Exclusive: How Are ‘Digital Twins’ Revolutionizing Infrastructure?

Why It Matters

Digital twins and AI deliver measurable cost, schedule and performance gains, positioning Canada’s infrastructure sector for higher resilience and efficiency. Early adoption sets a benchmark for globally competitive, digitally mature projects.

Key Takeaways

• Canada Line twin drives 99.8% availability via real‑time monitoring
• Eglinton Crosstown app cuts design‑construction conflicts with 4D scheduling
• LNG Canada AI identified 150 avoidable delay days, focusing 0.5% high‑risk tasks
• 36% of built‑environment professionals use AI daily, per Arup 2025 survey
• Digital maturity needs ISO 19650 governance and early lifecycle data strategy

Pulse Analysis

Digital twins are moving beyond static 3D models to become living replicas that continuously ingest sensor data, enabling predictive maintenance and operational optimization. In Canada, the Canada Line SkyTrain’s twin aggregates LiDAR, ultrasonic and condition‑monitoring inputs, delivering a 99.8% availability rate that rivals the world’s most reliable transit systems. Similarly, Vancouver International Airport’s twin visualizes passenger flows, aircraft movements and weather in near‑real time, allowing operators to test scenarios and streamline gate assignments without disrupting flights.

Project‑level applications illustrate how twins and AI translate into tangible savings. The Eglinton Crosstown West Extension deployed a mobile‑enabled twin that lets inspectors tag site conditions with GPS coordinates, feeding a 4D schedule that surfaces design‑construction clashes before they become costly rework. LNG Canada’s AI engine mined historical risk data, isolating the half‑percent of tasks that generated the bulk of schedule risk and uncovering 150 days of avoidable delay—a feat impossible with traditional risk registers. Across the sector, Arup’s 2025 survey of 5,000 professionals found 36% already relying on AI daily for planning, design and document retrieval, signaling a cultural shift toward algorithm‑assisted decision‑making.

Looking ahead, a digitally mature Canadian infrastructure project will embed a lifecycle data strategy from the outset, anchored by ISO 19650 standards for information exchange. Contracts will incentivize data quality, and interoperable twins will link into broader smart‑city ecosystems, delivering seamless handover and long‑term asset insights. While data fragmentation remains a hurdle, AI‑driven cleanup and classification tools promise to tame the information overload, ensuring that the next generation of infrastructure is not only smarter but also more resilient and cost‑effective.