From Early Adoption to Sustained Use: Understanding GenAI Usage Among Software Developers in Italian SMEs
2026-05-25 • Software Engineering
Software Engineering
AI summaryⓘ
The authors studied why software developers keep using generative AI tools after they start using them, especially in small and medium businesses. They found that continued use depends mostly on how useful, enjoyable, and easy the tools seem to the individual developers. Social influences and company support did not have much effect on ongoing use. Their results show that once developers voluntarily start using these AI tools professionally, personal experience matters more than outside pressure to keep using them.
Generative AISoftware developmentUTAUT2 modelPost-adoption behaviorSmall and medium enterprises (SMEs)Longitudinal studyPLS-SEMUser experienceTechnology adoptionSustained use
Authors
Fabio Calefato, Alexandra Pajonk, Victoria Jackson, Guilherme Vaz Pereira, Rafael Prikladnicki, Filippo Lanubile
Abstract
Generative AI tools are rapidly transforming software development practice, prompting unprecedented research interest. However, existing studies have predominantly examined initial adoption rather than sustained use. Understanding what drives developers to continue using these tools after initial adoption remains underexplored, particularly in small and medium-sized enterprises where resource constraints shape technology decisions differently than in large organisations. This study investigates factors associated with developers' intentions to continue using GenAI tools, adapting the UTAUT2 framework to post-adoption professional contexts. We employed a two-phase mixed-methods design. Phase 1 comprised a six-month longitudinal pilot study at an Italian software company combining surveys and interviews with 17 developers to explore how perceptions of GenAI evolve as experience accumulates. These insights informed a structural model tested in Phase 2 through a cross-sectional survey of 154 developers across Italian SMEs, analysed using PLS-SEM. The model explained substantial variance in continued use intention (R2 = 0.647), with individual-level perceptions, particularly around productivity, enjoyment, and ease of use, driving sustained adoption, whereas social and organisational factors played no significant role. These findings suggest that, for GenAI tools, post-adoption behaviour differs from initial adoption patterns: in voluntary professional contexts, sustained use is driven primarily by individual-level factors rather than by social and organisational support.