How Large Incumbents Like Epic and Bridgewater Are Reshaping Healthcare & Finance
© 2025 Freddie Seba. All rights reserved.
The adoption of agentic GenAI is moving from theoretical discussions to widespread, real-world deployment. It has the potential to fundamentally transform healthcare, finance, and education. This presents significant ethical, governance, and regulatory issues for leaders.
Recent announcements from Epic Systems—controlling 37% of the inpatient EHR market and impacting over 250 million patients—and Bridgewater Associates, managing $124 billion in assets, illustrate how billion-dollar industry leaders integrate GenAI into high-stakes workflows. Epic, the largest EHR vendor in the U.S., announced deep GenAI integration in its healthcare software, automating clinical workflows and patient engagement (Boyd, 2023). Meanwhile, Bridgewater launched a $2 billion AI-driven investment fund, relying on machine learning for most investment decisions (GuruFocus, 2025).
These moves highlight a central question: How much autonomy should GenAI systems have in industries where compliance, trust, and human oversight are critical? Below, we explore how GenAI agents are being deployed in regulated fields, the governance dilemmas they pose, and why a structured GenAI ethics leadership framework is increasingly indispensable.
Seba’s GenAI Ethics for Leaders Framework- Previous Newsletters
This discussion extends our collective work in shaping the @2025 Seba’s GenAI Ethics for Leaders Framework—a resource for executives, policymakers, and industry professionals to structure GenAI governance.
Collectively, these editions keep our framework relevant, pragmatic, and responsive to the rapid evolution of GenAI.
Healthcare: Epic’s GenAI Expansion & The Future of Patient Interaction
Epic’s GenAI-powered EHR is rolling out rapidly across U.S. health systems, marking a pivotal shift in clinical decision-making (Boyd, 2023). Key developments:
Where should GenAI autonomy stop in healthcare? While GenAI boosts workflow efficiency, patient safety requires a human-in-the-loop to validate AI decisions and ensure they align with ethical and clinical standards (Wong et al., 2021).
Finance: Bridgewater’s AI-Powered Investment Fund
Bridgewater Associates, the world’s largest hedge fund at $124 billion in assets, launched a $2 billion AI-driven hedge fund, entrusting machine learning with most investment calls (GuruFocus, 2025). CEO Nir Bar Dea noted:
“We have been shifting the type of humans we bring into Bridgewater for 50 years. That means from looking for analytical skills and financial backgrounds to conceptual people who can ask philosophical questions.” Full story in Fortune.
Key Concerns:
- Explainability & Transparency:
- AI-based financial recommendations must be explainable to regulators and clients (Schroeder, 2024).
- Bias Mitigation:
- Ongoing testing of AI models is vital to avert systemic bias in risk assessments and investment strategies (Grobys et al., 2022).
- Regulatory Compliance:
- Agencies like the SEC, CFPB, and global financial regulators now closely monitor AI-powered funds for emergent risks (U.S. Senate, 2024).
Conclusion: The Future of GenAI Agents Demands Human-centered Leadership
As GenAI agents become more autonomous, leaders must keep humans central to AI-driven decisions. While GenAI speeds up routine tasks, high-stakes calls—especially in healthcare, education, and finance—demand human expertise.
A Human-in-the-Loop approach is not just an ethical measure but a leadership imperative. Those who embed ethical GenAI governance will reduce risks, maintain stakeholder trust, and comply with evolving regulations—while those who ignore these frameworks risk reputational and operational harm.
Mentions & Gratitude
University of San Francisco | USF School of Nursing and Health Professions | AMIA (American Medical Informatics Association) | AAC&U (American Association of Colleges and Universities) | Coalition for Health AI (CHAI)
#GenAIEthics #DigitalHealthInformatics #AIAccountability #Traceability #ResponsibleAI #EthicalTech #HumanCenteredAI #Leadership #TechnologyEthics #GenAI #AIethics #DigitalTransformation #FutureOfWork
About the Author
Freddie Seba is a recognized thought leader in Generative AI ethics, holding an MBA (Yale) and MA (Stanford) and pursuing a Doctorate in Education (USF) on GenAI Ethics. Since 2017, he has been a faculty member in USF’s Master of Science in Digital Health Informatics program, pioneering one of the first Generative AI Ethics courses in healthcare and education. A Silicon Valley entrepreneur, Freddie has co-founded financial services, healthcare, and education startups and held senior roles at BBVA, Epson, and Ingram Micro. As a speaker, writer, and faculty, he advocates for human-centered AI adoption and guides leaders through GenAI’s complexities with integrity and purpose. More at: www.freddieseba.com.
© 2025 Freddie Seba. All rights reserved.
References & Useful Links
- Advisory Board. (2025, March 14). Epic unveils new AI-enabled capabilities to improve EHR. [Advisory Board Daily Briefing]. Link
- Boyd, E. (2023, April 17). Microsoft and Epic expand strategic collaboration by integrating Azure OpenAI Service. Microsoft News Center. Link
- Fortune. (2024, July 1). Bridgewater’s $2 billion AI-driven fund invests via machine learning. Link
- Grobys, K., Kolari, J. W., & Niang, J. (2022). Man versus machine: On artificial intelligence and hedge fund performance. Applied Economics, 54(40), 4632–4646. Link
- GuruFocus. (2025, March 5). Bridgewater’s AI-driven fund matches human-led strategies. GuruFocus News. Link
- Schroeder, M. (2024, June 26). The role of human oversight in AI-driven financial services. Forbes Finance Council. Link
- Tai-Seale, M., Baxter, S. L., Vaida, F., Li, J., & Jones, C. (2024). AI-generated draft replies are integrated into health records and physicians’ electronic communication. JAMA Network Open, 7(4), e246565. Link
- U.S. Senate Committee on Homeland Security & Governmental Affairs. (2024). Hedge funds’ use of AI/ML technologies: Findings and recommendations. [Majority Staff Report]. Link
- Wong, A., Otles, E., Donnelly, J. P., Krumm, A., Snyder, A., & Judge, J. (2021). External validation of a widely implemented proprietary sepsis prediction model in hospitalized patients. JAMA Internal Medicine, 181(8), 1065–1070.
Transparency Statement
This newsletter integrates my research, professional insights, and experience in GenAI ethics. GenAI tools—including ChatGPT, Gemini, Grammarly, and ZoomAI—are used for trend analysis and content clarity. Some content was initially published on LinkedIn, Substack, and my website for enhanced accessibility.