Artificial intelligence (AI) is rapidly revolutionizing mental health by improving pharmacogenomic techniques to provide more personalized antidepressant medication. This dissertation looks at how AI-driven pharmacogenomics is observed, accepted, and applied in healthcare settings in India and Europe. The study's goal is to analyze the present state of knowledge, preparedness, and ethical issues around AI-guided prescription, as well as identify hurdles and facilitators that impact its clinical acceptance. The study used a concurrent mixed-method approach, combining quantitative data from 105 verified survey replies with qualitative insights from six expert interviews. The survey results, which were collected from healthcare professionals, researchers, and regulatory stakeholders, were analyzed using, while thematic analysis of the interviews was conducted using NVivo. The findings provide significant evidence for AI in improving antidepressant medication by minimizing trial-and-error prescription and improving treatment outcomes. 73% of all participants recognized AI's role in boosting accuracy, and 68% agreed pharmacogenomics might personalize therapy. However, geographical differences emerged: European professionals shown more knowledge and system preparedness, whereas Indian respondents raised worries about insufficient infrastructure, a lack of specialist training, and unclear legal frameworks. Data privacy concerns, ethical uncertainty, and inadequate integration into healthcare operations were recognized as common problems across both areas. Notably, the study found that increasing familiarity with AI corresponds higher trust in its application, emphasizing the importance of focused teaching initiatives. Furthermore, the readiness of healthcare professionals-particularly early adopters in both regions-indicates that stakeholder involvement, legislative reform, and technological investment are critical for wider adoption. In conclusion, the work highlights AI-driven pharmacogenomics as a possible tool for changing antidepressant prescribing habits. Healthcare systems may speed up the adoption of personalized medicine by solving regional disparities through training, ethical measures, and infrastructure development. These findings add to global conversations about digital health transformation and highlight the importance of locally appropriate policies that combine innovation with accountability.