How AI can help construction estimating

By

Hugh Seaton

and Kristen Frisa

Last Updated Apr 7, 2026

By

Hugh Seaton

and Kristen Frisa

Construction estimation requires a very particular skill set involving deep knowledge of the construction industry and an understanding of what it takes to complete a successful project.

Although no technology can replace the creativity, problem-solving, previous experiences, and analysis that a human estimator brings to a project, artificial intelligence (AI) can enhance construction estimating by automating repetitive manual processes and enhancing estimation accuracy, making it easier for estimators to generate precise cost estimates.

This article discusses the importance of efficient and accurate cost estimation on construction projects, and how AI can team up with human estimators to improve the quality of construction estimates.

Aiding humans — not replacing them

Nothing can replace the years of experience humans provide as part of the estimation process. Human estimators bring critical thinking and analysis based on many past projects.

AI can contribute to this project by doing much of the legwork involved in finding and sorting information from project plans, specifications, contracts, invoices, bids and market trends, so the human estimator has a base of data to work from. 

Estimators use several steps and a variety of data sets to determine all the costs involved in completing a construction project, helping contracting teams to bid strategically and set appropriate budgets. AI tools can pair with an estimator to provide specificity in the numbers and more quantitatively simulate how different scenarios might go.

People talk about having a human in the loop to make a decision at the end, but I am uncomfortable with that. How do they even make a decision at the end when they weren’t part of the rest of the process? Someone who’s been estimating for a long time adds value to the whole process, not just the end of it.

Hugh Seaton

CEO

The Link.ai

Machine learning models can then work to simulate a project based on the plans and specs to identify patterns and relationships that could impact construction expenses — so estimators can create better estimates, and even identify projects that may not be profitable.

Use cases for AI in construction estimating

Estimators can capitalize on AI’s abilities for more efficient and accurate estimates. Here are some of the ways it can be used.

Simulations

AI can run simulations to predict project outcomes under various scenarios so estimators can visualize different project trajectories. Using simulations, estimators can better understand potential risks and make informed decisions.

Instant estimates

AI algorithms can quickly process data to generate instant estimates. Rapid calculations can give estimators the information they need to make faster decisions and respond quickly to project changes.

Task automation

AI automates repetitive tasks like data entry, cost calculation, and document generation, freeing up estimators to focus on more strategic aspects of the project. Decreasing the time spent on routine tasks while improving quality standards improves the overall efficiency of the estimating process.

Managing labor shortages

Greater efficiency in the estimation process can help teams operate through labor shortages. First, the estimation process itself is faster, meaning estimation professionals can make the most of the time they have.

Further, AI can help analyze labor market trends alongside project demands to help predict and avoid labor shortages that would stall project progress.

Free AI in Construction Course with Hugh Seaton

Start learning today with industry expert Hugh Seaton and discover how AI can boost efficiency, reduce risk, and transform your projects.

Enroll for Free

Benefits of estimating using AI

AI has the potential to improve the estimation process for construction professionals by enabling quicker and more data-based decisions.

More accurate data analytics

AI has the power to process an incredible amount of information in a very short time frame — including data from past projects, up-to-date materials price databases and supplier price lists, local labor rate information, environmental data, and more — leading to more accurate insights and helping estimators make better-informed decisions.

Data-driven cost predictions

Rather than relying on recollections or dated information, AI can quickly locate data to produce an accurate basis for information and analysis.

Using machine learning algorithms, AI analyzes the collected data to identify patterns, trends and correlations that impact construction costs.

Streamlined workflows

AI can automate repetitive tasks like data entry and cost calculations, so these processes are faster and are less likely to suffer from human error. AI can integrate a variety of data sources to make workflows more efficient and allow estimators to focus more on strategic decision-making.

Further, AI can help source materials that will fit into the budget. Instead of having team members search and call for options, the AI will be able to search data bases to find available materials so a human can follow up effectively.

Tapping into new areas of work

One of AI’s most powerful capabilities may be in helping estimators to break into new areas of work. While they may be highly skilled at estimating high-intensity development projects, for instance, they may be less familiar with all of the details that go into data center construction.

 AI can help bridge the gap so estimators can quickly and accurately estimate new types of projects.

The future of AI in construction estimating

As AI continues to develop and evolve, estimators can benefit from pairing with the technology as a team, using it to run some numbers, explore different scenarios or provide some expertise in a new area of business.

AI in construction needs to work with the experience and expertise of a construction estimator, not instead of one. It does a great job of combing through and analyzing large amounts of information, but it needs to be read by someone with experience. Asking an AI chatbot for an answer to a complex problem and trusting the answer without background knowledge could lead to accepting an incomplete answer.

Written by

Hugh Seaton

CEO | The Link.ai

Hugh is CEO of The Link.ai, an AI consulting and software company for the construction industry. Prior to The Link.ai, Hugh served as a general manager at the Construction Specifications Institute (CSI). His career has spanned 30 years in technology, at Sony, AOL, Philips Electronics and Google, among others. Hugh is author of The Construction Technology Handbook, host of the Constructed Futures Podcast, and the AI in Construction Youtube channel, and Procore’s Data in Construction e-learning module. Hugh lives in Austin, Texas with his dog, Bob.

View profile

Kristen Frisa

Contributing Writer | Procore

116 articles

Kristen Frisa is a contributing writer for Procore. She also contributes to a variety of industry publications as a freelance writer focused on finance and construction technology. Kristen holds a Bachelor of Arts in Philosophy and History from Western University, with a post-graduate certificate in journalism from Sheridan College. She lives in Ontario, Canada.

View profile