Improving Clinicians' Digital and Artificial Intelligence-related Competence Within Healthcare Organizations in the United States: A Strategic Framework Proposal

Abstract

Objective

In recent years, there has been an emerging wave of artificial intelligence (AI) and digital tools in healthcare, thereby revolutionizing clinical practice. As health systems are increasingly utilizing these tools as a means to improve clinical and operational performance outcomes, it becomes imperative to train and professionally develop key frontline stakeholders, such as clinicians, in digital health and clinical AI to ensure seamless and responsible adoption within healthcare settings.

Methods

This paper presents a multi-level framework for healthcare systems to effectively integrate digital and AI tools by enhancing clinicians' proficiency and confidence in utilizing these emerging technologies.

Results

Our strategic framework consists of three integrated elements: (1) structured training programs to enhance clinicians' understanding and utilization of digital and AI tools; (2) leadership development pathways to cultivate champions who can drive implementation within clinical departments; and (3) performance management processes to ensure sustainable adoption aligned with organizational goals. This multi-level framework addresses current gaps in clinician preparedness for the digital health ecosystem.

Conclusion

The integration of digital and AI technologies into clinical practice requires systematic approaches to clinician development. By implementing multi-level training, fostering digital-based leadership, and establishing appropriate performance evaluation metrics, healthcare systems can better prepare their workforce for responsible technology adoption. This paper provides actionable strategies that healthcare organizations can adapt to their specific contexts to maximize the potential benefits of digital innovations in patient care.

Keywords

healthcare technology - clinician training and development - artificial intelligence - digital health - clinical informatics

Protection of Human and Animal Subjects

This project did not involve human subjects or human data. Institutional review board approval and informed consent were not required.

Contributors' Statement

M.P.P.: writing—original draft, writing—review and editing; T.S.: writing—review and editing; J.M.: writing—original draft; S.A.: conceptualization, writing—original draft, writing—review and editing; S.J.: conceptualization, supervision, writing—review and editing.

Publication History

Received: 21 August 2025

Accepted after revision: 04 March 2026

Accepted Manuscript online:
06 March 2026

Article published online:
23 March 2026

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