AI in healthcare : AI is new leadership skill

Sertis
35 minutes ago
3 min read

AI is becoming a part of healthcare, from administrative support to clinical workflows. The next challenge is ensuring that AI is used in ways that are reliable, governed, and aligned with how hospitals actually operate.

This was the main idea of the discussion "AI Is Now a Leadership Skill: How Hospital Leaders Delegate, Verify and Govern Work with Claude," presented by Mr. Tee Thuchakorn Vachiramon, Founder and CEO of Sertis, during the Hospital Management Program Class 55 at the Faculty of Medicine Ramathibodi Hospital, Mahidol University.

The session encouraged hospital executives to look beyond AI as a productivity tool and recognise it as a new leadership capability. The value of AI is not determined by how intelligent the model is, but by how leaders decide where to use it, how they delegate work, how they verify its outputs, and how they establish governance for responsible adoption.

A Four-Step Framework for AI Adoption

To help organisations adopt AI systematically, Mr. Thuchakorn introduced four key principles:

Understand: Understand AI's capabilities and limitations, identify which tasks are
suitable for AI, and recognise where human judgment remains essential.
Delegate: Assign work to AI with clear objectives, sufficient context, and the information needed to complete the task.
Verify: Review AI-generated outputs, sources, and reasoning before relying on the results.
Govern: Establish clear policies, ownership, and suitable use cases to ensure AI is deployed responsibly.

While these four steps provide a structured approach to AI adoption, leaders must also recognise that AI is not infallible.

Failure Models: Understanding AI's Limitations

Using AI effectively is not about trusting every response, it is about understanding where AI can fail and applying the appropriate level of human oversight.

Three key risks highlighted during the session include:

AI Hallucination: AI may generate convincing but inaccurate information or fabricate references that appear credible.
Sycophancy: AI may reinforce leading assumptions instead of providing objective, evidence-based responses.
Data Leakage: Improper use of confidential organisational or patient data may create privacy and security risks.

Recognising these limitations allows organisations to deploy AI where it creates the most value while reducing operational risk.

Prompt Like a Leader

Another key takeaway was that leaders do not need to write the perfect prompt. Instead, they need to manage AI the way they would manage a member of their team: assigning work with clear objectives and context, reviewing the results, and taking responsibility for the final decision.

This leadership approach can be summarised in three principles:

Delegation: Provide clear instructions, objectives, and relevant information.
Verification: Validate AI-generated outputs before taking action.
Accountability: While AI can support analysis and decision-making, accountability always remains with people.

The AI Governance Five Checks

Regardless of how capable AI becomes, verification remains essential. Before using AI-generated outputs in clinical or operational decision-making, organisations should verify five key areas:

Source: Can the information be traced back to a reliable source?
Number: Are figures, units, and calculations accurate?
Logic: Do the conclusions align with the available evidence?
Boundary: Is AI operating within its intended scope and level of authority?
Owner: Who is responsible for reviewing, approving, and acting on the output?

Together, these five checks serve as a practical governance framework, ensuring that AI is used to enhance speed and efficiency without compromising human oversight, accountability, or trust.

Leadership Will Define AI Success

AI has potential to improve healthcare, but technology alone is not enough. Unlocking its full value requires leaders who understand where AI should be applied, how to build the right processes around it, and how to establish governance that enables safe, reliable, and responsible adoption.

As AI becomes part of everyday healthcare, leadership is no longer just about managing people; it is also about leading how people and AI work together.

At Sertis, we help organisations turn AI ambition into real business impact, from identifying high-value use cases and developing AI solutions to establishing governance frameworks that enable AI to be deployed responsibly and at scale.