Trust and adoption maturity: An analysis of industry perceptions on the generative AI competency gap among business graduates

This study maps the importance, perceived needs, and competency gap of Generative Artificial Intelligence (GenAI) across four domains—Technical, Strategic, Ethical, Adaptive—and examines their associations with trust, adoption maturity, and industry context. Data were collected from 389 industry professionals in Indonesia using purposive and snowball sampling. The analysis employed descriptive statistics, Spearman correlation, Kruskal-Wallis H tests, and post-hoc Mann-Whitney U tests. The results indicate relatively high perceived GenAI competency needs across all domains, with the largest perceived gaps in the Technical and Strategic domains. Trust in GenAI was positively associated with perceived competency needs across all four domains and with perceived competency gaps in the Technical, Strategic, and Adaptive domains, but not the Ethical domain. Adoption maturity was associated with differences in several dimensions of industry perceptions, particularly industry-perceived graduate readiness to adopt GenAI and perceived needs in the Adaptive and Strategic domains. Sectoral differences were limited, with significant variation observed only in industry-perceived graduate readiness. The study contributes an integrated perspective linking trust and adoption maturity with perceived GenAI competency needs and gaps in Indonesia, highlighting curricular areas that warrant greater attention to applied Technical and Strategic capabilities across organizational GenAI adoption stages.