Competency, Skills, and AI in Project Leadership: Bridging Knowledge and Productivity Gaps for 21st-Century Workforce Readiness in the Construction Industry

About the Project

The UK construction industry faces persistent challenges of productivity stagnation, skill shortages, and fragmented professional development pathways (Farmer, 2016; Construction Leadership Council, 2023). Despite ongoing digitalisation efforts, the integration of artificial intelligence (AI) technologies such as predictive modelling, resource optimisation, and decision-support systems has not yielded proportional gains in workforce efficiency (Gbadamosi et al., 2022). This research proposes to investigate workforce readiness in the UK construction sector, focusing on how project leadership competencies, tacit knowledge, and practical skills can be effectively integrated with AI-driven systems to enhance productivity and project outcomes.

The urgency for transformation stems from an increasingly digital construction landscape where human expertise must evolve alongside technological innovation (Loosemore, 2021). However, the industry continues to rely heavily on traditional labour models and fragmented training systems that fail to prepare leaders for AI-enabled decision environments (Charalambous et al., 2022). This study aims to bridge this gap by identifying the critical competencies required for effective 21st-century project leadership where human intuition, experiential learning, and adaptive collaboration complement AI’s analytical capacities.

This research is grounded in Polanyi’s (1966) theory of tacit knowledge, which highlights the experiential, intuitive dimensions of expertise often unarticulated but essential to effective practice. In parallel, Ryle’s (1949) distinction between “knowing that” (explicit knowledge) and “knowing how” (practical know-how) provides a philosophical basis for understanding how embodied skills and situational awareness underpin leadership performance. These perspectives are vital for understanding how construction professionals engage with AI systems that rely on data-driven logic but often lack contextual sensitivity. Furthermore, theories of competency-based leadership (Boyatzis, 2008) and technological adaptation (Davis, 1989) will inform the study’s conceptual lens, enabling exploration of how cognitive, interpersonal, and digital competencies interact within AI-enhanced project environments. Together, these frameworks support the development of a holistic competency model that integrates human and machine intelligence for improved project delivery.

While AI technologies offer transformative potential, their success depends on the workforce’s readiness to collaborate effectively with them (Brynjolfsson & McAfee, 2017). Existing workforce frameworks often overlook the nuanced interplay between human judgment and AI-driven decision support, leading to a widening skills gap. This study will address the dual challenge of (1) enhancing human adaptability, problem-solving, and leadership capacity, and (2) ensuring alignment between workforce competencies and emerging technological demands.

The study findings will produce an empirically grounded competency framework that aligns human and AI capabilities for improved project performance. It aims to generate actionable insights for policy, training, and leadership development - informing how educational institutions and industry bodies can modernise professional standards to foster a digitally competent workforce (CITB, 2023).