AI-driven risk mitigation: Transforming project management in construction and infrastructure development

This study explores the transformative role of artificial intelligence (AI) in risk mitigation within construction and infrastructure development, addressing the growing complexities of modern project management. The purpose of the study was to evaluate how AI technologies, frameworks, and strategies can mitigate environmental, economic, and social risks while fostering sustainability and operational efficiency. Utilizing a multidisciplinary approach, the research integrates theoretical and practical perspectives to examine AI’s applications, ethical considerations, and future trends in project management. The study identifies predictive analytics, Internet of Things (IoT)-based monitoring, and blockchain technology as pivotal tools for enhancing decision-making, resource optimization, and transparency in project workflows. It underscores AI’s significant contributions to sustainability through climate-resilient design, energy-efficient systems, and environmentally compliant practices. Ethical and legal frameworks emerged as essential to ensuring the equitable and responsible deployment of AI, focusing on data privacy, accountability, and algorithmic fairness. Key findings demonstrate that AI-driven risk mitigation enhances project outcomes by reducing delays, minimizing costs, and fostering inclusivity. Applications in public health campaigns and social housing highlight AI’s capacity to address societal challenges while advancing sustainability goals. However, the study also identifies critical challenges, including organizational resistance, data quality limitations, and regulatory gaps, which hinder the full integration of AI technologies. The study concludes that AI is a transformative force in risk mitigation, offering innovative solutions to the multifaceted challenges of modern project management. To fully leverage its potential, the research recommends fostering interdisciplinary collaboration, developing adaptive ethical and legal frameworks, and advancing AI integration with emerging technologies like IoT and blockchain. Investments in education and training are also emphasized to bridge technical knowledge gaps and empower stakeholders.