<![CDATA[Purpose – The purpose of this paper is to provide insights into why construction companies fail or cannot move past the five years since their establishment by examining failures at both the individual and organizational levels and using AI as a tool to achieve productivity. Design/methodology/approach (SLR) – A systematic search has yielded 70 articles between 2019 and 2026 that met the inclusion criteria concerning construction failure, small business failure in general, and AI in construction literature; altogether, 15 of them, which were relevant from a theoretical perspective and had a high number of citations were analyzed in the context of organizational life cycle and resource-based view theories. Theoretical implications – The theories of organizational life cycle and resource-based view have been expanded through this research. Findings – The cash flow problem, employee turnover, and rigidity of management structures are the causes of a high failure rate after the first step; companies surviving past year five tend to survive with a high success rate, and AI will help with these issues. Originality/value – Proposes a Post-Startup Productivity Sustainability (PPS) model. This is the first framework linking AI capability maturity to construction enterprise life-cycle stage. Further research – There is a need for longitudinal, firm-level studies that test the model across developing and developed construction markets.]]>
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