INTRODUCTION: Generative Artificial Intelligence (GenAI) tools are reshaping professional education by enabling tailored content generation, automating tasks, and enhancing creative output. While widely studied in undergraduate and postgraduate education, little is known about their role in Continuing Professional Development (CPD), where professionals function as system-level educational leaders rather than learners. METHODS: A cross-sectional international survey (March-June 2025) explored GenAI adoption among CPD professionals. Using the validated Generative Artificial Intelligence Acceptance Scale and the Artificial Intelligence Attitude Scale, the study examined performance expectancy, effort expectancy, facilitating conditions, social influence, and general attitudes toward Artificial Intelligence. Quantitative data were analyzed descriptively and inferentially, and qualitative open-ended responses were analyzed using reflexive thematic analysis. RESULTS: A total of 110 respondents from 14 countries participated. Most reported moderate to high familiarity and comfort with GenAI, with frequent users demonstrating significantly greater confidence and perceived proficiency. Performance expectancy was high, particularly regarding efficiency and productivity, but lower for complex problem-solving. A proportion of respondents expressed undecided positions, indicating transitional stages of adoption. Qualitative analysis revealed three overarching themes: (1) adoption and utilization, (2) personal perspectives, and (3) perceived challenges and benefits. DISCUSSION: CPD professionals view GenAI as an augmentative tool that enhances efficiency and creativity rather than replacing human expertise. While individual readiness is high, sustainable adoption depends on institutional support, structured training, and ethical integration. This study provides novel insights into GenAI adoption at the CPD system level and highlights the importance of engaging the "undecided" to move from incremental use to meaningful transformation.
Valanci et al. (2026) studied this question.