Canadian construction firms are testing AI tools, but most remain unprepared
After years of promises, artificial intelligence is finally appearing on Canadian construction sites - though adoption remains limited and cautious. Firms are experimenting with tools that review contracts, optimize schedules, track progress and generate design options. Most, however, remain in testing phases and uncertain whether the technology will deliver real productivity gains or introduce new risks.
A global study from the Royal Institution of Chartered Surveyors found the construction industry at an inflection point, yet poorly equipped to move forward. Only 20 per cent of respondents reported their organizations are doing strategic planning around AI and running proof-of-concept tests.
Canadian construction lags even further behind. Statistics Canada data shows 12.2 per cent of all businesses used AI to produce goods or services in 2025. In construction, just 9.6 per cent of firms reported using AI software, and 3.6 per cent used AI hardware.
The numbers tell the story clearly: 45 per cent of construction firms have not implemented AI at all. Another 34 per cent are only running pilot projects. Fewer than 12 per cent use AI regularly in specific workflows, and less than one per cent have achieved organization-wide adoption.
Where construction sees the biggest opportunities
Industry professionals identified five areas where AI could add the most value: scheduling, progress monitoring, risk management, contract review and resource optimization. Many also expect AI-driven design analysis - where software rapidly evaluates multiple design scenarios - to become a competitive advantage.
Studies suggest the gains could be substantial. AI-assisted scheduling can reduce project timelines by 10 to 15 per cent. Digital workflows combined with AI-enhanced building information modelling may cut schedules by as much as 20 per cent.
The barriers blocking adoption
Lack of skilled personnel is the single largest obstacle. The RICS study found 46 per cent of respondents cited workforce skills as their main barrier to AI adoption. System integration challenges followed at 37 per cent, while 30 per cent pointed to poor data quality.
Construction remains one of the world's least digitized industries. Project information sits scattered across spreadsheets, emails, disconnected software systems and paper records. AI systems need clean, structured and centralized data to function reliably. Without that foundation, even sophisticated tools produce flawed recommendations.
Small and mid-sized organizations face especially acute challenges. Many still struggle with fragmented, incomplete or inconsistent data and lack the digital infrastructure to fix it quickly.
Legal and operational risks are mounting
As firms invest in AI, they face emerging legal exposures. Contract-review tools may overlook critical clauses or misinterpret negotiated language. Predictive systems trained on incomplete historical data might incorrectly flag subcontractors as risky or forecast delays that don't reflect actual site conditions.
If an AI-generated contract summary causes a project manager to miss a notice deadline or misunderstand a payment obligation, liability falls on the company - not the software vendor. That distinction matters legally and financially.
Cybersecurity presents another growing concern. As firms store more project data in AI-enabled platforms, they increase exposure to data breaches and cyberattacks targeting sensitive project information or connected equipment.
Perhaps the greatest risk is overinvesting in technology before organizations are culturally or operationally ready. Many companies plan to increase AI spending despite openly acknowledging they lack the workforce skills needed to deploy systems effectively. That disconnect can lead to expensive software purchases that fail to improve productivity, or worse - situations where employees spend time verifying and correcting AI output rather than eliminating work altogether.
How to adopt AI responsibly
Analysts recommend disciplined, targeted deployment rather than sweeping organization-wide rollouts. Firms should focus on specific operational problems where AI can provide immediate value - automating document review, improving estimating accuracy or enhancing project tracking.
KPMG warned in a recent report that Canadian organizations need to accelerate AI implementation into core operations to start achieving productivity gains in the near to medium term.
The RICS study calls for a coordinated industry roadmap involving governments, professional bodies and contractors. This roadmap should establish ethical standards, governance frameworks and training programs to guide adoption across the sector.
For construction professionals, the message is clear: AI tools work when deployed carefully on specific problems, with proper data foundations and skilled teams. Buying the technology without addressing those fundamentals wastes money and creates risk.
Learn more: AI for Real Estate & Construction covers AI applications in construction planning and project management. AI Agents & Automation explores how automation tools can streamline construction workflows.
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