Abstract
The global aging population, particularly the increasing number of individuals over 65 in Europe, presents both significant challenges and unique opportunities. This demographic shift has sparked the rise of the Silver Economy (i.e., a sector focused on the production, consumption and trade of goods and services aimed at improving the lives of the elderly), increasingly driven by technological solutions such as artificial intelligence (AI). Among these technologies, robo-advisors (RAs) hold promise in enhancing the quality of life, autonomy and social inclusion for older adults. However, while the potential of AI to integrate the elderly into society is widely acknowledged, there remain substantial gaps in understanding how best to deploy such technologies. Existing literature reveals critical limitations in methodologies and a lack of comprehensive models to guide the integration of AI into the lives of the elderly. This study addresses these gaps by adopting a constructivist approach and proposing a decision-support system to guide authorities in crafting effective policies and initiatives. The system is developed with input from field experts through participatory methods, specifically the Nominal Group Technique (NGT) and the DEcision MAking Trial and Evaluation Laboratory (DEMATEL), within a neutrosophic framework. By doing so, the study provides a more nuanced understanding of the barriers and opportunities in using RAs for the elderly, offering both theoretical advancements and practical recommendations to improve their integration into the AI-driven future of the Silver Economy.
•This study explores AI integration for elderly, focusing on robo-advisors and Silver Economy opportunities.•It develops a multi-criteria decision-support system using NGT and DEMATEL within neutrosophic logic.•The combined methodology identifies barriers, opportunities and cause-effect relationships for elderly adoption of AI technologies.•The study provides theoretical insights and practical recommendations for inclusive AI policy and solution design.