Editorial: The Role of Artificial Intelligence in Everyday Well-Being

Niko Männikkö^1*Artur Strzelecki²

• ¹Oulu University of Applied Sciences, Oulu, Finland
• ²Uniwersytet Ekonomiczny w Katowicach, Katowice, Poland

The studies in this Research Topic employ various methodologies, including qualitative interviews, feasibility studies, and advanced statistical modelling (structural equation modelling, SEM, and artificial neural networks, ANN) to investigate user attitudes, engagement, and behavioural factors related to AI. Conceptual contributions, such as opinion and perspective papers, address ethical, trust, and governance issues, while empirical research explores psychological determinants, gender differences, and educational impacts through cross-sectional and mediation analyses. Additionally, a bibliometric analysis tracks long-term trends in AI and mental health research, complementing intervention-focused studies that assess practical applications, such as voice assistants and generative AI tools, in real-world settings.The articles in this Research Topic collectively examine how AI impacts health, education, and well-being, highlighting both opportunities and risks. In healthcare settings, a qualitative study finds that patients consider ChatGPT a helpful tool for accessing oncological information. However, concerns about privacy and the irreplaceable role of human doctors emphasise the need for clear guidelines (Durosini et al., 2025). Similarly, an opinion paper highlights that AI's success in mental healthcare relies on fostering justified trust through transparency, patient education, and human oversight (Bach & Männikkö, 2025). At the same time, a perspective article emphasises the importance of governance frameworks and accountability in mitigating the ethical risks associated with algorithmic decision-making (Cheong, 2024).Several studies examine the role of AI in mental health and education. Research on generative AI art therapy finds that adolescents' engagement is motivated by perceived trust, enjoyment, and intuitive design, suggesting strategies such as gamification to boost participation (Peng et al., 2025). Another study indicates that academic engagement enhances mental health among Chinese college students, with confidence and behavioural intention towards AI use serving as important mediators (Wang & Wang, 2024). A feasibility study on a voice assistant for parents shows potential for supporting children's mental health, although technical complexity and privacy concerns remain obstacles to adoption (Richmond et al., 2024).Finally, two papers examine broader social and systemic factors. One study finds that women report higher AI anxiety and lower positive attitudes compared to men, revealing persistent gender gaps in AI adoption (Russo et al., 2025). A bibliometric analysis documents a sharp increase in AI-related mental health research over two decades, with machine learning dominating applications for risk prediction and personalised interventions, while highlighting ongoing challenges around data quality, privacy, and bias (Chen et al., 2024).The contributions in this Research Topic collectively emphasise the dual nature of AI in shaping everyday well-being: AI offers transformative opportunities in healthcare, education, and mental health support. At the same time, it presents complex ethical, psychological, and social challenges. Across studies, themes of trust, transparency, and user attitudes emerge as key factors for successful integration, alongside concerns about privacy, misuse, and equity. Original research highlights practical applications, from ChatGPT in oncology to generative AI in therapy and voice assistants for parenting, while also underscoring ongoing gaps such as gender disparities and governance needs. Notably, the perspective on transparency and accountability has garnered substantial attention, reflecting the growing recognition that robust governance and clear communication are crucial for safeguarding well-being in the era of AI (Cheong, 2024). Together, these insights call for interdisciplinary collaboration, robust regulatory frameworks, and user-centred design strategies to ensure that AI adoption promotes safety, inclusivity, and sustainable well-being.