Acceptance of business process technology: the role of usefulness, security and societal impact

Purpose Digital business process technologies are rapidly transforming the way business is done in China. Although the innovations in question purportedly come with agility and data-driven performance, their efficiency is not only dependent on technical design but also on building trust in the digital processes and governance frameworks that will govern the use of artificial intelligence (AI). This article analyzes the role of three of the most significant digital business process capabilities, including Process Automation Capability (PAC), AI-Enabled Analytics Capability (AEAC) and Process Quality (PQ), in shaping Organizational Agility (OA) through Trust in Digital Business Processes (TDBP). It also examines the moderation of the relationship between TDBP and OA by AI Governance Capability (AGC). Design/methodology/approach A quantitative survey design was used in this study, where 307 respondents who work in digitally transforming organizations across China were sampled using purposive sampling. To test the proposed direct, mediation and moderation hypotheses, Partial Least Squares Structural Equation Modeling (PLS-SEM) was used with Smart-PLS 4 due to its strength in prediction-oriented, complex models with latent constructs. Findings The analysis showed that PAC, AEAC and PQ have a strong positive impact on TDBP, which consequently has a strong positive impact on OA. The results of mediation confirm that TDBP is a crucial psychological and functional channel that connects digital competencies with agility outcomes. Furthermore, AGC has a positive moderating effect on the TDBP-OA relationship, indicating that organizations with high governance practices enjoy enhanced agility advantages of trusted digital processes. Originality/value The results show that digital agility is not simply a technological preparedness; it is the result of synergistic interaction of digital capabilities, trust in technology and responsible governance. Therefore, organizations need to put in place strong governance systems that will guarantee transparency and reliability in AI-based processes, which will strengthen trust and increase performance agility in the face of highly dynamic markets like China. Managers should be able to invest in automation and analytics technology, but also in the development of trust and the creation of responsible AI governance systems. Promoting the adoption of governance standards, which can ensure ethical, secure and transparent implementation of AI, can help policymakers to foster successful digital transformation.