Job Security in the Age of AI: A Structured Forecasting Approach

As Artificial Intelligence (AI) capabilities advance in cognitive and sensory domains, the landscape of global labor markets faces significant uncertainty. This paper proposes a structured forecasting framework to estimate job resilience by decomposing occupations into five core dimensions: cognitive processing, physical execution, social interaction, sensory perception, and environmental adaptability. By applying a weighted Human Advantage Score and accounting for economic adoption factors, the model provides a systematic method for quantifying occupational safety. We demonstrate the utility of this framework through case studies of construction, software development, and dentistry, offering a rational basis for career orientation and policy planning in the AI transition era.