## 6 Conclusions  
This study concludes that GAI usage in Spain is determined by a combination of individual (such as knowledge and openness to innovation) and contextual factors (such as perceived usefulness and regulation). The methodological robustness and sample size lend credibility to these findings, which not only validates the TPB as an explanatory framework but also offers new insights into the role of sociodemographic variables. The minimal influence of gender and income in the models invites a reconsideration of traditional assumptions about the digital divide, whereas the central role of knowledge underscores the need for educational policies. This study has some limitations. First, it relies primarily on existing research and technical documents, which may overlook recent empirical evidence on the direct impact of regulation in specific contexts. Second, the sample is exclusively based in Spain, potentially limiting the generalizability of the findings to regions with different regulatory frameworks. However, it is worth noting that our discussion highlights that several of our findings are consistent with those reported in other cultural settings. Finally, the rapid technological evolution of AI models creates a persistent gap between regulation and emerging technical capabilities. Therefore, gaining insightful knowledge about how generative AI is adopted requires longitudinal studies that capture the different phases of technology implementation. Future research should include empirical studies analyzing how different social groups (e.g., users, developers, and legislators) perceive the effectiveness of current regulations. It would also be valuable to study the impact of differentiated regulatory frameworks on countries with varying levels of technological development. Another promising direction is to explore hybrid governance models that combine formal regulation with self-regulation mechanisms, and open participatory algorithmic auditing tools. These lines of research may enhance the understanding of GAI adoption and trust, while contributing to the creation of a more ethical, inclusive, and secure technological ecosystem. Conceptualization, A.P.-P. and M.A.-O. ; methodology, A.P.-P. and M.S.-R.; software: J.d.A.-S.; validation: M.A.-O. ; formal analysis: A.P.-P.; investigation. A.P.-P. and M.A.-O. ; resources, M.S.-R.; data curation, J.d.A.-S.; writing--original draft preparation, A.P.-P. and J.d.A.-S.; writing--review and editing, M.S.-R.; visualization, J.d.A.-S.; supervision, M.S.-R.; project administration, M.A.-O. and M.S.-R.; funding acquisition: J.d.A.-S. and M.A.-O. All authors have read and agreed to the published version of the manuscript. This research was supported by Telefonica and the Telefonica Chair on Smart Cities of the Universitat Rovira i Virgili and Universitat de Barcelona (project number: 42. DB.00.18.00). The original data presented in the study are openly available at [[https://www.cis.es/es/detalle-ficha-estudio?origen=estudio&codEstudio=3495](https://www.cis.es/es/detalle-ficha-estudio?origen=estudio&codEstudio=3495)]([https://www.cis.es/es/detalle-ficha-estudio?origen=estudio&codEstudio=3495](https://www.cis.es/es/detalle-ficha-estudio?origen=estudio&codEstudio=3495)) (accessed on 2 May 2025). The authors declare no conflicts of interest. The following abbreviations are used in this manuscript: