From AI Literacy to Sustainable Design Capability: A Social Cognitive Inquiry Into Self‐Efficacy and Autonomy in Design Practice

Abstract

As artificial intelligence (AI) increasingly transforms organizational and creative workflows, sustaining human expertise has become a critical challenge for organizations seeking to balance automation with long‐term capability development. To prevent cognitive deskilling and support knowledge retention, organizations must understand how professionals develop, transfer, and maintain AI‐related competencies over time. Drawing on Social Cognitive Theory (SCT), this study examines the relationship between AI literacy and sustainable skill transferability, with technical self‐efficacy mediating and AI autonomy moderating. Data were collected from 260 professional designers using a three‐wave, time‐lagged research design and analyzed through SmartPLS‐SEM (version 4). The findings indicate that AI literacy positively influences technical self‐efficacy, which in turn enhances the sustainable transferability of skills across evolving technological contexts. However, the results also reveal that higher levels of AI autonomy weaken the positive relationship between AI literacy and technical self‐efficacy. This suggests that while autonomous AI systems may improve operational efficiency, they may simultaneously reduce opportunities for mastery experiences that support the development of confidence and long‐term capability retention. By extending SCT to AI‐enabled design environments, this study contributes to emerging debates on human–AI collaboration and offers practical guidance for designing co‐creative workflows that promote sustainable capability development rather than mere task automation.