Spending was up on a monthly basis in 8 of 16 nonresidential subcategories. Both public and private nonresidential spending were up 0.1% in June. Private nonresidential construction spending was down nearly 5% from a year ago.

“Through April 2025, private nonresidential construction spending ascended to $806.1 billion on a seasonally adjusted annual rate basis, an all-time high,” said ABC Chief Economist Anirban Basu. “Since then, that figure has expanded only three times over the past 14 months.

“Despite an ongoing data center construction boom, private nonresidential construction spending has declined to a seasonally adjusted annual rate of $745.3 billion since the April 2025 peak, which translates into a decline exceeding 7%,” said Basu. “Tellingly, private nonresidential construction spending excluding data centers fell 0.6% in June 2026 and is down 7.9% year over year.

“Meanwhile, data center construction was up 7% in June and up 46% from a year ago. Contractors working on data centers continue to benefit from this momentum. According to ABC’s latest Construction Backlog Indicator, the 13% of ABC members under contract to work on data centers have significantly higher backlog (11.0 months) than the 87% that are not (8.5 months).”

Visit abc.org/economics for the Construction Backlog Indicator and Construction Confidence Index, plus analysis of spending, employment, job openings and the Producer Price Index.

Associated Builders and Contractors is a national construction industry trade association established in 1950 with 67 chapters and 24,000 members. Founded on the merit shop philosophy, ABC helps members offer a robust employee value proposition, develop people, win work and deliver that work safely, ethically and profitably for the betterment of the communities in which ABC and its members work. Visit us at abc.org. 

The post June Nonresidential Construction Spending Up on Strength of Data Centers first appeared on Construction Executive.

Texas-based Central Builders was established in 1989 and specializes in large-scale remodels, expansions and ground-up new construction of supermarkets and grocery distribution facilities. As the company expanded, on-time project delivery and profitability were increasingly threatened by disconnected workflows and data silos that delayed job-cost updates, required duplicate data entry and limited insight into project performance.

The company invested in a connected construction ecosystem that aligns project management, financial operations and reporting to ensure that all teams work from a single source of truth across projects. Time and again, this decision has proven to be critical to project success.

The Challenge: Building on a 30,000-Square-Foot Pond

Central Builders has completed well over $500 million in grocery store projects over the past five years. One was a new $10-million Sprouts grocery store built in 2025 in an unlikely place: directly on top of a 30,000-square-foot pond. The challenging location was only the beginning of the complexities that tested the company’s capabilities and illustrated the value of the investment in connected technology. Persistent rain, the coordination of more than 40 subcontractors and a simultaneous Sprouts project in North Texas left zero margin for error.

Before vertical construction could begin, crews had to demuck the site, excavate unstable material and rebuild the pad with engineered fill. Central Builders completed the site preparation 10 days ahead of schedule, an advantage that proved vital when the weather turned.

Moisture affected nearly every downstream activity. Dry weather windows opened and closed quickly, and sequencing often shifted by the hour. Coordinating crews, materials and inspections under these conditions required clear communication and real-time visibility into job progress and costs.

Despite environmental and logistical challenges, the Sprouts project reached key milestones ahead of schedule. Steel erection and decking were finished five days ahead of plan, and the project closed on time and on budget.

Connecting the Field and the Office

Central Builders relies on a cohesive technology ecosystem built largely around Trimble solutions to bring people, data and workflows together in a shared environment.

Field teams utilize Trimble ProjectSight to manage RFIs, submittals and drawing updates. “With ProjectSight, everyone has real-time access to the most current information,” says Shellie Gregg, financial controller for Central Builders. “Shared visibility reduces rework and keeps our teams aligned as schedules shift and as documents are updated or added.”

In the office, the Trimble Vista financial management solution serves as the system of record for accounting, payroll, job costing and subcontractor billing. With field updates flowing directly into financial reporting, manual data entry has decreased by 90%. “Job-cost data reflects exactly what is happening on the jobsite,” says Gregg. “Plus, visibility into field updates enables our teams to closely track performance and respond quickly when conditions change.”

Gregg credits improved job-costing visibility with increasing field-budget forecasting accuracy by more than 30%, helping project managers hit margin targets.

Driving Efficiency and Cash Flow

The investment in connected construction didn’t take long to pay off. “Within eight months, we realized a return on investment,” says Gregg. “Payroll savings, reduced administrative overhead and better, faster operational decision-making enabled by real-time data collectively transformed our business.” 

The impact of a connected construction approach is visible across Central Builders’ operations:

• More Timely Job Costing: Integrated project and financial management systems bridged the field-to-office divide, allowing managers to align job cost with actuals in near real time.
• Faster Financial Reporting Cycles: Live dashboards connected to project financial data shortened monthly close cycles from 12 days to five.
• Labor Transparency: With real-time visibility into labor through phase-level time tracking and automated burden calculations, teams can assess performance weekly and adjust forecasts before a project drifts off course.
• Streamlined Vendor Management: Automating compliance and shortening approval cycles with Trimble Pay has reduced subcontractor payment processing time from two weeks to less than five days, keeping vendors engaged and materials flowing to the site.

Predictability in an Unpredictable Environment

Technology adoption has not only improved workflows at Central Builders but also changed how people work across the company and how they feel about their jobs.

“In a fast-paced construction environment where job costing, documentation and approvals can grind morale into dust, connected technology has become the backbone of clarity, speed and sanity,” Gregg concludes.

Project managers now spend fewer hours reconciling numbers and more time directing work. Predictability has reduced burnout and improved morale. Late nights reconciling numbers or “guessing” when trades should be on site have decreased dramatically, and office staff report a 35% decrease in rework caused by outdated or missing documentation.

These outcomes at Central Builders demonstrate the power of connected construction workflows for responding quickly, sharing data across the organization and making decisions based on reliable information rather than assumptions.

SEE ALSO: POWERING PROFITABILITY WITH CONNECTED CONSTRUCTION WORKFLOWS

The post Building on Water:  How Central Builders Leveraged Connected Construction to Conquer a Complex Jobsite first appeared on Construction Executive.

In 2025, Buildcheck officially launched after raising $5.9 million in seed funding—with help from Uncork Capital, Peterson Ventures, XFund, and founders and senior executives at OpenAI, Opendoor, CBRE, Zillow and more.

Michalatos sat down with Construction Executive to discuss the rigorous creative and prototyping process for this product, how he expects the technology to evolve over the next decade, as well as many details in between.

What type of technology is Buildcheck?

Buildcheck is an AI-powered design review platform. We’ve trained computer vision models to read construction drawings—the language of construction—so we can catch coordination errors, missing scope and cross-discipline conflicts before they turn into RFIs, change orders or city comments. We work with real estate developers, general contractors and design firms, and our customers typically see a 10x to 40x return on what they spend with us.

What was the impetus for creating Buildcheck?

The impetus is personal. I grew up in a construction family in Vancouver—my father built single-family homes for decades—and I spent my own career on the owner, general contractor and design sides: Stantec, Honeywell, EllisDon on hospital design-builds and QuadReal on mixed-use development. Across every one of those roles, I kept seeing the same pattern: small inconsistencies scattered across hundreds of sheets that nobody caught until steel was going up or concrete was being poured. Globally, that’s a $200-billion problem. When I stepped back, it was obvious: Construction doesn’t run on contracts or emails, it runs on drawings. Until AI could actually read the lines on a sheet, it was going to stay peripheral to real construction risk. That’s what Buildcheck is built to solve.

Who is Buildcheck’s main type of client within construction?

Primarily general contractors and real estate developers, with a growing number of architecture and engineering firms using us as an internal QA/QC layer. Our customers include EllisDon, AvalonBay, Novo Construction, Dempsey Construction and many more.

The common thread is that they’re all managing design risk—not just building. That’s a bigger group than it used to be. Public infrastructure is increasingly delivered through design-build and alliance contracts, which push design responsibility onto contractors. Mid-market developers are engaging general contractors earlier through preconstruction services or GMP structures. Architects are carrying more professional liability exposure on bigger, more complex drawing sets. All of them share the same underlying need: find the coordination gaps before they get priced into a change order.

We tend to fit best with firms that have already decided design coordination is a bottleneck. They usually know exactly where it hurts; our job is to show them that AI can now do something about it.

Do you work with clients outside of construction?

No, and that’s intentional. Computer vision on construction drawings is a uniquely hard problem—drawings aren’t standardized, symbol sets vary by firm and discipline, and layering conventions shift project to project. Training a model that genuinely understands an MEP sheet versus a structural sheet or civil sheet takes years of labeled data and domain expertise. That depth is the moat, and it only comes from staying focused.

That said, the underlying technology could apply to other drawing-heavy industries—shipbuilding, aerospace manufacturing and certain industrial engineering verticals. For now, the opportunity in construction alone is enormous. The global design-error problem is $200 billion annually and nobody has solved it. We’d rather be the best in the world at one thing than average at several.

Do you still run into problems with designers/companies hesitant to use AI for preconstruction? How do you create buy-in/convince them to get onboard in the first place?

Yes, and I think that skepticism is healthy. There’s a lot of AI-washing in construction tech right now and buyers are right to demand proof.

For our clients, a demo is the starting point, but the real conversation begins when we run their drawings through Buildcheck. In most cases, we come back with dozens to hundreds of flagged issues that their experienced team hadn’t caught. If that first project lands, a companywide rollout tends to follow naturally. We also invite any prospective customers to talk to current customers and hear directly from them, not us.

The other piece is framing. We aren’t replacing labor; we’re enabling your people to do more. Your senior reviewers still make the judgment calls. We just compress the hours of repetitive pattern-matching work—the missing power, the mismatched fire ratings, the clashing service connections—so your people can spend their time on the decisions that actually require expertise. When buyers understand that, the skepticism usually shifts from “will this work?” to “how fast can we roll it out?”

Does this type of tech only apply to the preconstruction process?

Preconstruction is where we start because that’s where the ROI is most obvious. Catching a coordination issue on a sheet costs almost nothing to fix; catching it in the field can cost six figures and weeks of schedule. Front-end planning research from the Construction Industry Institute has consistently shown returns of roughly 10:1 on investment in document quality before construction.

But computer vision on drawings unlocks workflows across the entire project lifecycle, such as shop drawing cross-checks against the IFC set, change-order quantification, automated takeoffs and, eventually, as-built verification. The same underlying models that detect errors today can drive proactive design improvement tomorrow—through real-time coordination feedback as drawings and design optimization evolve.

The long-term vision is that drawings stop being static PDFs and start being structured, machine-readable artifacts. Once that happens, everything downstream—estimating, procurement, coordination, closeout—gets meaningfully faster.

What was the development/prototyping process like for getting this product out the door?

Our process was and continues to be rigorous and disciplined. We’ve spent over three years building proprietary models trained specifically for construction drawings, but also building the user experience around it. Neither of these can be vibecoded because the domain expertise and customer feedback loops take time to establish.

Two things shaped the process. First, we chose quality at every step—from labeling the data and fine-tuning the models to having construction experts verify every AI output before it reaches the customer. Second, our earliest customers did more to shape the user experience than any internal plan ever could have. General contractors and developers willing to give us feedback are how we figured out what reviewers actually want to see first, how to surface severity and how the interface should mirror the way their teams already work.

How has this type of technology evolved since Buildcheck’s inception? Where do you see it going by the next decade?

When we started, most construction AI was optical character recognition, chatbots layered over contract text or basic clash detection inside a BIM model. Useful, but peripheral to the core risk. The shift over the last two years has been toward specialized vision models that can actually interpret 2D drawings—the medium construction still overwhelmingly runs on.

Looking out ten years, I’d expect three things. First, error detection becomes table stakes—every major project will run through automated review the same way it runs through code check today. Second, the tooling moves from reactive to proactive: Rather than flagging problems after a set is issued, AI will provide real-time coordination feedback inside the design-authoring tools as drawings evolve. Third, we’ll start to see genuine design optimization—AI that suggests smaller duct runs, more efficient structural layouts and value engineering moves grounded in both code and constructability.

Is there fear that this type of AI will ‘take people’s jobs’?

It comes up and it deserves an answer. AI isn’t going to replace most construction jobs—it won’t sequence concrete pours, negotiate a subcontract or lead a toolbox talk. Leadership and judgment in construction remain deeply human. And besides, there is a huge backlog of work for the entire industry. We want to do more and technology enables that; we can’t afford to lose people.

What AI removes is the repetitive, pattern-based review work that consumes hours: hunting missing dimensions across 400 sheets, cross-referencing fire ratings, chasing broken callouts. Given the industry’s labor gap and flat productivity, the real risk isn’t AI taking jobs. It’s the industry being unable to deliver enough projects, affordably, because we can’t scale human expertise fast enough. AI is a leverage tool for the people already here.

How has this tech saved money, time, safety, productivity?

Money and time are the easiest to quantify. Design errors and coordination gaps drive an estimated $200 billion in global overages annually. On individual projects, we regularly see six-figure savings and multi-week schedule protection—on one 230-unit multifamily project, over $500,000 in cost avoidance and 27 days of schedule saved. Under conservative assumptions, customers see 10-40x ROI.

Safety is the most underappreciated. The highest-severity inconsistencies we catch are life-safety issues—mismatched fire ratings between disciplines, undersized electrical feeds to fire pumps and missing sprinkler branches. Finding those in the documents, before installation, is meaningfully better than catching them at commissioning.

Do you believe this type of technology is gaining momentum within the industry? Is it helping give AI a friendlier reputation within construction?

Yes, clearly. Recent industry surveys show up to 64% of construction organizations experimenting with AI. Two years ago, the first meeting was about, “Does this work on drawings at all?”

Today it’s about which vendor, what pilot structure, what rollout. That’s a meaningful shift.Construction is actually one of the better industries for AI to land in, because it’s pragmatic. Professionals don’t care about hype—they care about dollars saved, days saved and risk reduced. When they see AI flag a real issue on a real drawing set, skepticism fades quickly. The caveat: Overpromising vendors can set the category back. The industry has a long memory for broken tech promises.

Anything else?

Don’t conflate AI with LLMs. A lot of construction buyers assume ChatGPT-style tools are what AI looks like. Those models are excellent at text—contracts, specs, RFIs—but construction’s highest-value problems are visual: drawings, models, site conditions. The vendors solving those problems are doing specialized computer vision work that looks very different from a chatbot wrapper. When you’re evaluating AI tools, the first question to ask is what the models were actually trained on.

SEE ALSO: SIX AI SOLUTIONS DRIVING PRODUCTIVITY AND PROFITABILITY IN CONSTRUCTION OFFICES

The post A New Vision for AI: Construction Design-Review Platform Lends Extra Eye to Image Analysis first appeared on Construction Executive.

The rapid buildout of data centers has triggered a hiring boom in the construction industry. Spending on data center facilities could reach as much as $7 trillion by 2030, with thousands of data centers currently underway and thousands more to be announced. The increased demand for construction jobs has created a strong pipeline for Gen Z entering the workforce.

With that said, Gen Z does not have hands-on experience like previous generations, and the industry is faced with the challenge of training a new generation in the complex tactical skills of estimating. Historically, knowledge transfer between veterans and newer estimators happened through years of proximity, learning to read drawing sets and price assemblies through repetition and correction. Now, leveraging technology and industry resources is the only way to equip newcomers with the skills needed to support the projected scale of AI infrastructure.

Less than a year ago, the rate of open construction jobs dropped to its lowest point in nearly a decade, thus renewed interest in construction jobs comes at a crucial time for the industry. The future of construction will depend on how effectively decades of institutional knowledge can be transferred from experienced professionals nearing retirement to the newcomers poised to replace them.

A Two-Sided Adoption Challenge

What makes the experience gap difficult to close is that it cuts in two directions, and most discussions of AI in construction address only one of them.

Many veteran estimators have built deep, trade-specific expertise inside legacy estimating platforms. For this group, adopting new AI-enabled tools is less of a skill issue and more so a technology latency issue. In their eyes, the methods they have used for years still work for them, so they are not motivated to learn new platforms. This is a key vulnerability of the profession, because if that group does not adopt new tools, their expertise stays hidden in workflows nobody else can see.

Newer estimators present the opposite risk. Handing an estimator an AI tool early in their career that can answer nearly any question raises the risk that they will rely on it instead of developing their own judgment. Getting answers isn’t the same as closing the experience gap. An estimator needs to learn how to find the right answers independently. The gap has simply been outsourced, which leads to problems when AI inevitably gets something wrong and no one on the team is positioned to catch it.

The industry’s approach to AI in estimating needs to account for both sides of that equation rather than focusing only on newer hires. Construction technology companies need tools that are trained by professionals who already know the trade, capture what is valuable about how they think and then transfer that knowledge to newer estimators in a way that builds skill rather than dependence.

Designing for Adoption and Depth 

Estimating software must satisfy two goals that are somewhat contradictory. It needs to be fast and accurate while answering in a way that provides a clear chain of reasoning that can be verified.

Speed is essential to user experience. A new estimator comparing a four-hour manual training to a twenty-minute AI-assisted one will choose the faster path almost every time, regardless of what’s happening underneath. However, speed without transparency trains estimators to trust outputs they can’t explain, which will lead to further problems down the line. 

The key to longevity is striking a balance; easy enough that a new estimator prefers using it, while preserving the source material and reasoning of legacy platforms. Every output should be traceable the same way a veteran would explain a number to an apprentice standing next to them. The goal should be to teach new estimators skills that are repeatable and train their instincts to identify how professionals arrive at conclusions.

That distinction is what separates a tool that can be widely adopted from one that erodes years of deep trade knowledge. An answer with no source teaches a new estimator nothing they can use again. An answer with a verifiable source teaches the underlying skill every time it is used. Software that can close the knowledge gap adequately prepares new estimators with the skills needed to do the job on their own if the software fails.

A Narrowing Window and Shortening Runway

Contractors, along with the CPAs, attorneys and suppliers who support them, are watching two trends collide at once: a construction labor market suddenly attractive to younger workers and a veteran workforce retiring faster than firms can replace it.

The industry should not see this as a crisis but as a window of opportunity for new talent to interact with veteran estimators before they age out of hands-on work. The data center boom has become an unexpected recruiter for the construction industry, handing the industry a new army of young talent with genuine interest in the work. What happens next is crucial to keeping workers around and keeping alive the legacy these firms have built.

It is critical that firms understand in order to maintain quality employees they need to pivot to strategies other than traditional training alone. For estimating departments specifically, that means the value of AI is not primarily about speed, though faster takeoffs and bids are a real byproduct. The true value is in capturing what departing professionals know before that knowledge leaves with them and putting it into the hands of the estimators arriving right now to take their place.

Ben Coffman is the Senior Vice President of Engineering and Product at STACK Construction Technologies.

Location: Los Angeles, California, United States

The post Closing Construction’s Widening Workforce Experience Gap With AI first appeared on Construction Executive.

The Escalating Threat of Heat Stress in Construction

Heat stress is a serious medical condition that occurs when the body cannot adequately dissipate heat, leading to heat exhaustion and, in severe cases, heat stroke. Heat exhaustion manifests as fatigue, dizziness and excessive sweating, while heat stroke is a life-threatening emergency, potentially resulting in organ failure and death.

Construction sites present unique risk factors, including prolonged direct sun exposure, physically demanding labor and heat-trapping personal protective equipment. According to the Occupational Safety and Health Administration, environmental heat exposure resulted in 999 fatalities from 1992 to 2021. As climate change intensifies heat waves, the urgency of addressing heat stress through effective monitoring and prevention strategies must become a priority for construction professionals.

Proactive Safety: Beyond Traditional Prevention Methods

Traditional heat safety protocols, such as access to water, rest breaks and shade, are essential but often lack real-time, individualized protection for workers. These reactive measures may not address the urgent needs of workers in extreme heat conditions. By leveraging technology, the construction industry can transition from reactive to proactive safety measures for workers.

Now, the industry is also improving hazard mitigation through real-time monitoring. Technologies such as drones and robotics are not new in the sector, but are now employed to identify jobsite risks in real time, enhancing safety and reducing production delays. This existing momentum also presents an opportunity to integrate individual-level safety technologies, providing every worker adequate protection from problems like heat stress.

The New Guard: Wearable Technology for Heat Stress Monitoring

Wearable technology is revolutionizing the way safety officers monitor heat stress on construction sites by providing real-time insights into physiological indicators. These innovative devices enable construction professionals to take proactive measures to protect against heat-related conditions, helping ensure the safety and wellbeing of workers in extreme environments. Below are several types of wearable technologies designed for this purpose.

Biometric Sensors and Smart Patches

Biometric sensors and smart patches stick directly to the skin, continuously tracking vital metrics such as core body temperature, heart rate and sweat rate in real time. These devices use advanced algorithms that analyze physiological data, providing early warnings of potential heat stress before workers themselves even notice symptoms. By promptly alerting individuals and supervisors, these sensors facilitate timely interventions that significantly reduce the risk of serious heat-related incidents.

Smart Hard Hats and Helmets

Smart helmets and hard hats represent another innovative approach to heat stress monitoring. These integrated systems measure the worker’s internal state by tracking body temperature and heart rate and also assess the external environment by gauging ambient temperature and humidity. This dual functionality enables comprehensive monitoring, ensuring that workers remain informed about hazardous working conditions. Real-time data activates alerts, enabling immediate action to protect workers’ health.

Connected Vests and Apparel

Connected vests and smart clothing equipped with embedded sensors offer continuous health monitoring within the construction environment. These garments provide real-time data on physiological indicators, similar to the biometric sensors, but some vests also feature manual or automatically triggered cooling systems. This functionality enhances worker comfort and safety, keeping them cool and maximizing productivity even in extreme temperatures.

From Data to Action: Implementing a Wearable Safety Program

The true value of wearable technology lies not only in the devices themselves, but also in the actionable data they generate and the responses they enable. By implementing a comprehensive wearable safety program, construction stakeholders can harness real-time insights that improve worker safety. A central dashboard becomes an essential tool, enabling site supervisors to monitor the status of all their workers simultaneously.

This dashboard provides alerts when individuals approach critical thresholds, enabling prompt intervention before heat stress escalates to a more severe condition. By adopting a proactive, prioritized, data-driven approach, construction teams can significantly accelerate decision-making, mitigate risks and ensure a safer work environment amidst a culture of accountability and care.

Examples of How Wearable Technology Can Help

Several construction companies have successfully integrated wearable technology into their safety protocols, with NIOSH resources reporting positive feedback on the real-time integrations. A suggested scenario used the following example of the difference the technology can make.

A construction worker’s biometric sensor triggered a rising-heart-rate and core-temperature alert. The worker’s supervisor immediately instructed the employee to take a break at a designated cooling station. This timely intervention helped avert a potential medical emergency.

Additionally, the data collected from scenarios like the above can inform long-term safety planning, such as adjusting work schedules on particularly hot days and identifying workers who may be more susceptible to heat stress.

The Future of the Connected Jobsite

The integration of wearable technology on construction sites promises numerous benefits, including improved worker safety, reduced incident rates, fewer project delays and a stronger safety culture. However, challenges such as securing worker buy-in and addressing data privacy concerns remain, and stakeholders must navigate these thoughtfully. As technology continues evolving, the connected and data-driven jobsite is becoming an increasingly standardized symbol of safety and efficiency within the construction industry.

Embracing advancements in real-time wearable tech and other modern technologies will lead to enhanced protection for workers and a commitment to ongoing safety improvements in the field.

SEE ALSO: ANALYZING THE BENEFITS OF EXOSKELETON USE ON CONSTRUCTION JOBSITES

The post Leveraging Real-Time Wearable Tech to Reduce Heat Stress on Construction Sites first appeared on Construction Executive.

Traditional AI vs. Generative AI

According to the United States Chamber of Commerce, traditional AI is defined as “a subset of artificial intelligence that focuses on performing preset tasks using predetermined algorithms and rules. These AI applications are designed to excel in a single activity or a restricted set of tasks, such as playing chess, diagnosing diseases or translating languages.” Most of us are using traditional AI on an everyday basis when we utilize the Siri function on our iPhones or the Alexa or Google virtual assistants. Indeed, even the filters on your email or phone preventing spam emails or calls from reaching you are forms of conventional AI.

In construction, contractors, suppliers and designers already use traditional AI in troubleshooting technical issues, training, reviewing credit applications or in evaluating a building’s intended use in order to make recommendations for a design or type of material or equipment.

Generative AI differs from traditional in that it emulates human learning and decision-making in order to develop new content. Unlike traditional AI which analyzes existing data, generative AI reuses what it knows to solve new problems. In the construction industry, generative AI is useful in preparing contracts, cost estimates, developing RFPs and scheduling, among other things.

Contract Negotiation and Drafting

Many aspects of a construction contract negotiation can be enhanced by the use of an appropriate AI tool. For example, specialized construction industry AI tools such as Document Crunch and Spellbook can analyze historical negotiation outcomes and provide input as to where the project participant can most benefit from a modification of a contract term. AI can then suggest alternate wording to address the specific issue of concern.

Generative AI tools can likewise be trained on a construction lawyer’s database of contracts and used to efficiently draft new contracts. AI can quickly and efficiently locate and suggest oft-used clauses from previous contracts or other sources. This method can be helpful in promoting consistency across a field of project documents by using standardized wording and by automating repetitive drafting tasks. Using AI in this way serves to reduce human error and reduce hours spent on time-consuming proofreading and cross-checking.

Construction contract drafting is also enhanced when an AI tool is used to identify ambiguous language, conflicts or unfair risk allocation. These methods can assist in avoiding disputes down the road.

Moreover, AI tools can be very effective in drafting individual contract clauses because a user can input prompts for the type of clause they are looking for; the AI tool will then quickly offer intelligent suggestions for contract language that is responsive to and inclusive of the information with which it was provided. For example, a user can request that AI develop a customized payment terms clause that considers that the project is anticipating funding at a particular time or upon a specific event. Using AI to create a first draft to address unique project terms (that is then edited and revised by a human lawyer) is a best practice proven to save costly attorney time.

The better developed the input, the better the result achieved in the output. That is, more detailed and specific parameters provided to the AI tool will result in higher quality output. Instead of asking AI to create a form subcontract, a user should include parameters in the request detailing that they need a form of steel erection subcontract for an a office building project of 50,000 square feet that is being constructed from ground up on an existing slab in a cold weather climate with a six month duration. Utilizing this method will result in an end product that is much more useful.

AI can then be used further to highlight inconsistencies with other contract documents. Because construction projects typically require multiple documents to create the whole of the “contract documents,” AI can provide substantial value in coordinating the contract document set. Caution should be used in relying on AI output, however, because generative AI cannot be trusted to consider unique project features or relationships.

Other contract drafting and negotiating efficiencies come from AI tools that allow real-time drafting collaboration, redlining, digital document execution and identification, and management of edits to conform content.

Contract Administration

AI is also an incredibly useful tool in construction contract administration, and its potential uses are widespread. It can assist in project planning and scheduling using data from past performance, as well as weather analysis and data about the availability of materials to create an efficient and attainable schedule. Coordination of trades using a schedule analysis can be performed by an AI tool. AI can assist in change-order and submittal tracking. It can review potential project risks and plan mitigation strategies in advance. It can analyze project specifications and use them to create realistic cost estimates for use in budgeting and project planning.  It can evaluate images to assess work quality and identify defects or deviations. AI tools can also decipher and summarize key contract terms and answer contract-related questions. Finally, AI can be used to draft and deploy contractually required notices and directives. All of this enhances communication and collaboration among project participants, the recipe for a successful project.

Inherent Dangers of Using Generative AI

Dangers arise when the data provided to the AI tool is incomplete, inconsistent or low-quality, not uncommon in construction projects. Indeed, the typical construction contract relies on data from multiple sources including design documents, site reports, contractor and subcontractor bids and owner requirements; errors and inaccuracies occur regularly. To avoid this risk, robust quality control of the information provided to the AI tool is imperative. Careful review and human judgment remain necessary because AI is not a substitute for human expertise and experience.

Although the output produced by generative AI can be very convincing and accurate, sometimes the information is just wrong. AI should not be used as anything other than as a preliminary resource for information that must be vetted. Its output must be verified using known and established sources. As an example, using generative AI to respond to an RFI is dangerous. AI can invent incorrect details or specifications that facially appear accurate but are technically incorrect. In order to prevent errors like this, human oversight is absolutely essential. In fact, in 2024, the American Society of Civil Engineers issued a policy statement cautioning that AI cannot replace the professional judgment of the human engineer.

While the use of AI in construction contracting may be hampered by obstacles such as lack of cost, lack of data integration, hallucinations and resistance from industry participants, its usefulness has the potential to far outweigh the barriers. Using AI in construction contracting will be driven forward by the anticipated efficiencies, availability of technology and presence of technology-savvy newcomers to the field. The ultimate result—improvement in project performance. As such AI tools are a welcome advancement in construction contracting.

SEE ALSO:

The post The Use of AI in Construction Contracts: Do the Pros Outweigh the Cons? first appeared on Construction Executive.

Lucas, who has held roles ranging from construction administrator and project manager to director of construction solutions, now works with contractors on improving preconstruction, estimating and project management workflows, and Lawrence, who is currently serving as a construction account executive, previously worked as a project engineer with general contractors in the Pacific Northwest and began her career managing painting crews.

Each woman established their careers in the construction industry before advancing into their newfound roles in the construction technology sector in late 2025. Were they expecting to level up when they did? Was this next step even on their radar? Were they content with their careers up to this point? Will they continue to advance beyond these new roles?

Construction Executive sat down with the women to learn more about their journeys—and how those journeys can affect progress for the future of the construction workforce as well as for construction technology.

“We are starting to see more representation of women in all facets of the construction industry,” says Lawrence. She attributes the slow—albeit steady—pace of the gender-shift in construction to “women thinking there’s not a place here for them. But there certainly is.”

How have you worked your way up to your current role?

Danielle Lucas: I actually started out on the operations side and then became a construction administrator. I’ve worked with both an HVAC specialty subcontractor and a general contractor in Florida where I used to live. So, I got a really good ground-level view of what happens on a project and I fell in love with the technology there while also learning the daily reality of RFIs and change orders and contracts. After that, I moved into project management and then finally over to construction technology itself. Before I joined IMAGINiT, I was a director of construction solutions. Today, I’m a construction engagement engineer and I specialize in preconstruction. I get to work closely with firms to improve how they’re approaching their estimating, takeoff, collaboration and construction administration.

Sarah Lawrence: It all started with a desire to gain work experience applicable to any career. I started as a residential exterior house painting intern. I was then recruited by a commercial painting subcontractor, which hired me as a project engineer. I never intended to have a career in construction; I never formally went to school for construction management. I’ve learned everything on the job and through my mentors—from interpreting contract documents to managing projects. Working for the commercial painting company was a great opportunity and I got great experience that set me up for a successful career in commercial construction.

From there I switched to the general contractor side, so I worked with a smaller firm doing 16-week tenant improvements. Then I accepted a role with Balfour Beatty, starting in their preconstruction department and supporting a couple of large projects from there. My role with IMAGINiT has exposed me to how technology is transforming our industry and I’m passionate about driving tech adoption across construction. 

Did you study technology or did you organically work your way up in the tech sphere of construction?

Lucas: I did not go to college and I didn’t study technology—I simply fell in love with it. If you want to learn, there are so many people who will help you do that.

Lawrence: Most of what I’ve learned and have been exposed to has been on the job. Technology-wise, I’ve encountered various tools to support my role. Working in construction and being an end-user has given me the unique perspective to understand how I can support my clients at IMAGINiT. It’s exposed me to the thought process that goes behind every decision when selecting and adopting new technology.

I’ve struggled through antiquated processes and contractors not fully trusting technology. I’m passionate about breaking stigmas and helping contractors streamline their operations by embracing technology. I felt like there was an opportunity to help enable teams to use their tools to their fullest potential.

AI is transforming the way that we work, there’s even more urgency around evaluating new tech tools and making sure that we’re adopting and embracing them. One of the things that contractors are good at is being adaptable to change. We’re starting to see more contractors leading the charge on tech adoption and driving innovation.

Contractors ‘being adaptable to change’ is a rather striking statement, because the opposite of that has been the trope in construction. It’s usually, ‘This is the way we’ve always done it.’ Are there any examples that stand out in your mind that make you say that?

Lawrence: I was listening to a podcast; the guest surveyed about 400 contractors, of which 60% said they were adopting AI. It was reassuring to hear that a majority of firms are trying to use it. It’s powerful to see contractors developing their own AI software specific to their needs. There are contractors leading the charge of the digital-era, wanting to be innovative and creative with technology.

Would you say that technology is attracting women to the industry?

Lucas: These new roles that are emerging, like ours, are more focused on strategy: process improvement, workflows, systems, many focus areas where women naturally excel. So, we’re getting a lot more meaningful innovation that’s happening because we can become leaders on that path. And that path is not following a field-first trajectory—a trajectory which traditionally doesn’t attract women. We’re seeing a lot more people come into the tech sector directly.

Lawrence: Both the construction and the technology industry are male-saturated. Tech is revealing more opportunities for people of different backgrounds to collaborate and contribute to the thought that goes behind workflows and operations. 

What efforts is IMAGINiT taking to draw more women to this industry and these types of roles? What—or who—drew you to this company and this role?

Lucas: What drew me to IMAGINiT Technologies is the level of expertise of the team overall and the software development they were doing. They were my biggest competitor! Folks like Sarah and I get to work together on opportunities and get into those rooms with other women. However, my former position was as a director at a company in New York City and the owner of that company was a male—someone doesn’t have to be a female to be a great mentor. People who give you that opportunity—even if it’s a stretch—and they believe in you, that is really what matters. And coming to the table, being confident in what you know from your industry experience will get you so far. It doesn’t really matter what your gender is, if you know what you’re talking about.

Lawrence: Part of what drew me to IMAGINiT was the women in leadership, both our director of construction and one of our construction team managers. I appreciate having those influences and women represented in leadership positions. Throughout my career, I’ve had both male and female mentors, all of whom supported me as I navigated my career in male-dominated industries. It’s important we embrace everyone’s contributions, the value we all contribute from our different experiences and backgrounds. Overall, both the construction and the tech industry promote and embrace diversity of thought.

Would you consider yourselves mentors today?

Lucas: Oh, for sure. Especially on my team and even in what I was doing before IMAGINiT, we’re sharing knowledge. We’re bringing people into that bubble of the construction world. I have colleagues on my team who are stronger in other areas of the industry than I am and vice versa. So, we’ll get together and share our strengths—there’s no shame in that. We stay curious about not just the technology, but how things are built. We don’t shrink ourselves and we know that because we’re in this seat and we’re in this room, we did earn it.

Lawrence: Absolutely, I’m always open and willing to support others in the industry. I make an effort to extend the same support I received to others—pay-it-forward—ensuring that folks entering the industry feel welcome and I provide guidance when needed. Ultimately, I want to highlight the importance of promoting psychological safety across your teams. One of my favorite construction-specific courses was through Arcade Construction Academy. They introduced 10 core precepts that I believe should be upheld by every team. To name a few: Stupid questions are a requirement for entry; It is the responsibility of leadership to create a safe space to fail; and, All mistakes should be discussed and dissected, never hidden. In construction and technology, things are constantly changing and you’ll never be an expert, not 100%. There is always something to learn and every project is different. It’s incredibly important to create an environment where teams can collaborate, exchange knowledge freely and admit mistakes.

SEE ALSO: MORE CONSTRUCTION COMPANIES ARE BUILDING A TECHNOLOGY-FOCUSED C-SUITE

The post Turning a Construction Career Into a Technology Career first appeared on Construction Executive.

That gap is the whole story. The capital that builds breakthroughs is going to one place and it isn’t the jobsite. It’s the office.

For an industry that has spent a decade waiting on autonomous bricklayers and exoskeletons, this should be clarifying. If great robots were ready, contractors would be deploying them. Hardware that has to operate safely in unstructured environments, around humans, in weather, on schedule, is genuinely hard. Capital markets know this and are voting accordingly.

Meanwhile, the systems behind the field-to-finance workflow like the expense report, the pay app, the change order and the submittal are being rebuilt right now with most of that $211 billion behind them. AI agents that read, route, approve and reconcile administrative tasks are in market, deployable this quarter. Leaders waiting for the robots to arrive are waiting in the wrong room.

The Hidden Constraint on Scale

Every construction firm carries administrative load. Time tracking, expense reports, pay apps, submittal logs and change-order approvals don’t disappear thanks to AI. But across many firms, back-office process flows still rely on spreadsheets, email and on-premise file servers. Even for firms using established project management systems, many handoffs remain manual and error-prone.

As firms grow, this is not an area where efficiencies are gained. A change order that took one review when the firm ran out of a single office takes five when a second branch opens. Data gets rekeyed across the project management system, the accounting system and the field reporting tool, now in two locations, with two AP teams reconciling against each other. Senior estimators and PMs end the week having spent ten hours on tasks no client paid them to do. The default response is to hire. Add an AP clerk, add a project coordinator, add another controller. It works in the short term. But every added admin head raises G&A permanently and adds another handoff where information can stall. Overhead starts compounding faster than backlog.

Why the Math Has Changed

The common objection from controllers and operations leaders is straightforward: Can an agent really do what a senior accountant, project coordinator or estimator does today? That is the wrong question.

The right question is whether an agent can create 45 hours of capacity across a five-person team: nine hours per person, per week. Framed this way, the answer changes quickly. Capacity compounds across workflows, not job titles.

On a fully burdened basis, an office hire is a six-figure annual commitment that improves incrementally with training and tenure. An AI agent, by contrast, holds a relatively stable cost profile and improves multiple times a year as underlying models are updated. Firms that deploy agents early inherit those gains automatically, without renegotiating compensation or restructuring teams.

That framing is supported by emerging labor-market data. In March 2026, research comparing what large language models could theoretically perform across occupations with what they are actually doing in live workflows today highlighted a significant gap. One chart from this report (a radar showing theoretical versus observed AI task coverage) captures the dynamic clearly.

Office, administrative, finance and professional roles show some of the largest gaps between capability and adoption. The ceiling is already visible. Most organizations are simply operating far below it. The binding constraint is not technology; it is deployment.

For construction firms, this matters. It explains why AI is not arriving as a single moment of labor replacement, but as incremental capacity gains embedded inside existing teams. The early wins are administrative: expense routing, time reconciliation, pay applications, submittals. Firms capturing that capacity now are not eliminating roles. They are changing how much work a fixed headcount can reliably support.

The Hiring Filter

Before any open requisition becomes a job posting, it should pass through a new gate: Can the work be handled by an agent? If the answer is yes for even half the role, the remaining work can be redistributed across the existing team and the role may not need to be posted.

If the answer is no—a body is genuinely needed—the requisition still has to clear a second test. Every new hire should be accretive, not dilutive, to the firm’s AI readiness.

That sounds abstract until you measure it. A simple internal benchmark works: What percentage of the team is AI-literate (can use the tools), data-literate (can structure information for them) and AI-curious (will reach for them unprompted)? In recent survey work with one client’s accounting department, those numbers came in at 55%, 85% and 70%. That’s the baseline. Every new hire either raises the average or drags it down.

This shows up in the job description before anyone is interviewed. Hiring a senior estimator? Add “fluent with AI-assisted takeoff tools” to the requirements, not the preferences. Hiring a project coordinator? “Comfortable building and refining agent prompts” belongs above “proficient in Excel.” The wrong hire isn’t the one who can’t do AI work today, it’s the one who has no interest in learning.

Burdened, an office hire is a six-figure annual decision. It’s worth the extra week to make sure that decision compounds in the right direction.

A Strategic Shift in How Firms Scale

Contractors that have moved furthest are no longer treating automation as a one‑time initiative, but as a permanent operational discipline shaping how they scale. Deploying agents aligned to real workflows lowers long‑term cost structures while improving execution and governance.

The capital markets have already made their bet. More than $200 billion is flowing into the systems that power paperwork and office workflows, not into autonomous jobsite labor. That investment is already at work in the back office, whether contractors deploy it intentionally or keep hiring around it.

SEE ALSO: THINKING OF AI AGENTS AS MEMBERS OF A CONSTRUCTION CREW

The post How Contractors Are Shifting Headcount Budgets to Agent Budgets first appeared on Construction Executive.

Cofounder of the Boston-based contech company, Cyvl, Pelaez is helping over 100 U.S. cities rethink how they build and rebuild their roads.

“Through vehicle-mounted sensing and analytics already embedded in day-to-day operations, Cyvl is effectively powering the reconstruction of roads up and down the country—determining what gets fixed, when and why,” says a representative of the company.

Having just been named in Cemex Ventures’ Top 50 Contech Startups for 2026—which recognizes companies that are already influencing how construction and infrastructure decisions are made on the ground—Cyvl sat down with Construction Executive to discuss their evolutionary work further.

Maybe even stay tuned for a sneak peek inside one of their AI-powered cars.

What was the impetus for starting this product/company?

DANIEL PALAEZ: It’s a fun story. It started with the problem and we found the technology to solve that problem. One of my first ever jobs was working on the road crew for a public works department in Southbury, Connecticut. And I was seeing firsthand how hard it was to manage infrastructure. The town was reacting to issues every single day, whether that be residents hitting a pothole or trees falling down or missing signage no one noticed until it caused an accident. This was a smaller city that was relying on outdated data that lived on paper in a three-ring binder.

I was only about 18 or 19 at the time, but I figured there had to be a better way. So, I started talking to lots of other communities and realized they were relying on similar techniques. When I entered college in 2020 for engineering is when I started to learn about these sensors used for self-driving vehicles, and that was the “a-ha” moment of seeing the massive problem firsthand, recognizing that pretty much every community across the U.S. is battling with outdated infrastructure and information. Then it was about figuring out how technology from self-driving cars could be applied to automatically map out infrastructure, and how to use AI to perform condition assessments, recommend treatments, budgets, etc. That is really where we saw the magic of applying that tech to this problem. Ever since then it’s been a very fun journey helping hundreds of governments implement this into their day-to-day workflows.

What was the process of getting this off the ground?

About halfway through college, I thought this would be a fun application of the tech. It was never a class project. I just started conceptualizing it in my mind and I recruited one of my best friends and roommates—we’ve actually known each other since we were seven years old—who is way smarter than I am to help me build it out.

We didn’t know anything about starting a company; we just thought we were solving a cool problem. We began looking for funding to make prototypes and entering innovation contests across the country. After winning a few of them, everyone kept telling us, ‘Hey, this is a really big problem that our country and the world needs to solve,’ which motivated us to take it more seriously. So, shortly after graduating, we decided to become cofounders and brought on a third friend of ours from college to help us with the AI side of things. We raised $100,000 from our first ever investors, which felt like a lot of money at the time—we were all just 22 years old. We made that last more than a year until we got our first customers. And it’s been a wild ride since then.

When did this product officially hit the streets?

At the beginning of 2022, we started our first projects with municipalities and a few civil engineering firms in Massachusetts. Those were crazy days where the product barely worked, but we were determined to make it better and to keep getting feedback from the cities and towns we were working with, which was invaluable to us at time.

Do these sensors/vehicles operate as a service (i.e. SaaS)?

It’s an annual investment the cities make in our technology. What that gives them is access to the sensors, which they can put on their vehicle so they don’t need to buy them, and access to our software program, which is what’s taking all the data from the sensors, automatically processing it, doing the condition reports and then creating plans and budgets so the city can get to work with more speed and accuracy.

Was it hard to get cities to agree to bring this tech on board?

Yeah, it was incredibly hard. Imagine a 22-year-old placing cold calls into every single town or city in the state telling them, ‘Hey, I have a better way to manage your very expensive roads and sidewalks.’ There was a lot of skepticism—especially when they asked how many customers we had and we had to say zero. We got a lot of nos, but, slowly but surely, we started building a reputation. It’s still challenging these days, but I think that’s what’s really been special.

Cities do see immediate value when they start working with our technology. Now there’s less perceived risk when we can present them with data from working with some of the biggest cities in the nation. It was never easy, but, as with any business, you just have to keep pushing through.

What is the smallest/biggest city you’ve worked with?

We’ve worked all over Massachusetts, Iowa, Wisconsin in some pretty small communities, about 5,000 people or under. Our first big customer was the city of Atlanta. We partnered with them about a year and a half ago, and we were just selected by the city of Nashville to do a full five-year infrastructure plan. We have a few other big cities that we cannot formally announce yet, and we’re even beginning talks with some state DOTs.

How do you hope to see your company evolve?

I’d say our number one goal and our mission as a company is to enable government agencies to build infrastructure 90% faster and 50% cheaper than they’re doing today. And if we can encourage a digital-first standard, I’m sure there will be more companies like us popping up, and I’m sure some of the major civil engineering firms are going to start to embrace these technologies, too. If we can make that the de facto standard for the U.S. by 2030, that will be a huge accomplishment for us. We’re really trying to change an entire industry here, and we’re not going to do that alone. So, bringing more people along with that shared digital-first mentality and the new operating model for infrastructure is incredibly important.

How do you hope that your story might inspire the future of construction business owners and innovators?

I’ve been so fortunate just to be surrounded by mentors and advisors and friends that have been cheering for us, supporting us, rooting for us unconditionally, because the construction industry is definitely not the quickest to adopt technology and rightfully so—there are major risks on the line when you’re talking about critical infrastructure. I think for good reason people are conservative about trying new things.

My advice is simply ‘don’t give up.’ It’s very easy to be told no 99 times and to return to whatever you were doing in life before. But, I guarantee you, that if you just keep your mind to it, you don’t give up, you persist, whatever you’re working on, whether it’s a business in this industry or not, you’ll be successful. Then surround yourself with like-minded folks, because you need that positivity. You have to be a default optimist.

SEE ALSO: NEW WALL-SCALING ROBOTS ARE SAVING CONSTRUCTION COMPANIES TIME, PRODUCT AND PERSONNEL

The post Contech Company Cyvl Uses Vehicle-Mounted AI Sensors to Collect Fresh Data for Some of America’s Biggest Cities first appeared on Construction Executive.

The result is redundant data entry and lag times that leave the back office relying on financial data that’s sometimes two to three weeks old. Without timely integration between the field and the office, budget overruns are difficult to catch early, making it harder to protect profitability before the damage is done.

Construction financial management is also inherently complex because it’s not just about moving money; it’s about managing a mountain of legal defense. Manually tracking insurance certificates, safety logs and lien waivers for dozens of subcontractors is logistically challenging. A missing signature or expired policy can halt a multi-million dollar project or expose the general contractor to massive legal liability.

That’s why more contractors are turning to financial management technologies to navigate increasingly complex financial environments—shifting from reactive accounting to fully connected construction workflows that more easily improve cash flows, reduce lag time errors and align teams.

With an integrated system in place, the finance team can act as a true strategic partner to project teams, helping them not just increase profitability, but take on bigger, more complex jobs—ultimately positioning the business for sustained growth and a stronger competitive advantage.

Integrated Workflows Start from the Field

Shifting to more integrated financial workflows begins with field data, which serves as the critical link connecting what’s happening in the field with back office personnel who must then process that information in a timely manner.  This includes information like labor hours, material and equipment costs, RFIs, submittals and change orders, which are recorded daily in the field.

Within many construction companies, the “field” (project managers and foremen) and the “office” (accounting and finance) operate in disconnected silos. Field teams use project management applications and field logs to track daily progress, while accounting relies on separate financial systems to manage invoices and payments. This lack of timely data flow can create a lag, delaying the discovery of financial issues sometimes weeks after they occur.

A connected ecosystem bridges this gap by unifying field and project data with financial management via a single, shared flow of information. This ensures that both the project lead in the field and the person cutting the check in the office are working from the exact same data.

This workflow ideally starts by transferring bid data directly into a field or project management solution. A common cost-code structure acts as the connective tissue between the field and the office. As crews work, they log hours and materials and other costs against those specific cost codes. This isn’t just “status tracking;” it’s the foundation of accurate job costing.

Hours estimated versus hours spent against the budget can be more easily seen and managed. For example—if a contractor budgeted 40 hours for framing and has already spent 38 hours with half the work done, the overrun will be flagged. This allows the problem to be fixed that week, rather than finding out at the end of the month when the bank account is empty.

Field to financial integrations can also help with change orders, which are often hidden costs that aren’t noticed until the very end of a project. But when systems are linked, the change order process moves from being a paperwork headache to a proactive financial strategy.

For example, when a subcontractor encounters an onsite conflict that results in a potential change order, it’s immediately logged in the financial management system as a pending item. The system automatically calculates the potential change order’s impact on the project’s bottom line and alerts the project manager if it threatens to consume the remaining contingency. Once the owner approves the change, it’s converted into an official change order and synced with the ERP, where it automatically updates both the subcontractor’s contract and the owner’s prime contract.

The Subcontractor Relationship: Facilitating Accuracy, Speed and Trust

Another critical workflow is invoice, compliance and lien waiver management—especially for subcontractors, who are often left chasing payments through emails and phone calls. Automated payment portals like Trimble Pay act as a digital bridge between project managers and subcontractors, standardizing payments through a digitized system. It replaces tedious paperwork with a guided digital experience, shifting the dynamic from chasing checks to simply verifying progress.

Subcontractors submit invoices through a dedicated digital portal, where built-in checks ensure everything is in order before submission. If a certificate of insurance has expired or a required license is missing, the system prompts them to upload the necessary documentation on the spot. It also automatically generates the appropriate conditional lien waiver based on the invoice amount, streamlining compliance and reducing delays.

Once an invoice is submitted, subcontractors gain full visibility into the review process, including who is currently evaluating the bill—whether it’s the project manager or accounting personnel. After approval, payments are released via ACH directly through Trimble Pay.

This transparent, end-to-end process replaces the back-and-forth of phone calls and emails. Subcontractors can track their invoice status from submission to final payment, fostering greater trust and strengthening working relationships.

The Connected Future

Moving from manual, siloed operations to an integrated data ecosystem provides three major benefits to contractors:

Elimination of the Visibility Gap: By integrating field data with back-office accounting, contractors achieve more timely project and financial visibility. This allows them to catch budget overruns (such as labor hours exceeding estimates) and track pending change orders when they occur, rather than discovering financial damage after a project is already over budget.

Reduced Risk and Automated Compliance: Managing compliance and lien waivers on spreadsheets is a gamble. By integrating workflows, financial solutions automatically collect and validate documents before money moves, reducing the risk of costly claims or financial disputes. The transition to automated payment portals reduces administrative friction, fosters trust and strengthens the long-term partnership between the contractor and their trades.

Scalability Without Overhead: Integrated systems allow contractors to take on more complex projects or a greater volume of work without expanding back-office staff. The efficiency gains in payment processing alone allow the finance team to act as strategic partners to the project teams.

Shifting to a fully connected financial ecosystem transforms construction management from a reactive struggle into a proactive strategy. Bridging the gap between the field and the back office helps contractors protect their bottom line through more immediate visibility, automated compliance and stronger professional partnerships. In an industry where a single missing signature or an unrecorded change order can erase a year’s profit, these digital workflows serve as the essential foundation for building a truly scalable and profitable business.

SEE ALSO: WHEN BUILDINGS FORGET: DIGITAL DATA SILOING

The post Powering Profitability With Connected Construction Workflows first appeared on Construction Executive.