Agility and AI-Driven Staffing Optimization for Bench Candidates in IT: A Cross-Industry Theoretical Framework

Anand Sunder

Abstract: This paper explores how artificial intelligence (AI) and organizational agility can be leveraged to optimize hiring and staffing strategies for bench candidates in the IT sector. It integrates insights from market demand forecasting, adjacency-based training models, and fulfilment cycle analytics. A theoretical model is proposed to generalize staffing strategies across industries, emphasizing adaptability, predictive analytics, and skill adjacency networks.

Keywords: Artificial intelligence, staffing, optimization, hiring supply chain, IT, organizational agility

How to Cite?: Anand Sunder, "Agility and AI-Driven Staffing Optimization for Bench Candidates in IT: A Cross-Industry Theoretical Framework", Volume 14 Issue 8, August 2025, International Journal of Science and Research (IJSR), Pages: 585-587, https://www.ijsr.net/getabstract.php?paperid=SR25812093330, DOI: https://dx.doi.org/10.21275/SR25812093330