As a Chartered Coaching Psychologist and Leadership Coach, I spend my days coaching medical and public health leaders and coaching global health leaders who operate in environments of extreme, unrelenting complexity. Lately, a pressing question in our coaching sessions is no longer if artificial intelligence will disrupt our systems, but how health leaders can successfully adapt. The rapid integration of AI is not just a technological upgrade; it is becoming a profound psychological and cultural shift.
To help you horizon-scan and protect your wellbeing, your teams, and your strategic partnerships, I have brought together the latest research on AI in healthcare for senior health leaders and health executives. Here is a summary of what you need to know to lead skilfully in the age of AI as a medical or public health director or public health specialist leader, or as a global health leader, along with links to two blogs I wrote on this subject a few years ago.
Summary of Key Insights for Global Health Leaders
- The Shift to “Multidimensional” and Transformational Leadership: Integrating AI into complex healthcare systems requires medical leaders and health leaders to move beyond traditional management into “multidimensional leadership” spanning technological, strategic, operational, and organisational domains. As a coach, I see this as a call for even more transformational leadership, motivating teams, fostering psychological safety, and managing the stress of change. To champion this, healthcare organisations are increasingly appointing Chief AI Officers (CAIOs) to bridge the gap between data scientists and medical professionals, ensuring ethical use and aligned enterprise strategy. Success depends on leaders prioritising “interpersonal capacity” to navigate the human aspects of this transformation.
- Re-Humanising Care and Reducing Cognitive Overload: One of the greatest threats to health executive and clinical wellbeing is burnout. Interestingly, AI is proving to be a powerful tool for re-humanising medicine by taking over mundane administrative tasks that consume up to 10% of a medical professional’s workweek. By alleviating this cognitive and administrative burden, AI has been shown to help avert healthcare worker burnout and return precious time to clinicians. This allows professionals to redirect their mental energy toward what machines cannot do: building meaningful human relationships, engaging in complex clinical reasoning, and coaching and mentoring junior staff.
- The Psychological Trap of “Automation Bias” and Deskilling: With the rise of Large Multi-Modal Models (LMMs), the World Health Organisation has highlighted a critical human risk: “automation bias.” This occurs when professionals or patients improperly delegate difficult choices to a machine or blindly trust AI outputs, overlooking errors. Furthermore, there is a recognised risk of clinical “deskilling” if experts come to over-rely on AI systems. From a psychological perspective, combating these cognitive biases requires a culture of critical thinking, where professionals are trained to question the machine, understand AI failure modes, and maintain their own clinical judgment.
- AI as a Strategic Co-Pilot & The “Wisdom of Crowds”: Generative AI is increasingly being used by senior health leaders for high-stakes strategic decision-making, acting as a researcher, simulator, and thought partner. However, a single AI model can produce inconsistent or biased evaluations. Just as I coach health leaders to develop greater cognitive diversity to avoid groupthink, research shows that aggregating insights from multiple, diverse AI models can offset inherent biases. This “wisdom of crowds” approach seems to yield predictions comparable to expert human judgment, providing leaders with a highly agile tool for planning ahead.
My previous blog posts on AI for Medical and Public Health Leaders
You might also like to read a couple of blogs I have written on the subject of AI.
‘The Robot Will See You Now’ – Are You Futureproofing Your Medical Career?
Here is a link to my blog from 2020, asking whether you are future-proofing your health career.
Anything you can do, AI can(‘t) do better!
Here is a link to my blog in 2024, reflecting on the opportunities and challenges of technology.
Conclusion: A Coach’s Perspective on the Road Ahead
Leading through the AI revolution is an adaptive and psychological challenge. As senior health leaders, you do not need to become software engineers, but you do need to cultivate the adaptive capacity to respond to uncertainty. Your role is to serve as the “Driver” or “Shaper” of AI adoption, championing a culture of continuous learning, transparency, and inclusivity to ensure these tools do not perpetuate existing health inequalities.
When teams face technological disruption, anxiety and resistance are natural human responses. To lead your organisations and multi-lateral partnerships effectively, you must focus heavily on change management and psychological safety. This means actively involving diverse stakeholders, from frontline nurses to administrative staff, in the co-creation and auditing of AI tools so that your staff feel empowered rather than replaced.
As you horizon-scan for your own career, remember that AI will not replace the need for strategic courage or human empathy. Let the algorithms absorb the noise and complexity of the data. Use the cognitive space that AI frees up to refocus your efforts on the uniquely human elements of leadership: coaching your teams, building multilateral trust, and advocating for equitable, patient-centred global health.
Additional Resources / Further Reading
For deeper understanding and actionable frameworks, I recommend these resources:
- Leadership for AI Transformation in Health Care Organization: Scoping Review (JMIR, 2024) An excellent breakdown of the “multidimensional leadership” framework, exploring the technical, adaptive, and interpersonal capacities required for modern leaders.
- Leveraging AI for Strategic Decision-Making in Healthcare Operations (AJHCS, 2026) A practical guide for executives on how to safely use Generative AI for scenario planning and how to apply the “wisdom of crowds” to reduce algorithmic bias.
- WHO Releases AI Ethics and Governance Guidance for Large Multi-Modal Models (2024) Essential reading on the systemic risks of AI, including cognitive automation bias, and the 40+ recommendations for safe, equitable AI deployment.
- Developing Healthcare Workers’ Confidence in AI (NHS AI Lab) A comprehensive report detailing AI workforce archetypes (Shapers, Drivers, Creators, Embedders, and Users) and how to structurally support their continuous education and transition.
- Future of Medical Leadership in the Age of Artificial Intelligence (BMJ Leader, 2025) – A concise overview of how AI integration relies on balancing rapid technological advances with a human-oriented approach and ethical prioritisation.
Partner with the world’s only Registered, Chartered Coaching Psychologist with a Medical & Public Health leadership background. Dr Fiona Day has helped over 500 medical and public health leaders worldwide lead with confidence, navigate career crossroads, and overcome burnout. Fiona’s evidence-based coaching is empirically proven to increase validated wellbeing outcomes by an average of +17.4%. Book a confidential Consultation today!
