Article: Why 2026 will be a critical year for physical AI in construction

Published: JANUARY 12, 2026 | Equipment Journal

Henri Lee, Xpanner CEO, contributed a thought leadership article to Equipment Journal on why 2026 will be a critical year for Physical AI in construction.

The article outlines the industry pressures driving adoption—and why data and deployment will define the next phase of automation.

The construction industry is entering 2026 under growing pressure from labor shortages, rising costs, and economic volatility, while demand for data centers and energy infrastructure continues to increase. Traditional methods will struggle to meet the required speed and precision, accelerating interest in Physical AI as a practical path to scalable jobsite automation.

A major shift in 2026 will be the expansion of real-world deployments and the large-scale collection of field data. Unlike digital AI systems trained on internet-scale datasets, Physical AI depends on high-fidelity jobsite data—captured from machines and real environments—to operate reliably in dynamic conditions.

Physical AI can be understood through three pillars: perception, intelligence, and actuation. Perception relies on sensors such as cameras, LiDAR, GNSS, and IMUs to observe jobsite conditions in real time. Intelligence refers to models that make task-level decisions. Actuation is software-driven execution through machinery and equipment in the physical world. Across all pillars, data remains the core foundation.

As deployments grow, data feedback loops become increasingly important. Better field execution generates better datasets—covering machine motion, operator adjustments, soil interaction, task sequencing, weather and terrain variability, and safety-relevant edge cases. These datasets continuously improve system performance and reliability, enabling broader and more consistent use across jobsites.

Long-term advantage will be shaped by organizations that build the strongest real-world data foundation early, combining near-term ROI from digitization, automation, and safety with the long-term compounding benefits of proprietary field data.