The construction industry is struggling to adopt AI. Estimating agents, project scheduling optimization, predictive risk analysis—the tools multiply every week, and so does the pressure to implement them before a competitor does.
According to the Associated General Contractors of America’s (AGC) 2026 Construction Hiring and Business Outlook, 61% of respondents said their companies were using AI or planned to increase investment in it, compared to 44% in 2025.
Growth like this makes adopting AI feel less like a choice and more like a necessity, but hardly anyone stops to ask: Is the data feeding these AI tools accurate, current and connected?
Barry Weber, a partner at Eide Bailly, a top 10 construction CPA firm, has spent years watching what happens when contractors rely on generic tools and struggle with data accuracy.
“The most common problem I see with people using generic accounting software is that costs are all over the place,” Weber said of contractors his company advises before moving to construction-specific systems.
Weber has seen the cost of small jobs and change order errors swing profitability up to six figures — errors that are not fully detected until the project is closed. Give this same data to the AI and the model won’t catch the errors either. It will only produce a safe forecast based on numbers that were already wrong.
AI adoption is moving faster than fundamentals
The adoption of AI in construction is already reshaping the way companies bid, schedule and manage risk, with competitive pressure, margin protection and risk management cited as key drivers.
This urgency is understandable. Commercial construction net profit margins are thin to begin with: just 3% to 7% on average, according to the Construction Financial Management Association (CFMA).
That doesn’t leave much room to absorb a costly miscalculation, whether by a human or AI.
The real risk is not the AI. It’s what feeds it
AI tools amplify the data they provide with predictions and analytics based entirely on information they pulled from existing systems or spreadsheets.
When that data is reliable and up-to-date, the insights produced by AI are truly useful. When data is out-of-date, incomplete, or separated across disconnected platforms or spreadsheets, AI doesn’t correct it. Instead, it produces a safe, well-formed, but incorrect response.
If your initial project estimate was created from inaccurate historical data, an AI estimating tool will not catch the error. It will just produce a number that is sure to be wrong in the same way that the last one was.
When change orders are not tracked or billed as they happen, scope variation is not managed. Revenue tied to that work is lost or never billed, and any AI-created cash flow projections are left forecasting numbers that were never right to begin with.
When job cost data is entered days or weeks late, all dashboards built on top of it are already out of date by the time it is loaded.
According to a recent survey, 37% of respondents failed to meet budget and/or schedule goals due to ineffective risk management, and only half of project owners’ projects met completion deadlines. When AI is fed outdated, disconnected, or incomplete data, it can produce a more confident forecast, but the numbers don’t improve.
Provide the AI with current and accurate data and these issues will be easier to spot.
Current labor cost data means that an estimate is made of what things actually cost today. Change orders entered and billed as they happen give an AI tool a clear, current view of scope, so project changes are flagged instead of increasing and eroding profit margins.
The real competitive advantage is not the speed of AI adoption
The contractors those who win with AI will not necessarily be the first adopters – they will be the ones to put systems in place to collect accurate, current and connected financial data before incorporating AI.
To get the most out of AI, contractors need a system that offers:
- Real-time job costs
- Reliable financial reports
- Accurate payroll data
- Standardized billing
- Updated change order management
- Consistent data entry SOPs that ensure all team members record information the same way
- Accountability structures that enforce these SOPs so that the data coming in reflects what is happening in the field
That’s the shift Weber has seen play out with his own clients. Once job costing, invoicing and budgeting live in one connected system instead of scattered across generic tools, his company has documented an 80% reduction in accounting errors, and forecasting that ultimately holds. For Weber, that level of accuracy starts with having all financial data connected in one place.
“This information is only accessible because of construction-specific accounting software, which tracks all of these budgets,” he said.
That same visibility—accurate, connected data that a CPA can trust—is exactly what an AI tool needs to be helpful rather than relied upon..
How AI works with reliable data
Once the AI receives reliable data (from similar previous projects and current active work), it can begin to build reliable insights that enable faster and better decisions.
An AI-powered analytics dashboard that works with current and accurate job cost data can identify cost overruns before they happen and project cash flow across multiple jobs in seconds. This gives you the ability to adjust to trends instantly instead of waiting for the close.
Before investing in AI, first fix the data
The instinct to adopt AI quickly makes sense when the pressure to keep pace with competitors is real and the margins leave little room for error. But speed without reliable data creates no advantage: it produces bad decisions faster and with enough confidence to make them harder to question.
The way forward starts before AI enters the picture: install a construction-specific accounting system, keep it up-to-date and ensure all teams are working with the same data. AI will be a powerful differentiator once this structure exists.
AI will not fix bad data. It will only make the cost of ignoring it more expensive.
To learn more about how a construction-specific accounting solution like FOUNDATION job cost accounting software can help you create the reliable financial data you need to get the most out of AI, visit foundationsoft.com.
