AI Techniques and Applications in AEC: Opportunities, Challenges, and Future Perspectives – A Review Paper

Abstract

Artificial Intelligence (AI) has emerged as a transformative force across multiple industries, yet its integration into the Architecture, Engineering, and Construction (AEC) sector remains limited. This review paper provides a comprehensive analysis of existing research on the application of AI in AEC, summarizing key findings from previous studies and highlighting the potential benefits and challenges associated with AI adoption in this field.

The paper examines fundamental AI techniques, including machine learning, deep learning, natural language processing, computer vision, fuzzy logic, and evolutionary algorithms, as discussed in prior research. It further explores their practical applications in AEC, such as predictive analytics, generative design, real-time site monitoring, robotics, and automated documentation. These AI-driven technologies play a vital role in enhancing project management, mitigating risks, optimizing resource allocation, and improving overall construction efficiency.

Despite the promising advancements, the literature indicates several barriers to AI adoption in AEC, including resistance to change, high implementation costs, data quality issues, and ethical concerns. By synthesizing insights from existing studies, this review outlines a roadmap for overcoming these challenges through collaborative efforts among policymakers, industry stakeholders, and technology developers.

Ultimately, this paper underscores the significant potential of AI to revolutionize traditional workflows in AEC, contributing to a more efficient, sustainable, and resilient industry. The findings of this review serve as a foundation for future research and industry advancements, providing a structured overview of the state of AI in AEC and its prospects for broader adoption