A new survey polling 250 engineering leaders at US and European manufacturing companies has discovered 95% believe it is either critically important or important for design teams to fully adopt AI within the next 12 to 24 months. The survey, commissioned by CoLab, spoke to engineering leaders working across the automotive, consumer hardware, heavy machinery, industrial equipment, and medical device sectors, between 1,000 to 10,000 employees.
100% of respondents said that AI would speed up design review times, and answers indicated that reviews could be conducted nearly three times as fast (2.8x). Automating repetitive design checks will be key to accelerating review times, with respondents estimating that nearly three-quarters (73%) of drawing reviews could be automated. This is crucial given the sheer scale of design reviews, with the survey revealing 70% of engineering teams had reviewed between 30,000 to over 50,000 drawings globally, across their organizations, in the last twelve months.
By using AI, design teams have the opportunity to not only increase the speed, but also the quality of design reviews. 95.6% of engineering leaders stated that following company design standards was either critically important or important. But existing processes are ineffective at ensuring these standards are consistently applied: the survey revealed that only 55% of company design standards are documented, current, and frequently used.
“There were a few instances where we had created a standard and, a few years later, I noticed people not even knowing the standard existed,” said David Sellers, Senior Director of Engineering at Hoshizaki America, a manufacturer of ice and refrigeration products for the food service industry. Hoshizaki’s engineering team is working with CoLab to digitise design reviews, capture institutional knowledge, and use AI to flag when a technical decision should leverage reference material.
“Only about half of company standards are documented, up to date, and consistently referenced today. AutoReview closes that gap – it pulls directly from a company’s own rules, whether they live in a PDF, Excel sheet, or SharePoint folder, and checks designs against those standards automatically,” added Adam Keating, Co-Founder and CEO of CoLab. “Now, we’re seeing teams start to be motivated to document and update standards, because they know they’ll actually get used.”
While there is strong executive-level support for AI adoption, with no respondents choosing this as a barrier, engineering leaders looking to adopt AI face a range of challenges. For large enterprises, where data is already organised through product lifecycle management (PLM) systems, the challenge lies in integrating with these systems securely.
“We’ve invested heavily in out-of-the-box integrations with Windchill, Teamcenter, and Dassault 3DEXPERIENCE to solve this challenge for enterprise customers,” said Keating. “With AutoReview built on top of CoLab’s platform, these integrations become even more powerful, pulling your PLM data directly into AI-driven design reviews without adding risk or complexity.”
Smaller companies are concerned that data is not sufficiently organised for AI to be useful.
“Spending months on cleanup projects defeats the purpose of productivity gains. That’s why we’ve designed AutoReview to work with whatever you have, in whatever format it’s in,” said Keating. “You can upload your standards and guidelines as-is, and the AI will ingest and reference them. We also plan to use unstructured data uploads to suggest custom design review checklists. In other words, we’re using AI not just to review your designs, but to make previously unusable data useful.”
One of the major challenges flagged by nearly 20% (19.6%) of engineering leaders is change management. “When it comes to AI in engineering, change management isn’t just about learning new tools — it’s about trust,” Keating explained. “AutoReview isn’t replacing engineers; it’s giving them instant access to their organization’s historical technical know-how so they can make more informed decisions. The AI handles the repeatable checks, the engineer makes the judgment calls. We think that’s the sweet spot for both performance and adoption.
“AutoReview isn’t trying to replace the decisions being made, it leaves the engineer to be an engineer and do what they are trained to do. It will help engineers focus their time where it’s really needed.”
Despite these challenges, almost every engineering leader (96%) plans to adopt 2D AI drawing reviews in the next 1–2 years, with half moving in the next six months. CoLab launched AutoReview, the first enterprise-ready AI system that automatically reviews 2D drawings and 3D models, in June 2025. The AI tool delivers immediate value by catching errors, missing specifications, and ambiguous notes on in-progress drawings during new product development — preventing costly downstream quality issues.
