Human-Centered AI for Decision Support Systems: A Systematic Review of Application Domains, Architecture Designs, Current Trends and Future Directions

Artificial Intelligence is increasingly used to support decision-making across many domains. However, concerns related to transparency, reliability and human oversight indicate the need for improved human-centered AI (HCAI) approaches in decision support systems (DSSs). In this paper, a systematic review was conducted in accordance with PRISMA 2020 in the Web of Science database: ninety research articles published between 2015 and 2025 were analyzed to investigate how HCAI is applied within DSSs in multiple application domains. HCAI + DSS research outcomes were analyzed and explored, first identifying the main architectural designs and discussing the involved components integrating human interaction, generative AI models, data and knowledge management, decision logic, and orchestration mechanisms, then focusing on specific domains and highlighting impact achieved, technologies used, and validation strategies employed. In addition, alignment with United Nations’ Sustainable Development Goals (SDG) was considered, and the temporal evolution of the most relevant topics was studied to identify more interesting trends and less investigated areas. Finally, findings were summarized, current limitations were discussed, and future research directions for helping researchers and practitioners in developing more reliable, explainable, and human-aware decision support systems were outlined.