Health Care Professional Association Agency in Preparing for Artificial Intelligence: Protocol for a Multi-Case Study

Area of Science:

• Healthcare innovation
• Professional regulation
• Sociotechnical systems

Background:

• Artificial intelligence (AI) is transforming healthcare, impacting professional roles, training, and regulation.
• Health professional associations play a crucial role in guiding members through AI-driven changes.
• Understanding how these associations navigate AI adoption is vital for future healthcare practice.

Purpose of the Study:

• To present a study protocol examining how health professional associations make sense of and legitimize AI-driven changes.
• To explore strategies associations use to prepare their members for the integration of AI in healthcare.
• To provide a framework for understanding professional adaptation to disruptive technologies.

Main Methods:

• An exploratory multi-case study design utilizing Normalization Process Theory (NPT).
• Data collection through key informant interviews, meeting observations, and document analysis across 4 selected health professional associations.
• Stakeholder network mapping for sensemaking activities and thematic analysis using a hybrid inductive-deductive model.

Main Results:

• Preliminary data includes 17 interviews (15 transcribed) and ongoing document review across 4 associations.
• Cross-case analysis will highlight guidance for AI implementation and NPT application at the macro level.
• Findings will depend on the priority and actions taken by associations regarding AI preparedness.

Conclusions:

• This protocol outlines a case study to understand professional association responses to AI disruption.
• It aims to elucidate the sensemaking and legitimization processes supporting members' adaptation to AI.
• The study will offer insights into managing technological change within professional bodies.