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Artificial intelligence is finally arriving on Canadian construction sites — albeit on a limited basis.

After years of hype, the industry is beginning to experiment with AI tools that can review contracts, optimize schedules, track project progress and provide even greater design options.

However, despite growing enthusiasm for the technology, most firms remain in the testing phase, uncertain whether the tools will deliver meaningful productivity gains or create a new layer of risk.

A global study from the Royal Institution of Chartered Surveyors (RICS) suggests the construction industry stands at an unprecedented inflection point, but there has actually been very limited AI adoption among construction organizations, and they are poorly prepared.

The study found only around 20 per cent of respondents reported their organization is engaged in strategic planning around AI and undergoing proof-of-concept testing of AI solutions.

Figures from a recent nationwide survey by Statistics Canada show 12.2 per cent of all types of businesses reported having used AI to produce goods or services in 2025. However, the construction industry in Canada appears to still be at an early stage, with just 9.6 per cent of firms reported using AI software and 3.6 per cent reported using AI hardware.

“Canadian organizations need to accelerate AI implementation into core operations to start achieving near- to medium-term productivity gains,” Stephanie Terrill, managing partner of digital and transformation at KPMG in Canada, warned in a recent report prepared by the company.

The RICS report found 45 per cent of firms have not implemented AI at all. Another 34 per cent are only experimenting through pilot projects. Meanwhile, fewer than 12 per cent report regular use in specific workflows, and less than one per cent have achieved organization-wide adoption.

The survey found industry professionals see the biggest opportunities in scheduling, progress monitoring, risk management, contract review and resource optimization.

Many expect AI-driven design optioneering – where software rapidly evaluates multiple design scenarios – to become a major competitive advantage.

Presently, construction is one of the world’s least digitized industries. Project information is often fragmented across spreadsheets, emails, disconnected software systems and paper records. AI systems depend on clean, structured and centralized data to produce reliable results. Without that foundation, even sophisticated tools can generate flawed recommendations.

The RICS report noted lack of skilled personnel was cited by 46 per cent of respondents as the single largest barrier to adoption of AI. System integration challenges followed at 37 per cent, while 30 per cent pointed to poor data quality and availability.

“This is a foundational requirement for effective AI use, as high-quality, structured data is essential for fine-tuning and deploying AI models,” the RICS report states. “However, many firms still struggle with fragmented, incomplete or inconsistent data. This barrier may be especially acute in small and mid-sized organizations with limited digital infrastructure.”

According to a recent legal analysis published by E. Peyton Aldrich, a litigation attorney with Smith Currie Oles LLP, contractors and owners face several emerging risks with investing in AI.

“While these tools can make projects more efficient and data-driven, they also introduce legal, contractual and operational risks that aren’t always obvious at the outset,” she wrote in the analysis.

“As AI use grows, contractors need to understand how it works, where it creates exposure, and how to manage those risks.”

Meanwhile, AI systems can produce inaccurate information, contract-review tools may overlook critical clauses or misinterpret negotiated language, and predictive systems trained on incomplete historical data may incorrectly flag subcontractors as risky or forecast delays that do not reflect actual site conditions.

The legal risks are significant. If an AI-generated contract summary causes a project manager to miss a notice deadline or misunderstand a payment obligation, liability ultimately falls on the company – not the software.

Cybersecurity also looms as a 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, though, is overinvesting in technology before organizations are culturally or operationally prepared to use it properly.

The RICS findings reveal many companies plan to increase AI spending despite openly acknowledging they lack the workforce skills needed to deploy the systems effectively. That disconnect raises the prospect of expensive software purchases that fail to improve productivity.

Worse, it can create a situation where employees spend time verifying and correcting AI-generated output rather than eliminating work altogether.

Still, there is growing evidence that carefully targeted AI deployment can deliver measurable gains. Studies show AI-assisted scheduling can reduce project timelines by 10 to 15 per cent, while digital workflows and AI-enhanced building information modelling may cut schedules by as much as 20 per cent.

The key, analysts say, is disciplined adoption.

Rather than attempting sweeping organization-wide rollouts, firms are being encouraged to focus on specific operational problems where AI can provide immediate value — such as automating document review, improving estimating accuracy or enhancing project tracking.

RICS is calling for a co-ordinated industry roadmap involving governments, professional bodies and contractors to establish ethical standards, governance frameworks and training programs.