Bluebeam survey of 750 US AEC firms finds 28% run AI in production and 17% credit it with less rework

Bluebeam released its 2027 AEC Technology Outlook Report on October 13, 2026. Hanover Research ran the survey online for Bluebeam in July 2026, and the US edition covers 750 decision-makers at architecture, engineering and construction firms. About 28% of those firms say AI is in production, and 7% say it runs across several core workflows. Among the 448 firms using AI in any form, 64% name greater cost predictability as a benefit and 17% name reduced rework. The questions follow AI from estimating and design through the handoff to the field, and then ask what stops firms from scaling it and whom they can hire to run it.

Firms placed themselves on a five-step scale, and 28% landed in the top two

The survey tests no product. Respondents work full time at AEC firms, at manager level or above, with authority or influence over technology decisions. The 750 US answers come from a wider study of 1,100. Each firm placed itself on a five-point adoption scale.

"In production" is Bluebeam's grouping of the top two rows, 7% and 21%. Add the 32% piloting and 60% of firms have started with AI in some form. (The five rows add to 101% from rounding.)

Most figures below come from one of three groups of respondents:

1. 750All 750 firms answered the adoption question.
2. 448The 448 firms using AI, pilots included, answered the questions on where they use it, what it delivers and what blocks scaling.
3. 210The 210 firms past the pilot stage answered what got them there and what they saved.

Firms using AI credit it with cost predictability at 64% and less rework at 17%

Among firms using AI, the most common uses are office and preconstruction work: cost estimation and design and modeling at 69% each, project planning at 63% and document management at 60%.

Bluebeam groups the top three benefits as ways of knowing about a problem sooner. Reduced rework ranks 11th of 12. Bluebeam's reading is that AI sits in estimating, design and planning, while rework happens in the field, where the people who could stop it have the least access to the systems that flagged it.

The report puts the direct cost of rework near 5% of total construction cost, citing Construction Industry Institute research and a 2009 study by Hwang, Thomas, Haas and Caldas, and it adds that those studies lean toward industrial capital projects. Bluebeam CEO Usman Shuja says in the report that he has watched a model flag a clash three weeks early and seen the same clash get built anyway.

“Prediction is a data problem, and we have largely won it.”

Resistance to change is named by 27% of piloting firms and 17% of scaled firms

Cost is named by exactly half of each group, so it does not separate the firms that scaled from the ones that stalled. The press release gives different figures for some rows, 22% for resistance to change and 18% for security, because it pools both groups. The arithmetic checks out:

1. 27% of 238 piloting firms is about 64 firms, and 17% of 210 scaled firms is about 36.
2. That is 100 of 448 firms, or 22%.

The same weighting turns 15% and 22% on security into 18%, and 3% and 0% on trust into the 2% the release quotes.

Trust shows up twice in the survey. Only 2% call a lack of trust in outputs a barrier, while 20% of scaled firms list trust in AI outputs as something that carried them to production. The barrier question and the success question ask about different things, so a firm can count trust as a help without ever having found it missing.

Integration with existing systems carried 47% of scaled firms to production

Integration with existing systems leads at 47%, and a clear return on investment sits at 12%. Bluebeam itself calls this question the weakest evidence in the study, since firms describe their own success after the fact. The use pattern lines up with it: 41% of firms using AI use it mainly to connect data across tools they already own, 37% to automate tasks within individual tools and 23% to replace several tools with one platform.

Among the 210 firms in production, 40% estimate AI savings above $500,000 and another 31% between $100,000 and $500,000. The period and the baseline behind those estimates are not part of the published report.

Digital tools proficiency is the most sought skill at 93% and the hardest to find at 77%

Digital tools proficiency is both the most sought skill, at 93%, and the hardest to find, at 77%. AI knowledge is second-hardest at 59%. Only 16% of firms report no labor or skills shortage, and 82% of all respondents say shortages limit their ability to deliver projects to some degree. Among firms reporting a shortage, 74% name more work for existing employees and 49% name delayed project timelines. (Bluebeam's hiring chart lists field and trade experience on two rows with different values, so this table leaves that capability out.)

Availability and cost

The full US report is a free page on Bluebeam's site. This year's study covered three countries, reported as two separate markets, and this page is the US edition. Construction Briefing covered the US findings on November 2.