TLDR: A recent study by RSM US and Big Village reveals a significant surge in AI adoption within the US and Canadian construction sectors, with 94% of firms now utilizing AI tools. Despite this widespread adoption, a notable ‘maturity gap’ exists, indicating that while firms are using AI, many are not fully prepared for its comprehensive integration.
The construction industry in the US and Canada is experiencing a dramatic increase in the adoption of Artificial Intelligence (AI), with a new study indicating that over nine out of ten firms are now leveraging some form of the technology. This marks considerable progress for a sector that has historically lagged in technology adoption. The survey, conducted by assurance, tax, and consultancy specialist RSM US and Big Village, polled 80 construction firms, revealing that 94% of respondents currently employ AI tools in their business practices. Of these, 80% utilize machine learning tools, and a striking 95% have adopted generative AI.
Generative AI tools, primarily used as general-purpose AI assistants, are most commonly applied for communication, workplace productivity (such as creating presentations and analyzing data), and research and planning. This widespread use demonstrates a clear recognition of AI’s potential to enhance various operational aspects within construction.
However, the study also highlights a significant ‘AI maturity gap.’ While an encouraging 93% of construction respondents reported having or exploring a formal AI strategy or roadmap, and 94% of generative AI users have achieved some level of maturity (from initial implementation to full or partial integration), a substantial portion remains unprepared for comprehensive AI adoption. Specifically, 59% of generative AI users stated they are either only ‘somewhat prepared’ (47%) or ‘not very prepared’ (12%) to fully integrate AI into their business practices.
This ‘maturity gap’ is attributed to several key challenges identified by the survey respondents. The top five hurdles faced during AI tool implementation include data quality (36%), budget constraints (32%), data privacy and security (29%), insufficient internal skills/expertise (28%), and regulatory or compliance concerns (28%). The lack of in-house AI expertise and ongoing data quality issues are particularly cited as reasons for this preparedness gap.
Also Read:
- AI Adoption Surges in Data Centers, But Trust and Data Quality Remain Key Concerns
- AI Adoption Hindered by Insufficient Governance and Training, New Surveys Reveal
Despite these challenges, the rapid embrace of AI signifies a transformative period for the construction industry, moving it closer to other sectors in terms of technological advancement. The focus now shifts from mere adoption to strategic integration and overcoming the identified barriers to fully harness AI’s potential.
