Constructing Excellence’s AI Programme continued with a thought-provoking discussion delivered in collaboration with ARCOM, the Association of Researchers in Construction Management, bringing together academic insight and industry experience to explore how artificial intelligence is reshaping construction practice, skills and decision-making.
- AI must be adopted pragmatically, not uncritically — the session challenged both the hype around AI and the instinct to reject it, calling instead for a balanced approach focused on better outcomes.
- Human judgement remains essential — AI can support analysis, design and decision-making, but it cannot understand context, exercise accountability or replace professional scepticism.
- Skills and education need to evolve — the discussion highlighted the importance of critical thinking, clear argumentation and confidence in human intelligence alongside digital capability.
- Responsible AI requires strong governance — participants explored risks around data privacy, cyber security, automation bias, sustainability and the need for collaboration across industry and academia.
The session, part of an ongoing collaboration between Constructing Excellence and ARCOM, created space for a wide-ranging conversation about the opportunities, risks and responsibilities associated with AI. It reflected the purpose of Constructing Excellence’s programme: to look beyond individual tools and use cases, and to consider the people, process and cultural change needed if AI is to support better outcomes for the built environment.
Dr Dimosthenis Kifokeris, Associate Professor in Construction Management and Production at Chalmers University of Technology, shared a research-led perspective grounded in more than a decade of work on AI and construction management. He outlined how AI, including machine learning and large language models, can support areas such as risk analysis, design optimisation and decision support. However, he also emphasised that AI systems should not be mistaken for human intelligence. They are powerful pattern-recognition tools, but they do not understand context, exercise judgement or carry accountability.
A strong theme throughout the discussion was the need for balance. The session challenged both uncritical enthusiasm and outright rejection of AI, instead calling for a pragmatic approach in which the industry actively shapes how the technology is adopted. Participants explored the importance of professional scepticism, critical thinking and human judgement, particularly in a sector where decisions have real-world consequences for safety, quality, cost and relationships.
The conversation also highlighted the implications for education and future capability. Dr Kifokeris warned that over-reliance on AI in higher education can weaken students’ ability to construct and defend robust arguments, even where written outputs appear more polished. For construction, this raises important questions about the skills future professionals will bring into the workplace, and the need to develop confidence in human intelligence alongside digital capability.
Industry contributors shared practical examples of AI beginning to change workflows, including procurement and bidding. Used well, AI can reduce time spent processing large volumes of information and create more space for quality review, moderation and deeper decision-making. However, the group also recognised the risk that efficiency gains could simply intensify workloads, rather than enabling more creative, collaborative and meaningful work.
Governance and sustainability were central to the debate. Participants considered issues including data privacy, cyber security, accountability, automation bias and the environmental impact of AI infrastructure. The discussion reinforced that responsible AI adoption is not only a technical challenge, but a collaborative one requiring input from industry, academia, professional bodies and clients. For Constructing Excellence, the session underlined the value of convening these conversations: helping the sector move beyond hype towards a more mature understanding of how AI can be used responsibly to deliver better outcomes.