Nearly nine in ten contractors expect artificial intelligence to have a meaningful impact on construction, with many anticipating industry-wide transformation of project delivery and business operations. Research by Dodge Construction Network, in partnership with CMiC, also found that 85% of respondents expect AI to cut time spent on repetitive tasks, over 70% believe it will support better decision-making, and three-quarters see value in mining historic project data for lessons learned.
Organisational readiness is mixed but momentum is building. More than half of surveyed firms are running AI pilots and preparing staff for AI-related roles, 40% have ringfenced budget for AI and 38% have set up implementation teams. A further 19% are adapting legacy workflows for an AI-enabled environment, while just over half are actively evaluating a range of AI-driven changes across their businesses.
Current use of AI remains limited across most project and company management functions, with fewer than half of contractors aware that specific tools are AI-enabled and fewer than 15% using most of the 23 functions studied. However, feedback from early adopters is strong: over 70% of contractors using AI-enabled functions rate them as highly effective compared with previous methods, suggesting scope for rapid scaling once solutions mature and awareness improves.
Contractors highlighted several priority use cases on live projects, including automated constructability analysis (backed by 81% of respondents), intelligent permit submission with automatic compliance checking (80%) and autonomous project optimisation that can adjust programmes and resources in real time (79%). On the business side, 76% see potential in dynamic pricing optimisation, 92% in automated contract creation and management, and 79% in intelligent bid/no-bid decision support.
Data remains the main brake on wider deployment. More than half of contractors are concerned about data accuracy (57%) and security (54%), and over a third cite implementation costs and internal resistance as barriers. Only 26% currently rate their data quality as high, underlining the need for better information management if AI is to be embedded at scale across UK construction supply chains.
