Expectations and Perceptions on Artificial Intelligence and Innovation in the AEC Sector : A Case Study on Project Managers

Sammanfattning

The Architecture, Engineering, and Construction (AEC) sector is one of the least digitized industries and subject to low performance growth and inefficient project management practices, stemming from inherent challenges with managing change. In response to this, the sector is beginning to explore artificial intelligence (AI), expected to be one of the most transformative technologies in the coming decade, and its possibility to streamline processes and increase project productivity. Given the AEC sector’s need for enhanced project management practices and its slow digital transformation, this thesis aims to explore the intersection between AI and project management, and challenges associated with implementing new technology and work methods from the perspective of project managers. To fulfill the purpose of this study, a single case study at the infrastructure department within one of the largest Swedish AEC consulting firms was conducted through a qualitative interview study. A review of relevant literature served as a complement to the primary data retrieved from the interviews, serving as a theoretical foundation to support the analysis. The results show an overall positive attitude towards AI and reveal several potential application areas in project management and project related work in the AEC sector. The results show a generally positive attitude towards AI among project managers, viewing it as a tool for enhancing efficiency, quality, and reducing costs by automating labor-intensive tasks and leveraging predictive capabilities. While AI is not seen as a threat to project managers' roles, there are concerns about its impact on other roles within projects. Successful AI integration is expected to increase competitiveness and business capacity through enhanced efficiency within the sector. However, challenges associated with technology implementation and changed work methods include the decentralized organizational structure, lack of top management support, inadequate standardized methods, poor knowledge transfer, and the variable compensation model. This study contributes to the literature by highlighting potential application areas for AI in project management within the AEC sector as well as corresponding impacts. By providing a nuanced understanding of barriers to technology adoption and change within the sector it further underscores the need for top management support and strategic direction to harness the full potential of technologies as AI.