<p>The study examines the causal relationships between the dimensions of enhancing human resource flexibility (HRF) and in turn, firm performance of construction companies in the automation-intensive industry. It aims to model the dynamics of impact under uncertainty and ambiguity, delivering a robust framework for developing HR strategies in a technology-transformed environment. The Grey Decision-Making Trial and Evaluation Laboratory (Grey-DEMATEL) technique is adopted to mitigate ambiguity and riskiness in decision-making. Initial data were collected through 76 expert surveys from senior human resources (HR) and project managers of national and multinational construction companies across India, using both online and offline participation.&#xa0;The complex causal relationships between the dimensions and sub-dimensions of human resource flexibility (functional, numerical, temporal, and cognitive) and key company performance indicators (efficiency, innovation, adaptability, and scheduled project performance) are derived, indicating that functional and cognitive flexibility are the main causal drivers, significantly impacting innovation, adaptability, and scheduled project performance in automation-enabled construction environments.&#xa0;The study is geographically constrained to firms operating in India and relies on subjective expert input, although this is mitigated through grey systems modelling. Future research should consider hybrid approaches such as Grey-DEMATEL-Artificial Neural Network (ANN) or real-time performance analytics to enhance generalizability and decision support. The study contributes to a nuanced, uncertainty-aware causal model that supports human resource-driven flexibility in the face of automation and digital transformation, thereby filling a significant gap in the performance management literature.</p>