The inadequate allocation of financial and human resources globally characterizes mental health service delivery. Health Information Technologies (HITs) can address a significant portion of these challenges by increasing access, quality, and efficiency in providing healthcare services. This study, therefore, aims to assess the determinants of patient adoption of Artificial Intelligence (AI)-guided psychotherapy through the proposition of an integrative technology acceptance model. The modeling sought to evaluate the impact of trust and self-efficacy, constructs known to be relevant in health technology adoption, and the construct of hope, which is strongly associated with health and mental health yet remains underexplored in technology adoption studies. The structural equation modeling (SEM) technique was applied to data collected from questionnaires completed by 220 participants. The results partially confirmed the model. The low effect of trust and the non significance of the Perceived Ease of Use (PEOU) effect on adoption intention were unexpected. Even so, the model explained 56.1 percent of the variance in the behavioral intention to adopt AI-driven psychotherapy. Hope had a consistent effect on both PEOU and Perceived Usefulness (PU). These results reinforce the idea that hope may represent a highly valuable predictor in technology adoption studies in health and mental health, mainly when using models such as the Technology Acceptance Model (TAM).