Generative Artificial Intelligence in Instructional Design Practice: Adoption Patterns, Perceived Value, Implementation Challenges, and Emerging Professional Strategies

Abstract

Drawing upon the Unified Theory of Acceptance and Use of Technology (UTAUT), this study investigates how instructional designers in Saudi Arabian context integrate generative AI tools into their professional activities and what benefits, obstacles and the practices they have developed to support responsible implementation. A mixed-methods research design was employed which involved a survey of 262 instructional design professionals and in-depth focus group discussions with 12 practitioners representing higher education, corporate training, government, and nonprofit sectors. The findings indicate that instructional designers increasingly view generative AI as a collaborative design resource rather than a replacement for professional expertise. Performance expectancy emerged as a significant predictor of adoption, particularly in tasks involving ideation, content development, assessment design, and workflow acceleration. At the same time, participants expressed ongoing concerns regarding output accuracy, pedagogical appropriateness, data privacy, and organizational governance. The results also reveal the emergence of sophisticated human–AI collaboration models in which designers actively evaluate, revise, and contextualize AI-generated outputs before implementation. This study contributes to the growing body of research on educational applications of artificial intelligence by providing a theoretically grounded understanding of technology adoption among instructional designers. It further highlights the importance of organizational support, professional competencies, and ethical oversight in shaping effective AI integration strategies within instructional design practice.