Abstract
Worries and concerns are long recognized as barriers to technology adoption in organizations (Bedué & Fritzsche, 2022; Mariani et al., 2022). Artificial intelligence (AI) exemplifies this tension: While it promises significant benefits (Wilson & Daugherty, 2018), individuals and organizations also fear its potential harms, from job loss (Kelly, 2023) to biased or opaque decision making (Rainie et al., 2021). Such concerns can shape both individual behavior (Shell & Buell, 2022) and organizational adoption strategies, particularly for generative AI (e.g., ChatGPT) (IBM Institute for Business Value, 2024). This study analyzes survey data from over 10,000 U.S. adults (Pew Research Center, 2021) to investigate whether worries about AI and related technologies are expressed uniformly or cluster into distinct attitudinal patterns. Using cluster analysis and ANOVA, we identify three groups with differing levels of concern and show that these groups vary systematically across specific technologies, following a consistent directional order.
Our findings contribute to research on technology acceptance by highlighting attitudinal heterogeneity and by linking individual-level dispositions to organizational challenges in AI adoption. They also provide practical insights for managers seeking to address concerns that may otherwise slow the integration of AI into organizational practice.