Analyzes user perceptions of AI and automation in ERP systems, suggesting key influences on adoption.
This article proposes an original analysis of the perception of users of integrated enterprise resource planning (ERP) systems regarding the adoption and use of Artificial Intelligence systems and automation tools. Building on previous results from established theories such as Unified Theory Acceptance and Use of Technology (UTUAT), Technology Acceptance Model (TAM) and Theory of Planned Behavior (TPB), the study addresses a particularly research question: why do some companies benefit from process robots, predictive analytics and intelligent automation, while others fail to capitalize on their investment? Based on 388 valid responses to a questionnaire from the users of an ERP system which is used by more than 40,000 companies, the methodology used in this research employs the PLS-SEM structural equation model. The results are interesting in the specific context of the adoption of AI and automation tools within the ERP systems, highlighting the significant influencing factors: performance expectancy, effort expectancy, social influence and job relevance. Perceived trust has an influence only in the case of the adoption of automation tools, while the moderation analysis highlighted the robustness of the model across the entire population. Based on the results obtained, theoretical and practical implications are presented, as well as future directions.
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Simionescu et al. (2026) studied this question.
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