Artificial intelligence adoption among construction firms has shown a dramatic increase in the US and Canada, with more than nine out of 10 using some form of the technology, according to a new study
The survey of 80 construction firms by assurance, tax and consultancy specialist RSM US and Big Village shows considerable progress in AI use after years of lagging behind other industries in technology adoption.
Some 94% of respondents now use AI tools. Of these, 80% use machine learning tools and 95% use generative AI.
The most widely available and popular generative AI tools are designed to serve as general-purpose AI assistants. As such, these tools are primarily used for communication (eg, drafting emails and internal memos), workplace productivity (creating presentations and analysing data), and research and planning.
However, the survey found that some firms are discovering new ways to leverage generative AI tools for more than just basic tasks. Mac Carroll, a senior analyst for the construction industry at RSM US, observed sophisticated use cases where clients are using Microsoft Copilot to integrate data lakes (centralised repositories) for more advanced analytics.
However, RSM cautioned that it is critical to understand the potential risks in using some generative AI tools and, specifically, tools that use an open-source approach. Unauthorised or unmonitored use by employees can further heighten the risks.
Brandon Maves, a partner and the national construction industry leader at RSM US, said: “Construction firms are seeing the potential for AI to reimagine their business models to create, deliver and capture value.
“Just imagine the possibilities for generative AI to enhance planning and design, reduce project timelines and costs, and even improve safety by proactively mitigating risk.”
The AI maturity gap
Encouragingly, 93% of construction respondents said they either have or are exploring a formal AI strategy or roadmap for AI adoption. Among the 76 respondents whose firm uses generative AI, 94% said their organisation has achieved some level of generative AI maturity, ranging from initial implementation to full or partial integration.
However, 59% of respondents who use generative AI said they are either only somewhat prepared (47%) or not very prepared (12%) to adopt and implement AI overall in their business practices.
Why the gap? Their reasons included:
- Lack of in-house AI expertise.
- Data quality challenges.
- Unclear AI strategy.
The overwhelming majority of construction respondents whose firm uses generative AI agreed that it has impacted their organisation more positively than expected (89%); that they have the right staff in place to implement generative AI effectively (87%); and that they are prepared for compliance with emerging AI regulations (88%).
Yet 64% believe they need outside help to get the most out of their generative AI solutions, and 61% agreed that generative AI has been harder to implement than expected.
Additionally, about a quarter (26%) reported unintended consequences when implementing AI overall, such as cybersecurity threats, poor data quality and workforce-related impacts.
Challenges hindering deeper integration
RSM asked the survey respondents from construction firms that use generative AI about the biggest challenges they’ve faced when implementing AI tools and processes.
The top five answers were:
- Data quality (36%)
- Budget constraints (32%)
- Data privacy and security (29%)
- Insufficient internal skills/expertise (28%)
- Regulatory or compliance concerns (28%)
Budget and outsourcing trends
The construction industry has backed its enthusiasm for AI adoption with action. Eighty-two percent of construction respondents whose firm uses generative AI said they have a designated budget for investing in the technology. Among these respondents, 90% expected the budget to increase in the next fiscal year.
Additionally, nearly half (45%) of those with a designated AI budget for AI adoption overall are allocating funds to outsourcing consulting services.
Mac Carroll, industry senior analyst at RSM US, said: “Firms don’t just need AI tools; they need a roadmap and strategic support that addresses people, process, data and technology.”
