Bagra [14:29] "I got a report from my, my visit. It actually had links to break down complex medical terms that I could understand, right. As a patient." – Dr. Ravi Bapna [17:43]

6. Avoiding Dehumanization & The AI Paradox

[20:37–23:58]

• Burnout & Human Connection: Automating transactional, administrative work allows clinicians to focus on relational, human-centered care.
• AI as a Humanizer: Rather than dehumanizing, AI—if correctly implemented—re-humanizes care by restoring focus on empathy and human presence.
• Quote:

  "I would actually argue and introduce this concept of AI and automation paradox. I think these tools allow us to rehumanize healthcare." – Dr. Anjali Bagra [21:52] "When not done right... that’s a risk. But when done right... these tools really allow us to be more human." – Dr. Anjali Bagra [23:55]

7. The ‘Four A’s’ Framework for Human-Centered AI

[23:58–27:13]

• Awareness (knowing what’s possible)
• Automation (streamlining tasks)
• Augmentation (enhancing human capability)
• Accountability/Agentic AI (responsibility, explainability, and agency)
• Agentic AI: Next-gen autonomous agents that leverage both human knowledge and traditional IT tools.
• Quote:

  "So those four A’s, I think become really powerful to thinking about human centric AI." – Dr. Ravi Bapna [27:07]

8. Cognitive Burden & Physician Burnout

[27:13–30:09]

• Dr. Bagra: While there’s a learning curve with AI, effective tools (like Open Evidence) actually decrease cognitive overload by summarizing research and supporting better-informed decisions. The clinician always retains final authority.
• Quote:

  "Now I can use tools that can give me the five most important studies to know. And based on my patient presentation, here is a suggestion..." – Dr. Anjali Bagra [28:37] "So yes, to your point, there is a training curve... but essentially, at the end of the day, I’m the one making the best decision for my patient." – Dr. Anjali Bagra [29:30]

9. Accountability for Adverse Outcomes from AI

[30:09–32:42]

• Primary Responsibility: The care team is ultimately responsible. AI must be appropriately governed, and blind trust in technology is dangerous.
• Education: Healthcare and business students must learn to properly use and evaluate AI as part of their training.
• Quote:

  "At the end of the day, the buck stops with the care team taking care of the patients." – Dr. Anjali Bagra [30:31] "...maybe the lawsuits will come for those doctors for not using the technology actually." – Dr. Ravi Bapna [32:20]

10. Equity: Rural & Underserved Communities

[32:42–36:17]

• Both Opportunity & Risk: AI and digital care can reach underserved populations but require political, regulatory, and organizational alignment to avoid worsening disparities.
• Quote:

  "Now is the time where we have an opportunity to make a real difference. It may not be human workforce, but we can bring care to patients in the comfort of their homes." – Dr. Anjali Bagra [35:11]

11. Safety, Guardrails & Ethics

[37:35–42:45]

• Problem-Driven & Context-Specific: Start with real problems, then design guardrails—like demographic representation in algorithms and tools for bias detection/correction (e.g., synthetic data).
• Human & Machine Partnership: Joint oversight boosts safety—AI can flag risks (e.g., early sepsis detection) that humans may miss when overloaded.
• Quote:

  "With human and machine oversight together, we have way more capability." – Dr. Anjali Bagra [41:45]

12. Preparing Patients for the Automated Future

[42:45–46:49]

• Digital Health Literacy: Patient journeys now begin online (Google, ChatGPT). Patients should raise their own awareness, use digital resources, and actively participate in their care—a more empowered, less hierarchical model.
• Quote:

  "Today my patients... are on their portal all the time. My patients get access to their tests before I can see their tests." – Dr. Anjali Bagra [44:40] "And that gives you agency, right?" – Dr. Ravi Bapna [45:55]

13. Addressing Patient Fears

[46:49–48:32]

• Meet Patients Where They Are: Fear is natural but often addressed through clear information, transparency, and discussion of real trade-offs; technology will always remain a tool, not a replacement for hope and healing.

14. Thriving Amidst Rapid Change

[48:32–51:06]

• Personal & Collective Growth: Both guests emphasize lifelong learning, embracing change, partnership, and excitement for the future as the path to professional and personal thriving in healthcare.
• Quote:

  "And just being able to learn from each other, doing this together to challenge the status quo and knowing that we have real capability to make experience just exponentially better for human beings." – Dr. Anjali Bagra [50:32]

Notable Quotes & Timestamps

• "These algorithms are lurking in the background... People don’t understand them necessarily." – Dr. Ravi Bapna [02:25]
• "These are not replacing people, but they are adding to our toolbox..." – Dr. Anjali Bagra [04:09]
• "I get my note generated automatically... I give my full attention to my patients." – Dr. Anjali Bagra [07:38]
• "Trust and transparency is core... this is everybody’s responsibility." – Dr. Anjali Bagra [14:29]
• "AI and Automation Paradox... these tools allow us to rehumanize healthcare." – Dr. Anjali Bagra [21:52]
• "So those four A’s... become really powerful to thinking about human centric AI." – Dr. Ravi Bapna [27:07]
• "At the end of the day, the buck stops with the care team taking care of the patients." – Dr. Anjali Bagra [30:31]
• "We are in this together... knowing that we have real capability to make experience just exponentially better for human beings." – Dr. Anjali Bagra [50:32]

Timestamps of Key Segments

• [02:06] – Societal readiness for AI’s pace
• [03:41] – Healthcare system’s preparedness for automation & AI
• [07:23] – How AI augments (not replaces) doctors and researchers
• [11:32] – Why most AI pilots fail in healthcare
• [14:29] – Who’s responsible for trust and transparency?
• [20:58] – Risks of dehumanization in medicine
• [23:58] – Introduction to the Four A’s Framework
• [27:48] – Cognitive burden and decision-making with AI
• [30:09] – Responsibility and accountability for AI-driven harm
• [33:08] – Impact on rural and underserved care
• [37:35] – Guardrails, safety, and ethical requirements for AI
• [42:45] – Advice for patients preparing for AI-driven medicine
• [46:49] – Addressing patient fears about automation
• [48:32] – Personal strategies to thrive in the new era of healthcare

Tone & Language

The episode features a thoughtful, collaborative tone with optimism, candor, and emphasis on both opportunity and caution. Guests use clear, relatable examples—balancing high-level frameworks with practical anecdotes—aimed at empowering both healthcare professionals and patients to participate in a human-centered, data-driven healthcare future.

Conclusion

This episode paints a nuanced, forward-thinking vision of AI in healthcare. While embracing robust, scalable digital tools to augment human care, the ultimate message underscores trust, transparency, shared responsibility, and the irreplaceable value of empathy and human connection. Listeners are invited to anticipate and contribute to a future where technology and humanity not only coexist but enhance each other to achieve better outcomes for all.