Strategic Workforce Planning Through Human-AI Collaborative Intelligence: A Dynamic Capabilities and Predictive Analytics Framework.​

ABSTRACT:

Contemporary organizations encounter substantial challenges in strategic workforce planning, with empirical evidence indicating that merely 15% of enterprises engage in comprehensive long-term talent forecasting beyond conventional headcount methodologies. This investigation develops an integrated theoretical and operational framework for optimizing human-AI collaboration within strategic workforce planning domains, specifically addressing critical deficiencies in organizational capabilities and predictive talent management systems. Through systematic examination of dynamic capabilities theory synthesized with human-computer interaction paradigms, this study advances an innovative collaborative intelligence architecture that harmonizes AI-driven predictive analytics with human strategic reasoning processes. The framework directly confronts the anticipated 85 million vacant positions projected by 2030 through enhanced organizational performance mechanisms and strategic talent optimization strategies. Principal findings establish that effective human-AI collaboration necessitates methodical integration of technological competencies with human cognitive advantages, transparent decision-making architectures, and adaptive organizational configurations. The proposed framework contributes substantially to theoretical comprehension and practical deployment of collaborative intelligence systems within workforce planning environments.

Keywords: Human-AI collaboration, strategic workforce planning, predictive analytics, organizational capabilities, talent forecasting.