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InsightConnect: An AI-powered talent intelligence system for optimized workforce matching and forecasting
Shao-Lun Lee1, Mei-Hua Hsu2, Max Yue-Feng Wang3
1Department of Information Management, Asia Eastern University of Science and Technology, New Taipei, Taiwan.
Abstract:
The rapid advancement of artificial intelligence (AI) is reshaping talent management by enabling data-driven approaches to recruitment, skill development, and workforce planning. This study introduces the InsightConnect AI Empowerment System, an integrated digital platform designed to optimize talent-project matching, recruitment forecasting, and knowledge sharing through predictive analytics, natural language processing (NLP), and graph-based learning. Grounded in a Design Science Research (DSR) framework, the system was developed and validated using anonymized datasets comprising 10,000 user profiles and approximately 2,000 enterprise projects (1,840 completed projects used for evaluation).The hybrid recommendation model, combining content-based, collaborative, and graph-embedding techniques, achieved a 12.7% improvement in precision and a 10.4% increase in recall over traditional baselines, while the predictive module attained a Root Mean Square Error (RMSE) of 0.083, indicating strong forecasting accuracy. Prototype deployment results revealed a 24% rise in successful talent-project matches and a 30% reduction in search time, enhancing both organizational efficiency and user satisfaction.The findings highlight how AI-enabled ecosystems can advance workforce intelligence, improve data-informed decision-making, and support policy innovation for sustainable human capital development.
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