AI Adoption Stalls in US Construction Firms

A Bluebeam survey of 750 US industry decision makers finds most architecture, engineering and construction firms are still piloting or have not started using AI.

Updated on Nov. 2, 2026 in Artificial Intelligence

AI Adoption Stalls in US Construction Firms

Live Poll

Do you think AI is making construction projects better or worse overall?

Only 28% of US architecture, engineering and construction firms have moved AI into operational use, according to a Bluebeam survey of 750 US industry decision makers. Just 7% have embedded AI across core workflows, while 32% are piloting it in limited applications.

Why it matters

The findings suggest the industry is still early in translating AI interest into routine practice across projects. High costs and skills gaps are the main obstacles for firms that have started experimenting with the technology.

The Bluebeam survey of 750 US decision makers found 28% of firms run AI in operations, while 50% of pilot or scaling firms cite implementation costs as the top barrier. The report does not establish whether these adoption levels are rising or how the savings figures were verified.

The players

Bluebeam

Bluebeam is a construction software company whose PDF and project collaboration tools are widely used across the architecture, engineering and construction industry.

The details

Among firms running AI in production, 40% reported cost savings above $500,000, and 64% of AI users said they gained greater cost predictability. Barriers beyond cost include a lack of internal AI skills cited by 34% of respondents, security and compliance concerns by 18%, and workflow integration difficulties by 15%.

- Bluebeam's survey findings were published on November 2, 2026, in the AEC Technology Outlook Report 2027.

Roadmap

The survey shows US construction AI adoption remains concentrated in pilots, with only 7% of firms embedding it across core workflows. This places the sector behind the operational rollouts often discussed for AI across broader enterprise software.

For construction professionals, the survey signals that AI tools are still early in workflow integration, so project teams may see uneven results across tools. Firms weighing adoption should plan for implementation costs and internal skills development, which were the most-cited obstacles.

The takeaway

Firms that want measurable AI results should prioritize cost planning and staff training before expanding beyond pilot projects. Early attention to risk identification may offer the most immediate benefit, since 58% of AI users reported catching issues sooner.