By Shawn Gray, Founder and CEO, ConstructIQ Advisory

In 2025, construction saw record AI curiosity; and while majority are experimenting with AI-assistants for personal use-case, AI delivered measurable gains for firms that approached adoption strategically.

The year clarified that success hinges less on data or tools and more on clarity, capacity, process, and environment. Across dozens of Proof of Value Projects through our national AI Adoption Initiative, firms unlocked $3M+ in working capital to fuel innovation and growth, proving budget no longer needs to delay adoption. The true constraint is capacity — time, skills, and selecting the right project and people to demonstrate value.

Mid-market firms continue to lead meaningful AI-adoption; focusing on how AI can increase capacity for preconstruction teams to set project delivery up for success, and for reducing administrative drag preventing project staff from proactive and profitable execution.

With AI agents, human-in-the-loop practices, and accelerated learning now emerging, 2026 will reward firms that invest in codified processes and structured Proof-of-Value approaches to scale these gains across the business.

For Proof of Value case-studies, AI Adoption resources, or to participate in the 2026 AI Adoption Initiative, visit www.constructiqadvisory.ca

Across 2025, construction saw unprecedented curiosity around AI. In industry surveys and Proof-of-Value (PoV) projects, 80% of professionals reported strong interest in AI, and 65% now use personal AI assistants daily. Yet fewer than 4% of firms have translated that interest into measurable, operational results — despite more than 1,000 AI-enabled construction tools now on the market.

The reason is clear: AI success depends far more on clarity, capacity, and environment than on tools, models, or data maturity.

After a year of PoVs and executive sessions across Canada’s construction associations, largest builders, and fastest-growing mid-market firms, several AI-Adoption truths became unmistakable:

• Data is not the true barrier most assume. Most early AI use cases require accessible data, not perfect data; and are more people and process reliant, than data reliant.
• Budget is a key constraint but no longer a barrier.  Over 85% of firms exploring AI lacked adequate budget for new technology and resources with skills to implement, citing they assume funding would come from enterprise overhead, project margin, or clients; which have proven ineffective and unsustainable methods of digital adoption.
• Across the AI Adoption PoV Initiative, firms uncovered more than a dozen financially sustainable ways to fund adoption without taxing projects. These mechanisms unlocked over $3M in capital, enabling firms to move faster, reduce risk, and bring in people with the time and skills to implement. Many now operate self-perpetuating innovation funds that replenish through operational savings.
• Capacity is the true constraint. The real remaining blockers are time. Choosing the right project and people environment for value to emerge is surfacing as the most common pitfall preventing firms from successful value-recognition and moving to scaled adoption.

Large enterprises remain committed to highly ambitious and complex data-reliant initiatives and in-house technical departments that eclipse the size of the average construction business. Despite this, and the marketing, actual scaled adoption and meaningful gains remains yet to be realized, slowed by staff hesitation stemmed from tech-fatigue and failed past initiatives, organizational politics and complexities, and blurred lines of ownership, authority, and decision making.

Mid-market firms, however, are continuing to outpace large enterprises by focusing on key underlying constraints and minimum viable tools, leveraging strategic innovation funding mechanisms, collaborating with emerging tech SME’s for mutual win-win outcomes, and joining cohorts of similar business for AI adoption insights exchange.

As a result, mid-market firms are winning the race in moving beyond experimentation and adopting meaningful applications of AI with less risk, time, and cost.

The firms that achieved meaningful results answered six foundational questions before touching a tool:

• Why — What business objective are we solving (growth, profit, cashflow, costs)?
• What — What are the key challenges staff face preventing this business objective
• What — What are the underlying constraints and minimum viable solutions?
• How — How will we support adoption with budget, time, and skills?
• When — Which project timing offers sufficient runway and stability?
• Where — Which environment can demonstrate visible, measurable value?
• Who — Which champions have influence, experience, and openness?

This clarity — paired with adequate capacity and the right environment — predicted success far more accurately than data readiness or tool selection.

Once their strategic AI-Why was established, they proceed to establish Proof of Value in real-world scenarios, focused on staff value-recognition and adoption metrics over dollars.

One of the biggest learnings of 2025 is that AI’s universal value is capacity — freeing time so people can focus on resolving constraints and move the business forward.

Take preconstruction; the #1 area firms sought support in: Most teams drown in RFP responses, contract and drawing reviews, bid leveling, vendor pricing, and manual documentation. As a result, opportunities are either lost completely, or key risks are missed and handoffs to operations suffer, creating execution risks from the get-go that directly translate into impacts on costs, cashflow, profitability, and staff satisfaction and retention.

AI-enabled processes proved to remove hours of low-leverage work in those areas — but the real business gains came when firms intentionally repurposed that freed capacity into clearer assumptions and risks, stronger execution plans, and higher-quality handovers. This enabled operations to more effectively triage their time and produce predictable project outcomes and has already improved profitability and cash flow for firms heading into 2026.

Based on this year’s PoVs, five categories consistently delivered the highest ROI:

1. Business Development & Preconstruction

• Proactive project opportunity identification, RFP extraction, and proposal drafting
• Spec and drawing reviews for early risk detection and mitigation
• Real-time lessons learned incorporation
• Bid leveling & assumptions/risks extraction
• Risk management and execution plan production
• Handover to operations

2. Contract & Risk Intelligence: Remove review-capacity bottlenecks and improve upstream risk mitigation, provide contract compliance and change identification downstream.

3. Project Administration & Operation: Reducing admin drag so staff can focus on supervision, coordination, and prevention.

4. Workforce Upskilling & Capacity Expansion: AI gives junior staff senior-level insight, allowing firms to grow with less HR cost.

5. Knowledge Reuse: Capturing lessons learned and injecting them directly into estimates, proposals, contracts, and execution plans.

Three themes will define 2026:

• AI Agents Will Rise — But Processes Will Determine Winners. Without standardized, codified workflows, agents simply recreate the chaos of bespoke spreadsheets.  Success with agents will depend on process maturity, not hype.
• The 10-80-10 Human-in-the-Loop Model Will Become Standard. 10% human framing → 80% AI drafting → 10% human review.  This isn’t a limitation — it’s a best practice that aligns with ISO-backed business quality management standards.
• “AI Zombies”. Despite headlines suggesting over reliance is creating mindless zombies who lack critical thinking and foundational knowledge, real adoption shows the opposite: AI accelerates learning, exposes insights earlier, and strengthens critical thinking when paired with proper review. Given the resource gaps and need for accelerated learning, leaders will ignore headlines and lean into this.

Those who fuel or subscribe to hype and myths are revealing their weakness in areas of both AI-acumen and true business management acumen. While leaders are recognizing how AI empowers their people and enhances business best-practice fundamentals.

Construction doesn’t need more AI hype. It needs execution, proof of value, and adoption founded on clarity, capacity, the right environment, and strong processes.

2025 proved that with the right approach, AI can provide significant gains, and adoption requires far less data, far less budget, and far less risk than most firms believe.

The companies that internalize these truths will define the industry’s success stories in 2026 and beyond.

Explore related articles you won’t want to miss:

Can Data and AI be Leveraged to do More with Less? The BuildexBC Contech Showcase proved a clear ‘YES’

How AI Enabled a Mid-Sized Contractor to Cut Costs & Reduce Risk by Freeing Up Field Resources and Improving Documentation