The integration of Artificial Intelligence (AI) in construction project management is revolutionising the industry; offering innovative solutions to enhance efficiency, reduce costs, and improve decision making. This structured literature review explored the current applications, benefits, challenges, and future trends of AI in construction project management. This study synthesised findings from 135 peer-reviewed articles published between 1985 and 2024; representing Industry 3.0 (3IR), Industry 4.0 (4IR), and Industry 4.0 Post COVID-19 (4IR PC). Analysis showed that the Planning and Monitoring and Control phases of the project have the greatest application of AI, while decision making, prediction, optimisation, and performance improvement are the most common purposes of AI use in the construction industry. The drivers of AI adoption within the construction industry include technology availability, project outcome and performance improvement, a competitive advantage, and a focus on sustainability. Despite these advancements, the review revealed several barriers to AI adoption, including data integration issues, the high cost of AI implementation, resistance to change among stakeholders, and ethical concerns surrounding data privacy, amongst others. This review also identified future ongoing applications of AI in the construction industry, such as sustainability and energy efficiency, digital twins, advanced robotics and autonomous construction, and optimisation. By providing a comprehensive analysis of the evolution of practices and the future direction of AI application, this study serves as a resource for researchers, practitioners, and policymakers seeking to understand the evolving landscape of AI in construction project management.

Purpose: The purpose of this study is to explore the barriers to implementing lessons learned in project-based organisations and how they can be effectively captured and embedded to create knowledge that drives project success and organisational performance. Design/methodology/approach: The study adopted a qualitative research design to explore the perceptions and experiences of project practitioners through the lens of social learning theory (SLT). Semi-structured interviews were conducted to uncover individual project practitioners’ views and opinions about lessons learned in the project environment to facilitate project success. Findings: The findings indicate that effective application of lessons learned and knowledge sharing significantly enhances project success by fostering a culture of collective learning and continuous improvement. The key barriers identified are misinterpretation of lessons learned, lack of mentoring, knowledge hiding, non-participation from relevant stakeholders and lack of a collaborative environment. Practical implications: Organisations should formulate clear guidelines, implement robust knowledge repositories and standardise lesson-learned processes to foster uniform understanding within and across projects. Organisations should also invest in training programs and promote mentorship and top management support to foster a culture of learning and accountability. Originality/value: The paper presents a unique avenue to understanding lessons learned in the context of project-based learning. It highlights barriers and strategies across dimensions and explores them through a participatory and social lens. By using an SLT theoretical framework, the study provides a fresh perspective on how knowledge can be shared and utilised within project organisations. It bridges gaps in literature and provides actionable insights, making it highly valuable to both academic and practical fields.