Ally or adversary? AI and the perceived threat to autonomy in services – The case of real estate professions

This study investigates the impact of perceived threats to professional autonomy on the adoption of artificial intelligence (AI) by real estate professionals. It aims to examine how emotional and motivational factors shape attitudes toward AI, particularly within the augmentation-automation paradox, which juxtaposes AI's potential to enhance capabilities with fears of diminished autonomy. The research adopts a cognitive appraisal framework and employs structural equation modeling (SEM) to analyze survey data from 310 real estate agents. The study assesses relationships between intrinsic motivation, perceived autonomy threat, performance expectations, perceived effort, emotional responses, and willingness to adopt AI systems. The findings reveal that intrinsic motivation positively influences performance expectations and reduces perceived effort, while perceived threats to autonomy negatively impact performance expectations. Emotional responses mediate the relationship between these variables and the willingness to adopt AI, with positive emotions encouraging adoption. Social influence, surprisingly, shows no significant effect on performance expectations or perceived effort. This study advances the understanding of AI adoption by emphasizing the role of emotional and motivational factors in professional settings. It highlights the unique challenges faced by real estate professionals, where autonomy is a key aspect of their role, and contributes to the broader discourse on the augmentation-automation paradox in AI integration. • Explores the augmentation-automation paradox in the adoption of AI in real estate services. • Identifies the perceived threat to professional autonomy as a key barrier to AI adoption. • Integrates Lazarus's cognitive appraisal theory to examine emotional and motivational responses. • Reveals that AI adoption depends on balancing technological benefits with autonomy preservation. • Provides actionable strategies for mitigating resistance to AI through tailored organizational practices.