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- Focus AI efforts on back-office operations and margin protection, where it provides the most measurable ROI.
- Leverage AI’s strengths in document intelligence, language analysis, and pattern detection to catch errors and prevent revenue leakage.
- Prioritize data hygiene and keep humans in the loop, ensuring AI implementations are driven by specific financial outcomes rather than technology for its own sake.
This is the first in a four-part series on the use of AI in the construction industry, featuring Boomi partner Eide Bailly Technology Consulting, a Boomi partner and business advisory firm specializing in the implementation, customization, and integration of leading ERP, CRM, and cloud technologies.
Where It All Started
ChatGPT was released in November 2022. People thought it was interesting. You could do some funny stuff with it, like create a picture of George Washington crossing the Delaware in the style of Picasso. But no one really recognized its potential business value.
“Back then, among our customers, there was curiosity but zero appetite to spend money to implement it with their businesses,” says Nick Mortensen, Principal at Eide Bailly.
By contrast, today, the firm Gradually AI tracks 157 LLMs from 23 providers, 98 of which are proprietary and 59 are openly available. And the focus has evolved from generative AI to agentic AI, or AI that mixes the two.
AI’s Relevance in Construction Today
There’s a version of the AI conversation that construction executives are tired of hearing. It involves autonomous equipment, computer vision on the jobsite, and robots doing things humans currently do with their hands. It’s interesting. But it’s also largely irrelevant to your P&L right now.
The AI that’s generating real, measurable return in construction doesn’t have a camera or a mechanical arm. It reads documents. It flags anomalies. It catches the things your team doesn’t have time to catch. And in an industry where margins routinely run between 2% and 5%, those things add up fast.
The Real Problem Isn’t On the Jobsite
Every experienced construction CFO already knows that you can execute a project nearly perfectly in the field and still lose money. Delays in billing, missed change orders, duplicate payments, and miscoded labor don’t announce themselves. They accumulate quietly across hundreds of transactions, buried in the documentation and workflow gaps that no team has the bandwidth to chase down manually.
That’s where AI earns its keep. Not on the jobsite, but in the back office. And the gap between what AI is being marketed as and what it actually does well today is worth understanding before your organization makes any investment decisions.
AI in Construction Finance
If you’re the CFO, the value of AI is in margin protection. It’s about whether the leakage it prevents justifies the investment. Usually, the math is straightforward once you quantify what’s currently slipping through — and that makes it an easy win.
“Finance is the low-hanging fruit of AI in construction, as it is in many businesses, because it’s very easy to get a return that’s measurable,” Mortensen says.
Here are three ways AI is delivering real outcomes for construction finance teams right now:
1. Document Intelligence
Construction is one of the most document-intensive industries in existence. Contracts, subcontracts, pay applications, lien waivers, change orders, invoices. The list goes on, and the volume is staggering, as is the cost of processing it manually. AI can read, classify, extract, and route these documents with a speed and consistency no human team can match at scale. The downstream benefits include faster billing cycles, fewer errors, and a reliable audit trail.
2. Language-based AI
Large language models (LLMs) are well-suited to construction workflows involving unstructured text such as emails, RFIs, meeting notes, and project logs. AI can monitor communications for change order triggers, flag potential disputes before they escalate, and surface relevant contract language in seconds rather than hours. For project teams managing dozens of contracts simultaneously, this is significant.
3. Pattern and Anomaly Detection
This is arguably the highest-value, near-term application for construction finance. AI can analyze transaction data at a scale and speed that makes human review look like a rounding error. Duplicate payments, billing inconsistencies, cost coding errors, and budget variances that would otherwise slip through until month-end or even later can be flagged in real time. This is a tangible way to prevent revenue leakage.
Beyond Cost Savings
Mortensen says there is a limit to how much cost savings you can gain by implementing AI. But there’s not necessarily an upper limit on how much you can increase revenue by improving a process with AI — even if revenue is only an indirect goal.
If you’re the COO, this is about reducing friction across workflows that touch multiple teams, systems, and external parties. Fewer manual handoffs, fewer errors, faster cycles.
If you’re the CIO, this is about building an adaptable technology layer. One that can connect your existing systems, ingest new data sources, and scale without requiring a rip-and-replace every time the business evolves.
“We have a construction company that built an AI model that analyzes their properties and their performance,” Mortensen says. “When looking for new lots to buy, they look at the lots they’re considering and compare them with lots in the portfolio having similar characteristics. The model gives them the best data-backed bets to make on lots with the highest likelihood of success. It would take a team of analysts forever to churn through that data.”
AI Is Not a Replacement for Humans
Before your organization builds an AI business case, it’s worth being clear about what AI cannot do. At least not yet, and not without the right foundation.
AI is not a replacement for your finance team, or operations, or IT. The highest-value AI implementations in construction keep humans in the loop (HITL). AI handles volume and pattern recognition. Humans handle judgment, relationships, and exceptions. Organizations that treat AI as headcount reduction tend to underinvest in governance and oversight — and pay for it later.
And don’t make the mistake of thinking that AI is a fix for poor ERP discipline. It’s not. If your data is fragmented, inconsistently coded, or siloed across systems that don’t communicate, AI will accelerate the chaos rather than resolve it. Data hygiene isn’t a prerequisite that can be deferred. It’s the foundation on which everything else runs. Ignore it at your peril.
“The emergence of AI highlighted just how bad data integration and data hygiene were in many organizations,” Mortensen says. “A proper integration strategy should be to build the plumbing that moves data throughout your entire application ecosystem. So, every workflow, every report, and every automation has the data it needs when it needs it.”
Eide Bailly + Boomi for AI
For Eide Bailly customers, Boomi provides the resilient, connected, and active data foundation that’s vital for infrastructure to be agentic AI-ready. But giving an agent unfettered access to systems of record is overwhelming. Without context, that much information causes AI to hallucinate. Instead, Boomi offers the ability to manage and govern AI agents through Boomi Agentstudio, and discover, create, and monitor MCP servers that connect to systems of record and gather highly precise data in real time.
The Boomi Enterprise Platform can provide deterministic process flows wrapped with an MCP layer. So, an agent can call an MCP server that gets precisely the right information from a system of record in real time and serves it in a way that is more efficient and more accurate for the agent while consuming fewer tokens.
Thoughtful Planning Is Key To Success Metrics
The use cases are real. The ROI is demonstrable. But the firms seeing results aren’t the ones that started with the technology. They’re the ones that started with the outcome they needed to achieve.
“I would say six out of 10 AI ideas that customers come up with end up being just regular workflows,” says Mortensen. “Trying to shove AI in just so you can say you used AI doesn’t help anybody. Picking the right business problem where AI has something to add, that’s a whole different story.”
If you’re not sure where AI fits in your construction company’s operations, start with outcomes. Eide Bailly works with construction firms to assess where AI can create a measurable financial impact, and what it takes to get there.
Contact our team of Boomi experts to discuss how Eide Bailly and Boomi can help your organization.