Construction leaders evaluating AI in construction often start by asking how much time it will save. They want to know if it can analyze bids faster, simplify drawings management, identify unusual payroll activity, or help finance teams review project performance.
These questions are important, but they reflect the same function-by-function approach that has shaped construction technology investments for decades.
As AI becomes part of everyday construction workflows, leaders should look beyond the time it saves within a specific function and consider whether it helps teams understand how decisions made during preconstruction, project delivery, workforce management, and finance affect each other.
At Sage, we see the best opportunity where operational and financial data come together, giving AI the context to help teams understand not just what’s happening, but why it’s happening and what it could mean for the project.
How is AI used in construction?
AI is used in construction through estimating, project management, document review, workforce management and financial forecasting. It can help teams analyze bids, find project information, identify unusual cost or labor activities, and review project performance more efficiently.
The financial performance of a project begins long before finance sees it
Consider a subcontractor bid that is well below the expected range. Although flagging an outlier highlights a potential problem, further analysis is required to determine whether the contractor achieved real savings or the subcontractor did not capture the full scope of the project in its bid. This requires a comparison with expected prices, similar projects and the subcontractor’s past performance.
Once work begins, locating a drawing more quickly has value, but teams still need to know they’re working from the current revision and understand what has changed. A review can affect the field activities, labor requirements, schedule and cost of the project.
Payroll can then identify an unusual increase in hours, while project information shows whether teams are responding to revised work, schedule pressure, or an activity taking longer than estimated. Finance can calculate the effect on the forecast, but deciding what to do requires understanding the cause.
When margin pressure appears in an updated forecast, the underlying problem may have started with an estimating assumption, a scope problem, a drawing revision, or a changing work requirement. Identifying a problem and understanding what caused it are two different things.
How does connected project data improve decision making?
Connected project data helps construction teams understand how changes in one part of a project affect another. When estimating, schedule, labor, cost, and financial information can be considered together, teams can identify risks earlier, understand what’s driving performance, and respond with more confidence.
When project developments are reviewed separately, contractors may still need to compare reports, talk to colleagues and retrieve decisions through spreadsheets, emails and separate systems to understand what has changed.
An AI tool can automate work within a department without necessarily helping a contractor understand why a project is going off plan or how to respond.
Estimate assumptions should be incorporated into post-award budgets and commitments, while drawing and schedule changes should be considered alongside activity and labor cost. When finance investigates a margin change, the team should be able to review the project activity that preceded it without reconstructing the job history from disconnected records.
Construction ACT experienced this challenge when estimating and setting up work were handled separately. After connecting these processes with Intact Sage Constructionestimates made in project creation and teams gained a more consistent view of financial and project information. Chief executive Joe Murray described the result as supporting the business “from initial leadership to project completion”.
How should construction leaders evaluate AI?
Construction leaders should evaluate AI by asking whether it can connect the right project context, reveal relevant operational and financial information, and help teams act before problems impact the bottom line. The goal is not simply faster completion of tasks, but more informed action throughout the project life cycle.
Can a low bid be evaluated based on expected price and past performance? Can a drawing review be considered along with its schedule and job implications? Can an overtime variance be reviewed in relation to current field activity and the project forecast? Can a margin problem be traced back to the assumptions and changes that contributed to it?
The construction industry already has technology that describes individual parts of a project. At Sage, we believe the opportunity for AI in construction is connecting these parts into a complete project story, helping teams understand how project decisions affect outcomes, identify risks earlier, and act while there’s still time to influence the outcome.
Julie Adams is Senior Vice President of Construction, Product at Sage. Based on a deep understanding of customer needs, she and her team define product strategy and deliver market-leading solutions that elegantly solve complex business requirements through technology. Julie has extensive experience building high-performance teams and has held various product leadership positions for cloud applications at large enterprises as well as smaller startups.
