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 This was a smaller city that was relying on outdated data that lived on paper in a three-ring binder.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of seeing the massive problem firsthand, recognizing that pretty much every community across the U.S. is battling with outdated infrastructure and information.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.

From technology’s ever-increasing enmeshment with the construction workforce to persistent data-siloing issues and more, Jon Fingland, vice president and category general manager at Trimble, sat down with Construction Executive to reveal the findings of this first-ever study.

The throughline of this survey seems to be the enmeshment of construction technology and the workforce. How have you seen construction technology and the workforce become more intertwined as technology develops and the workforce shortage worsens? 

I lived through the move to the cloud, the transition to mobile devices. Now we’re living through the age of AI. If I rewind to getting paper cuts from blueprints—that’s how old I am—then fast forward to today’s ability to have the latest drawing set available at the touch of a device in the field, that seems profound. That was one of the first big problems we had to solve in the industry: making sure people are working off current data.

I think what’s interesting about this moment in time is that you need some outside factors to really get people serious and honest about making the change of how they deliver the project and how they process internally. If you look at what’s happening in our market right now, it’s all coming to a head of supply-chain pressures and tariffs and workforce shortages.

We need a half million more workers this year. And 40% of the workforce is going to retire in the next five years. Combine the complexity of the work with the pressures on the supply chain and you start to see signals of shifts even in how people contract work.

They just don’t have enough workers. It’s a real problem—they must figure out how to do more with less and how to collaborate and create more predictable construction. That’s where this survey really comes into play and serves as validation that our customers are truly feeling it; that it’s not something they can continue to absorb. It’s forcing them to look at different techniques.

Would you say that, while your contractors seem pretty optimistic, they are still behind the eight ball when it comes to certain action items?

If we rewind again to 10 years ago, I don’t think the environment felt so different, but I think that now the industry is in a place where with labor and supply-chain constraints, contractors are needing to make changes. So, I look at that as a glass half full. If over 80% of contractors have an optimistic outlook about AI, but only 40% are implementing it, that 40% is still probably higher than it was 5-10 years ago. That’s a material amount of the market; I’ll take it.

Why is survey and positioning tech some of the most sought after pieces of technology that you found in this survey?

A lot of it comes from what our customers are asking us for, and it’s triangulated based on market research. There’s also an influx of outside investments from the VC and PE community investing in this space which is good for our industry. Every day it’s changing and it’s interesting to see it at the top of the survey list this year.

When it comes to companies either not adopting contech at all, not adopting enough of it, or the right kind, how can the industry as a whole continue to encourage or ramp up the buy-in of this technology?

We need to change behavior, which is hard to do. You still hear, “It’s just the way we’ve operated. This is how we schedule, how the spec is written…” There is a lot that must change. So, we have to encourage people to continue to do more, to commit to the journey.

On the vendor side, to really change behavior, you’ve got to build trust. There’s no doubt that AI can get involved in helping with decision making and automation. But when we do those things with AI, we’ve got to be able to show the vendors how we decided so that they can trust that and see where that recommendation came from.

When it comes to data siloing, one silo of sorts is the 40% of the workforce that’s set to retire. How can the industry ensure that that knowledge isn’t gone when that set of people retire?

If we take a lesson learned in the industry from 15 years ago: They started to build VDC departments, but they kept their normal estimating, scheduling and project management departments, creating an us-versus-them mentality. What we need is the experience from all domains that all these folks leaving have, plus these new folks coming in. The next generation is coming in more accepting of AI, more accepting of 3D and VDC workflows, et cetera. But you’ve got to bring those teams together. If you’re trying to change culture and behavior, you need to merge those folks in. You must use that experience and adopt a new process.

In an earlier conversation, the word ‘democratized’ was used regarding the advancements of scanning and positioning technology. Elaborate on what that means.

The way the industry has historically worked with data is in starts and stops. You design it, you hand it over and then you start to construct it, but often when you hand it over, you lose knowledge. It’s that stair step or see-saw. Every functional area and every stakeholder have their own data and data model. We’ve got to find a way to liberate that data so that it can be used throughout the process. We want the data to be available to everyone across the lifecycle. With new technology, what was once only accessible to bigger, more advanced companies is now also accessible to smaller contractors.

The construction industry’s attitude around AI has already gotten so much better. Would you say the industry is on a cusp when it comes to AI adoption and implementation?

Exactly. That’s why I get so excited when talking about the 40% who are already implementing. That’s very close to 50%. That’s what I need. I don’t need 100% right now. We need 40-50% to make certain moves. And I’ll bet, once the other half sees those moves, they won’t be able to unsee them and they’ll want to make them themselves.

SEE ALSO: THE BENEFITS OF INCORPORATING AI INTO THE CONSTRUCTION LIFECYCLE

The post Trimble Launches New Survey at Annual Dimensions Conference first appeared on Construction Executive.

Construction Technology That Actually Works

Construction technology should target sources of profit loss, such as downtime, rework, budget overruns and safety incidents. Here are proven investments with measurable ROI.

Building Information Modeling

The concept of 3D modeling has been valuable in producing geometric representations of blueprints. Building information modeling takes it a step further by creating and managing extensive project data, including costs, materials and schedules.

Companies can expect better stakeholder collaboration and reduced rework when they connect on these crucial elements and stay aligned. BIM is already expected to increase from $10.27 billion in 2026 to $27.12 billion by 2034 with a CAGR of 12.90%.

Reality Capture and Machine Learning

Reality capture through drones and sensors is versatile, as these tools can be used for site surveys, progress monitoring and safety inspections. Combined with machine learning, progress reports become accurate enough to improve worksite safety for workers.

The collected data can also be used to improve equipment quality and lifespan. Use it as a basis for predictive and preventive maintenance, helping companies experience 52.7% less unplanned downtime than those using reactive maintenance.

Centralized Project Management Software

Centralized project management software can streamline communication, documentation and scheduling all in one platform. A report found that 77% of optimized users saw increased profit margins.

The software also offers productivity gains. By unifying project tasks and enhancing real-time visibility into project progress, construction businesses can reduce their administrative errors and minimize field delays.

Overvalued Tech With Uncertain ROI

As important as technology is, certain buzzwords have innovative potential but are risky or have low ROI. Firms should practice more careful consideration to avoid poor technological investments and implementations.

Metaverse

The metaverse has become more possible through a combination of virtual reality, augmented reality and artificial intelligence. It has the potential to improve virtual visualization and 3D modeling, thereby impacting energy efficiency and reducing construction waste.

However, despite its power, technological limitations and data privacy concerns still hinder its widespread adoption in the construction industry. Investing in it now without proper development might involve little to no return.

Blockchain for Supply-Chain Management

Tracking materials and other resources from a factory to a jobsite can involve numerous documents. Integrating blockchain solutions can boost operational efficiency by 25% while reducing fraud by 50%, which improves transparency between workers and stakeholders.

However, it’s hard to ignore the high implementation costs associated with blockchain. It can also be complex to understand, which isn’t ideal for construction start-ups that may prefer simpler options, such as centralized project management software.

Generative Design

Another application of AI is generative design, which entails creating plans with minimal human input. It’s intended to simplify the planning process, but there are concerns about the unethical use of this technology, given GenAI’s challenges with domain knowledge and model accuracy.

Generative design is prone to hallucination and mistakes. Removing the input of experienced architects and engineers early on in the process can also lead to further delays and expenses in the long run.

How to Choose the Right Technology for the Firm

Differentiating between technological investments that deliver measurable results and those that are simply buzzwords can be challenging. It’s important to take the time to analyze these prospects. Here are tips to help construction industry professionals choose the right ones.

1. Identify Problems Instead of Products

Instead of chasing technological solutions based on what’s popular, focus on what problems the construction business is actually facing. For instance, to improve equipment lifespan, predictive maintenance analytics would be most effective.

Start by defining a problem and then work from there. If there are no clear areas for improvement, take the initiative to identify what would positively impact the company’s profits.

2. Consider the Investment Risks

As high as the ROI may be for certain technologies, it’s still important to understand any risks associated with their implementation. Small- to medium-sized companies, especially, should be vigilant about where they invest their money.

For instance, BIM is ideal for improving planning. However, implementation costs can be relatively high, with some services charging monthly or annual fees, depending on the scale and complexity of the project.

3. Implement a Pilot Project First

Before widespread technology adoption, it’s safe to implement a pilot project first. This will involve a limited number of users to evaluate functionality and gauge the budget and resources required to use the tool effectively. It’s best to have an IT specialist who can help lead its integration.

A pilot project should have a specific timeline and a list of goals that would warrant its implementation. Profitability is a key performance indicator, but it’s also important to assess other elements, such as reduced delays and errors compared to traditional methods.

4. Get Employees Involved Through Training

Incorporating new technologies can become much smoother when employees are involved in the process. Managers should provide adequate training sessions to familiarize construction teams with using these tools, ensuring greater success and better results.

Training can also translate to a more positive evaluation of the pilot project and encourage buy-in from business leaders. Seek their feedback to explore any adjustments in the implementation process when it goes companywide.

Be Intentional With Technology Adoption

Technological adoption should enhance profitability and productivity in the construction industry. Evaluate industry solutions before integrating them into the project process to ensure that upcoming investments have a real impact.

SEE ALSO: EXECUTIVE INSIGHTS 2026: LEADERS IN CONSTRUCTION TECHNOLOGY I

The post Which Construction Technology Investments Actually Move the Needle on Profitability? first appeared on Construction Executive.

One common thread links both problems: Documentation gaps turn minor issues into major disputes.

When issues pull teams away from higher-value work, visual site documentation, especially 360° imagery, is shifting from a nice-to-have to a strategic safeguard. Captured consistently and linked to location and time, 360° documentation strengthens risk mitigation, supports compliance, speeds dispute resolution and helps teams deliver higher-quality outcomes across the full building lifecycle.

The Documentation Gap: Why Traditional Methods Fail

Most site teams already take photos. The problem instead is that conventional documentation often fails under pressure because it is hard to retrieve when needed most.

The pattern repeats across projects:

• Fragmented storage across photos, emails, paper logs and shared drives
• Limited context in standard photos that show detail(s) but not the surrounding conditions
• Inconsistent formats across stakeholders, including subcontractors and third parties
• Slow retrieval during inspections and audits
• Weak defensibility when key phases were not documented clearly

Records can exist and still be unusable. When an owner or insurer asks for proof of an inspection step, or when subcontractor disputes come down to “Who did what when?” teams can lose days searching for information or relying on memory and partial notes. When documentation processes add a layer of risk, it is the way visual information is captured that needs to be reworked.

What 360° Visual Documentation Changes

A 360° capture builds a continuous record of the site. Instead of a single photo that shows details in isolation, 360° imagery creates a time-stamped record of what was built, where it was built and what else was happening at that point.  Beyond capturing the site, documentation must be standardized across teams ensuring formats stay consistent and site data is stored in one place. With full context and a defined structure, teams can build compliance reports quickly and retrieve supporting evidence without a time-consuming search.

Stronger Risk Mitigation and Fewer Disputes

Claims often hinge on proof, sequencing or installation quality. Gaps in proof create ambiguity, which leads to disputes in predictable scenarios:

• Subcontractor responsibility disputes (what was complete when the next trade started)
• Delay claims tied to access constraints or work-area readiness
• Defect allegations where workmanship is questioned after walls close
• Warranty discussions that depend on installation conditions at handover

Consistent 360° visual documentation reduces ambiguity by showing site conditions and progress status in a single view. The discipline matters as much as the technology. When contractors capture sites consistently, disputes shift from memory-based arguments to fact-based conversations about documented conditions.

Better Compliance and Inspection Readiness

Regulators want visual proof that safety steps were completed. Insurers want transparent records to evaluate risk management and, in some cases, to shape coverage terms. Paper-based logs and disconnected systems slow teams down during audits. Digital documentation helps by centralizing workflows, which reduces errors and ensures documentation is continuous. A structured digital record can be pulled into a report in seconds. 360° capture strengthens compliance records by showing full context: not just what was installed, but what surrounded it and what stage the work was in.

Higher Quality and Less Rework

Rework is expensive because it pulls labor off planned work and creates downstream schedule impacts. A consistent 360° record helps teams track progress at each stage and compare conditions over time before they are concealed behind walls or ceilings. Later, during troubleshooting, teams can review what was installed at a specific phase without opening walls. Side-by-side comparisons between two dates show exactly when something changed, which speeds issue resolution.

How 360° Capture Fits Into Standard Workflows

To protect margins and reduce exposure, successful teams treat 360° capture as part of routine site workflows, not a separate task. Field teams walk a floor or zone with a helmet-mounted camera on a predictable schedule, then upload the imagery to a central project record where it is pinned to plans and timestamped.

When capture is consistent, it becomes useful across quality assurance, safety, progress tracking, owner reporting and closeout. Features like PlanRadar’s SiteView, for example, pair 360° walks with AI algorithms to automatically map imagery to 2D floor plans, so teams can access site areas by location rather than scrolling through folders.

Structured Data: The Foundation for AI-Assisted Workflows

As teams capture more site data, structure becomes critical. When documentation is stored consistently, tagged the same way, pinned to plans, centralized in one system, AI can retrieve information in seconds instead of hours.

This enables AI-supported capabilities like:

• Search across captured project data to find relevant records faster
• Automated project overviews generated from current field documentation
• Faster retrieval of critical information during audits, inspections or claims
• Earlier visibility into risks and patterns, such as repeat issues by location or trade

The payoff depends on fundamentals. Structured documentation today creates the foundation for AI-assisted insights tomorrow.

Documentation as a Competitive Advantage

In short, 360° documentation is risk management. It helps contractors prove what happened on a project, which supports compliance, strengthens quality control and reduces uncertainty when stakeholders disagree. When project data is structured, centralized and time-stamped, AI can surface insights in seconds, turning documentation into actionable clarity.

As projects grow more complex and regulatory expectations rise, the contractors who thrive will not be the ones with the most photos. They will be the ones who can prove what happened, when it happened and what else was happening at the same time, in seconds, not days. That’s documentation as a competitive advantage. 

SEE ALSO: THE REALITY OF IMPLEMENTING VR/AR ON THE JOBSITE

The post Full Project Transparency: Why 360° Documentation Is Becoming Essential on Modern Construction Sites first appeared on Construction Executive.

“The research indicates the construction industry is nearing a tipping point for AI adoption,” says Steve Jones, senior director of industry insights at Dodge Construction Network, who sat down with Construction Executive to delve further into the survey questions and answers and what the industry’s current position on them means for AI’s future role in construction.

Other results worth noting include:

• 85% of contractors expect they will spend less time on repetitive, mundane tasks
• Over 70% believe they can make better decisions because AI offers insights they might not arrive at on their own
• 75% look ahead to AI helping them learn from past projects by mining historical data
• 40% are currently allocating a dedicated budget to AI
• 38% are creating implementation teams
• 19% report adapting legacy workflows for an AI environment
• 51% are actively evaluating several potential AI-related changes across their teams
• 81% recognize the benefit of automated constructability analysis to identify potential field issues during design
• 80% express interest in intelligent permit submission with automatic compliance checking
• 79% note strong potential for autonomous project optimization that adjusts schedules and resources in real time
• 76% identify opportunities in dynamic pricing optimization based on market conditions and risk factors
• 92% acknowledge the value of automated contract creation and management
• 79% value intelligent bid-no-bid decision support

The overall findings seem overwhelmingly optimistic. Was that surprising?

No, because there’s already so much in the general consumer environment about AI. It’s very different than when BIM came out—because that wasn’t widely talked about; you had to be in the industry to even have heard of it and it was easily dismissed as just another form of 3D. But now AI is so wide and there probably isn’t anybody who answered our survey who isn’t already also using ChatGPT or Claude or one of these LLMs. They know how it functions, what it does, and they’ve heard so much about it.

I expected the job loss question to score pretty highly in terms of concern—I was pleased to see that that was pretty low, around 20%. I think we may have gotten over that concern.

For the last two years I’ve been pushing to call it augmented intelligence instead of artificial intelligence. AI is here to help us all be better and faster. It isn’t here to replace anybody.

The survey shows 85% of contractors expect they will spend less time on repetitive, mundane tasks. It’s surprising that that’s not 100%. It that because contractors don’t expect AI to be able to automate everything?

There are certain repetitive tasks that don’t lend themselves to AI. It will be interesting to come back to a study like this two or three years from now asking similar questions and compare answers. The answer may be 99% at that point, but at the end of the day, AI’s not going to dig a ditch for you. But there is a robot that’s going to dig that ditch. And the robot will be powered by AI.

Would you say AI is creating opportunities for more jobs rather than replacing workers?

I don’t know that it’s creating the opportunity for more jobs, but what it’s going to be able to allow people to do is contend with the resource strain and drain from the workforce shortage that isn’t going away. The combination of AI automating mundane tasks and robotics being able to actually do labor will help people become much better decision makers.

Only 40% of those surveyed are allocating a budget for AI. Is it that people can’t yet afford these full tech stacks? Or is there just not enough buy-in to AI in general?

There still seems to be a general wait-and-see attitude. People like to know they’re not alone in whatever it is they’re doing. We can say, ‘Here is what a hundred other folks who look a lot like you are doing with this and what’s working and what isn’t working.’ So, they can have the confidence to move forward.

With AI, once people are in the game, they like to play the game and they don’t know why they didn’t start playing earlier. So, how fast do you see the number of players increasing by the end of the decade?

I think it’s longer than that. Because even as big as AI already is, construction is a people business at the end of the day. Human beings have to make the decision to get in the pool and how far down towards the deep end to swim. It’s such a fragmented and growing business right now, nobody has very much time to put energy into something that would seem extracurricular.

If you look at this industry 15 years from now, it will look dramatically different than it does today. But I don’t think the next four or five years are going to show that much. We will begin to see greater preparation, much more engagement and awareness. And I think we’ll see a similar pattern of those who have gotten into the game and are using AI saying that it’s great. The vendors need the feedback coming from the users. The more people who’re using AI, the more feedback they can give and then the better the vendors can make those tools function. The function of AI already far outpaces what construction’s ready for now.

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

The post New Survey Reveals Overwhelmingly Optimistic Results on the Use of AI in Construction first appeared on Construction Executive.

Construction as a Technology Leader

One of the defining moments of CES 2026 came during Caterpillar’s keynote address. CEO Joe Creed addressed a packed room with a question many may have been thinking: “Why is a construction equipment company delivering a keynote at CES?”

The answer became evident quickly. Modern construction equipment is no longer just mechanical—it is digital, autonomous, connected and powered by sophisticated technology stacks. Caterpillar announced five autonomous construction vehicles and demonstrated Level 4 autonomy capabilities. The shift underway is significant: Operators are transitioning from inside the cab to remote environments where fleets can be managed simultaneously. Perhaps the most notable unveiling was the CAT AI Assistant, scheduled to go live in Q1 2026. During a live demonstration, a simple voice command adjusted an electrical line warning height to 13 feet. The assistant integrates speech, text and image recognition—representing a move toward multimodal AI systems that assist real-time field operations. Construction is no longer simply adopting technology—it is helping define how technology is applied in the physical world.

A Connected Equipment Ecosystem

Across the LVCC West Hall, the evolution of heavy equipment was unmistakable.

Oshkosh and JLG showcased paired scissor lifts engineered specifically for lifting structural steel—an example of equipment designed around task optimization rather than generalized capability. John Deere continued expanding its autonomous ecosystem, reinforcing the trend toward intelligent fleet coordination.

Battery innovation companies, including Lyten, demonstrated advances in energy density and battery chemistry, highlighting that electrification is moving beyond experimentation and toward jobsitewide energy strategies.

Electrification discussions at CES 2026 extended beyond machines themselves. Charging infrastructure, energy management systems and power optimization software were part of the broader narrative. As cities push for lower emissions and reduced noise pollution, electric equipment is becoming a practical solution for urban and indoor projects.

It is no longer just about whether electric machines can perform—it is about how entire jobsites can be powered efficiently and sustainably.

Innovation from Startups: Solving Field-Level Problems

The Venetian’s Eureka Park, home to emerging startups, provided a view into construction’s next wave of innovation.

Autodesk demonstrated advancements in component modeling, reinforcing the growing integration between design intelligence and field execution. As digital models become more detailed and connected to real-world data, the gap between virtual planning and physical construction continues to shrink.

Cosito introduced AI-powered voice and sensor technology capable of automatically generating daily reports and field documentation. For an industry burdened by administrative paperwork, automation in this space could unlock significant productivity gains.

MIMO Detect presented underground pipe detection technology using ground-penetrating radar. While still in prototype phase and currently stronger in horizontal positioning than depth accuracy, the technology reflects ongoing efforts to reduce subsurface risk and prevent costly utility strikes. 

What stood out across the startup ecosystem was focus. Solutions were not speculative—they were targeted at real-world construction challenges: documentation, detection, visualization and efficiency.

Robotics and Spatial Computing

Robotics once again drew attention throughout the North Hall, with humanoid platforms, quadrupeds and service robots on display. However, the emphasis has shifted from novelty to application.

Exoskeleton technologies continue improving in wearability and ergonomic support, aiming to reduce strain injuries and extend workforce longevity. AI hardware companies such as DeepX demonstrated embedded processing systems powering autonomous vision and robotics applications. One particularly compelling development was spatial computing integrated through hard hat-mounted camera systems. By capturing and processing real-time visual data from a worker’s perspective, these systems aim to enhance hazard detection, progress tracking, and documentation. Robotics at CES 2026 felt less like spectacle and more like support—tools designed to augment skilled workers rather than replace them.

Workforce and AI Literacy

Technology alone does not build infrastructure—people do. Several CES sessions focused on preparing the workforce for rapidly evolving tools.

In the session “Next Gen Skills: Preparing Students for Tomorrow’s Tech,” leaders from Amazon, Oshkosh, CTA, and Tech Access emphasized AI literacy as a foundational skill. Amazon has committed $2.5 million to certify students in AI education and pledged to prepare four million students to use AI by 2028. Apprenticeship models are expanding to support data center construction and advanced infrastructure projects.

Key themes included:

• Prompt engineering as an emerging skill
• Understanding how to work alongside AI agents
• Collaboration between industry and education
• Ensuring technology remains accessible

Construction faces ongoing labor shortages and safety challenges. With less than 5% of the workforce employed in construction but accounting for nearly 20% of safety incidents, AI-powered safety systems and automation could play a transformative role.

New roles are already emerging: fleet autonomy managers, digital twin specialists, AI operations coordinators and construction data analysts. Preparing for jobs that do not yet fully exist is becoming part of the industry’s responsibility.

Connectivity: The Infrastructure Behind Innovation

Discussions involving FCC and NTIA leadership highlighted another critical factor: connectivity. Universal broadband access, spectrum policy, 6G development and WiFi 7 readiness are not abstract regulatory topics — they are foundational to connected construction ecosystems. Autonomous fleets, remote equipment management, real-time drone processing and AI-driven safety systems all depend on reliable, high-speed networks. As infrastructure becomes smarter, connectivity becomes as important as concrete and steel.

Lingering Thoughts Towards a Shift in Equipment Design

In conversations with industry leaders, an intriguing idea surfaced: As autonomy advances, equipment design itself may fundamentally change. If machines no longer require operators in cabs, what happens to traditional controls? Do we eliminate joysticks, operator compartments, and certain mechanical components altogether?

Autonomy does not just change how machines operate—it may redefine how they are built.

Looking Ahead

CES 2026 demonstrated that construction technology is no longer niche. It is integrated across AI, robotics, electrification, manufacturing and policy.

The industry is entering a phase where digital intelligence and physical infrastructure are inseparable. One key takeaway resonated: Technology should be deployed to solve problems, not simply to showcase innovation. That principle applies directly to construction. Adoption must be strategic, measurable and outcome-driven.

Autonomous fleets, AI assistants, spatial computing, electrified equipment and workforce AI literacy initiatives are not distant visions—they are active deployments.

Construction is not standing on the sidelines of innovation. It is helping build it.

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The post Building the Future: Construction at the Center of Technological Innovation at CES 2026 first appeared on Construction Executive.

The problem isn’t opportunity. It’s access. Construction companies can readily identify the processes that drain skilled labor without adding value: preparing bids, revising estimates, updating schedules, coordinating subcontractors and managing compliance documentation. Many of these tasks could be reduced from hours to minutes with the right AI-driven automation. Instead, they pile up on wish lists, stalled by overburdened IT or central AI teams that can’t keep pace with demand.

Since the rapid rise of generative AI, tensions have intensified. Technology leaders argue that business teams lack the expertise to build reliable, secure solutions. Project managers and sales teams counter that long development queues are strangling innovation and forcing them back to spreadsheets, email and manual rework. In some cases, field teams have taken matters into their own hands, adopting unapproved tools to meet deadlines and creating “shadow AI” that quietly introduces security and governance risks.

A Different Model

A growing number of firms are closing this gap with a decentralized AI model. Rather than routing every solution through a central development team, organizations are empowering frontline business users to design and build most automations themselves, using no-code platforms. With guardrails already built in, central IT and AI teams retain oversight, managing security, governance and integration while shifting their primary role to training, standards and scalability.

The timing matters. Construction is experiencing a surge in complex renovation work, particularly in class-A office space. As return-to-work mandates accelerate, owners are reconfiguring offices to improve comfort, collaboration and performance, projects that involve intricate design decisions, compressed timelines and intense competition. Speed to bid is increasingly becoming speed to win.

In a decentralized model, sales teams and estimators don’t wait months for a custom tool. They build solutions that help design and quote complex office renovations more efficiently. Generative AI can draft proposals that incorporate past project data, updated building standards and client-specific requirements, cutting proposal turnaround from days to hours. In a crowded market, that difference can decide a contract.

Beyond the Bid

Productivity challenges extend well past estimating. Modern office renovations increasingly incorporate performance standards tied to acoustics, air quality and sustainability. Open plenum designs, alternative wall assemblies and advanced ceiling treatments manage sound transmission and airflow while meeting sustainability goals. Evaluating these options traditionally requires multiple rounds of engineering analysis, revisions and cost checks.

Advanced AI tools can compress that cycle. Engineers and sales teams can simulate sound and air flow performance across design scenarios, quickly comparing trade-offs between budget, comfort and code compliance. Customers gain clearer visibility into how design choices affect outcomes. Project teams reclaim the hours spent on manual calculations and rework.

Under a decentralized AI framework, these tools don’t require a central development team to build from scratch. Business users assemble workflows using approved no-code platforms, drawing from validated data sets and engineering rules. Central IT ensures underlying models meet security and quality standards, while allowing rapid iteration as project needs evolve.

The Citizen Developer Model

The citizen developer model formalizes this approach in practice. Central IT and AI teams provide a standardized no-code platform, along with governance, training and support. Security controls, data access rules and best practices are embedded into the platform, reducing risk while accelerating deployment. Frontline teams then design solutions tailored to how work actually gets done.

In construction, that means tools for workforce allocation, supply chain coordination and change order management. Individually, each automation may save only a small amount of time. Collectively, they can move the needle on productivity across an entire project portfolio.

That cumulative effect is precisely what the industry needs. Saving 30 minutes per estimate or an hour on a weekly coordination report may seem marginal. Across dozens of projects and hundreds of employees, those savings translate into thousands of reclaimed labor hours and measurably lower operating costs.

Decentralized AI also strengthens risk management. Automated tools can scan contracts, specifications and correspondence to flag potential scope gaps or compliance issues earlier in the project lifecycle. Supply-chain workflows can monitor vendor performance and material availability, helping teams respond faster to disruptions. Tariff and customs documentation, increasingly relevant for imported materials, can be drafted and reviewed with greater consistency and speed.

Ducker Carlisle, for example, applied this mode internally, achieving a 3% reduction in operating costs within 90 days. The savings were driven not by a single large system, but by many small automations built by employees outside traditional IT roles. The firm is now helping construction and engineering clients apply the same playbook.

Governance Is the Foundation

Successful adoption requires discipline. Without clear structure, decentralized efforts can fragment into disconnected tools and inconsistent data. Organizations that get it right establish guardrails from the start—standardized platforms, approved data sources, clear ownership and accountability. Training ensures business users understand both the power and the limits of AI, while central teams focus on scaling what works.

The shift also demands a cultural change. Construction is traditionally cautious with new technology, particularly when it touches core operations. Decentralized AI asks leaders to trust frontline teams with new capabilities, while maintaining accountability through structured oversight. It also redefines the role of IT from gatekeepers to enablers, a shift that, for many firms, may be the harder change to make.

The Competitive Case

As return-to-work renovations, sustainability requirements and labor constraints continue reshaping the industry, the ability to move quickly is becoming a competitive differentiator. AI can address construction’s long-standing productivity problem, but only if it is deployed where work actually happens, not locked behind a central development queue.

Decentralized AI doesn’t eliminate the need for central expertise. It amplifies it, allowing small, skilled teams to support dozens of use cases across the organization. For construction firms ready to close the productivity gap, the fastest path forward isn’t waiting for one perfect solution. It’s trusting the people closest to the work with the tools to build their own.

SEE ALSO: WIRING THE AI ECONOMY: CONSTRUCTION SPENDING ON DATA CENTERS

The post Decentralized AI: A Faster Path to Construction Productivity Gains first appeared on Construction Executive.

Digital transformation is discussed everywhere in construction. What does it actually mean in practice?

In practice, it means fewer surprises. For many contractors, “digital transformation” sounds like a technology conversation. In reality, it is a control conversation. Construction companies have always relied on experience, project managers’ judgment and periodic reporting. That approach worked when markets were stable and growth was incremental.

Today, most nonresidential contractors are running several complex projects at once. Labor availability shifts week to week. Material commitments change quickly. Scope adjustments move through multiple layers of approval. If leadership receives information only at fixed intervals, it is already reacting to something that has been developing for days or weeks.

Digital transformation, when implemented properly, shortens the distance between what is happening in the field and what executives see at the portfolio level.

Why is real-time visibility more important now than it was five or 10 years ago?

Volatility has increased. That changes the math. In a stable pricing environment, small inefficiencies could often be absorbed. Today, margin compression happens quickly. A procurement delay combined with overtime labor and a pending change order can materially affect profitability before the issue is visible in traditional reporting cycles.

In one commercial portfolio, delayed reporting contributed to cost variance approaching 9% midway through execution. After implementing integrated dashboards that connected labor hours, committed material costs and change-order exposure, variance in comparable projects declined to approximately 3%–4%. The difference was not better craftsmanship. It was earlier visibility.

When deviation is identified in its early stages, it can be managed. When it surfaces late, it becomes damage control.

How does enterprisewide oversight differ from reviewing projects one at a time?

Reviewing projects individually often hides systemic patterns. A single project may show minor productivity issues that appear manageable. When those same issues are present across multiple projects, they become structural. Enterprise-level visibility allows leadership to see recurring themes: trade stacking during transition phases, procurement timing conflicts or documentation bottlenecks.

In one instance, portfolio analysis revealed consistent labor congestion during overlapping mechanical and electrical installation periods. Adjusting sequencing across projects reduced schedule volatility and improved labor efficiency across several sites at once. That type of adjustment is difficult to identify when projects are reviewed independently.

Enterprise oversight shifts the focus from project recovery to portfolio stability.

What impact does this have on financial planning?

It improves confidence in the numbers. Forecasting in construction is never perfect, but it becomes significantly more stable when operational data feeds financial projections continuously. In structured environments, forecast variance at mid-project milestones has narrowed to within 2%–3% of final outcomes. Prior to integration, deviations closer to 6%–7% were common.

For executive teams, that difference affects capital planning, liquidity management and growth decisions. When projections fluctuate widely, expansion feels speculative. When projections are consistently reliable, leadership can make strategic commitments with greater discipline.

How does digital operational control influence bonding relationships?

Sureties are evaluating predictability. Bonding capacity is not only about financial statements. It is also about operational control. Firms that demonstrate disciplined reporting structures, documented variance monitoring and consistent forecasting stability signal lower risk. That perception strengthens underwriting conversations.

In competitive markets, bonding credibility affects which projects a contractor can pursue. Operational transparency therefore supports strategic positioning, not just internal management.

What about insurance and liability exposure?

Documentation quality has direct financial consequences. Many disputes and warranty issues are not the result of technical failure. They stem from incomplete records or inconsistent approvals. When documentation is centralized and timestamped, and when scope adjustments follow structured workflows, ambiguity decreases.

Several organizations that integrated documentation into operational dashboards reported measurable reductions in dispute frequency and post-closeout claims. Fewer disputes mean less management distraction and reduced indirect cost.

Digital discipline in this context becomes risk containment.

Change orders are often cited as a source of margin leakage. How does integration help?

Informal change management is expensive. When scope modifications are approved verbally or documented inconsistently, revenue recognition lags and exposure increases. Structured workflows requiring quantified cost impact and formal acknowledgment reduce that risk.

In environments where digital change management was implemented, approval-cycle duration decreased by nearly 40%. That acceleration improved cash flow and reduced working capital strain. More importantly, it protected contract value by reducing ambiguity.

Workforce retention remains a challenge, especially in merit shop markets. Does real-time operational control influence workforce stability?

Yes, indirectly but meaningfully. When schedules fluctuate unpredictably, overtime spikes and crews are reassigned frequently, morale declines. Real-time workforce analytics allow leadership to rebalance deployment earlier and reduce reactive reallocation.

In one regional portfolio, improved oversight reduced overtime volatility by approximately 15%. That translated into more predictable scheduling and improved retention. Stability on the job site is increasingly a competitive advantage.

Cultural resistance can undermine transformation efforts. What differentiates successful implementations?

Clarity of purpose. When digital initiatives are framed as technology upgrades, they often encounter skepticism. When they are positioned as tools for improving operational stability and protecting margins, adoption improves.

Successful implementations typically begin with pilot deployments and limited scope before expanding enterprise-wide. Measurable improvements – reduced variance, improved forecasting accuracy, fewer emergency schedule adjustments – build credibility. Over time, transparency becomes part of operational culture rather than an imposed requirement.

Does operational governance provide competitive differentiation?

Increasingly, it does. Owners and institutional clients are evaluating contractor reliability with greater scrutiny. Firms that demonstrate disciplined oversight and predictable execution project stability. In procurement environments where pricing differences are narrow, perceived reliability can influence award decisions.

Operational governance strengthens that perception.

What are the long-term implications for firms that fully integrate real-time operational control?

The long-term implication is resilience. Construction will remain cyclical and volatile. Firms that rely solely on experience and periodic reporting will continue to face reactive management cycles. Firms that integrate operational data into executive oversight reduce uncertainty at the enterprise level.

Reduced uncertainty does not eliminate risk. It makes risk manageable.

Over time, that difference compounds. It affects margins, bonding credibility, workforce stability and growth discipline. Digital transformation, in that sense, is not a technology initiative. It is a structural shift toward sustained control.

SEE ALSO: HOW FIELD TECHNOLOGY IS TRANSFORMING CONSTRUCTION JOBSITES

The post Digital Transformation in Construction Management and Real-Time Operational Control first appeared on Construction Executive.

What are some of the trends/patterns you saw this year as they relate to construction technology?

When we were coming into 2025, we were thinking about the things that were going to have a large impact in the industry. I think we were scratching the surface on AI in those conversations, but that paid dividends much larger than many of us expected. The advancements in that space have just been so incredibly voluminous and fast that it has given us a lot of things to talk about. And I think when we talk about AI everybody goes right to Chat GPT and the LLMs, but there’s a lot more to that.

Procore spent all of last year doing research on our The Future State of Construction report—a five- to eight-year outlook on Contech. Some of the themes popping up were automation and augmentation—whether through AI agents or robotics—and I think we’ll only see them continue to accelerate in 2026. The good news there is that, when we surveyed construction leaders in 2024, 55% believed that [that type of tech] is really going to change the way that we work moving forward. That number has likely grown significantly in the past year. I think a lot of this automation and augmentation can make the industry a lot safer; it can allow people to actually spend the time on the work that they really, really want to do, which is actually building. We can automate a lot of those dull, boring, dirty, dangerous tasks. I think that’s what we’re going to see pulling into 2026 and we’re going to see a bigger payoff.

Are there any specific products you have seen throughout the broader industry that you think will become more mainstream in 2026?

There’s no doubt that we are going to see construction specific agents. You’ll see people start to really take advantage of things like agent builders and programs to use really specific industry knowledge and data sets to accelerate workflows. And they’ll be trained to do things that we know that people need to do on a jobsite everyday. A great example: Nobody went to school to be a civil engineer or a construction manager to process submittals. It’s a paperwork process that’s just incredibly intensive. It’s boring, but it has to get done. Those are things that are ripe for automation via agents.

The conversation I have with leaders at construction companies is they’re all trying to figure out what practical applications they can start with. It’s no longer a question of if they’ll use them; it’s how. Where it used to be a $100,000 to have a Boston Dynamics robot dog, now you can buy a similar quadruped robot at like $10,000 . And the integration at the software level, how much technical knowledge you need to have, is significantly changing as well.

People are realizing that it’s incredibly important to have really good data. That’s probably the thing that holds the industry back in some cases from being able to get the insights that we want. That’s where we are going to see the use of large language models that are really good at looking at large, structured data sets.

So, the technology is there for the mass adoption of these tools. The culture and the technical knowledge I think is what has to evolve very, very quickly, which is why I think you’re going to end up seeing a ton of upskilling in our space, which is really good because I think it allows us to bring in a lot of talent to the industry. We will probably see a broader workforce come into construction, and I think we’ll see those who are here really work on upskilling their talent to have the skills around these technologies that we need.

Where and/or how does a smaller contractor start to successfully create and implement an AI agent? How can a larger company adopt these AI agents with regulation/security in mind? How can they be sure that the data is being analyzed properly and safely?

I think of it as three buckets.

The first bucket: A small contractor 100% focused on building, but that wants to put these type of tools in the hands of its people because it’s going to help them get their job done. For those people, they have to rely on the technology vendors that they are already working with. A great example of this is that we’ve built out-of-the-box agents to do very specific workflows that we know are common across all of construction: RFI creation, daily log summary, submittal review, etc.

If you’re a smaller contractor that doesn’t have a lot of resources, you can still take advantage of those things today. Use the things that’s inside of the tech stacks that you already have. There are great LLM AI capabilities inside of Microsoft and Google. They are great for your day-to-day—summarize my emails, help me schedule meetings. They should be using those things because they’re probably baked into their tech stack already.

The middle bucket: People who have some technology already and more specific use cases that they want to tackle. This company will definitely be building their own processes and workflows in something like an agent builder. But they might also want to be able to integrate those agents across platforms. It’s not a completely custom agent that they’re building. It’s doing specific tasks based on data sets that it has access to, but it’s also within a very trusted environment for them.

The third bucket: Your larger, national and/or international companies. Now you’re talking about getting into a world where they are probably building their own agent orchestration platform, which may be something that is integrating into a program like Procore, but also many other systems because they’ve got their own custom data lake already built. They’ve invested a lot more in the infrastructure and they want to do much more advanced tasks. This is not about necessarily just helping to automate a submittal process. This is trying to help automate job set up, reviewing financials, maybe time sheets which are in your HR system. How do we reconcile all of those things? Maybe they’ve gone right to Chat GPT for an enterprise license or an open AI and are building out their own workflows inside of those systems that go across many other systems.

Those are the varying stages, but the one thing that’s consistent across all three of them is it has to be something that your people will trust. If they don’t trust it, they won’t use it. And it’s very hard to earn construction professionals’ trust. So, the change management or the rollout of these things is really, really important. It’s okay to experiment. It’s okay for things to not go right, but don’t roll things out to the entire organization until you have a level of confidence.

How can construction companies get ahead of the ban of Chinese-manufactured drones on federal projects yet still operate within their own means?

That’s a really interesting situation and I think what it all comes down to is truly understanding where your data is going and how it’s being captured and where it may end up. We just talked about AI and agents—It’s the same conversation there. You have to understand where your data’s going to go and what’s going to happen with it because it is an asset to you. And so when we talk about drones and robots, the reason that the price point is coming down on robots is there are a lot of international-based companies that have been developing this technology to drive the pricing down.

But the reality of it is, at the end of the day, I think understanding the control processes of where the data actually goes and gets processed is really important. And then you choose to work with a partner that you know where your data is going and who you trust.

If you just look at reality capture as a whole here—drones, robots walking around the jobsite, humans walking around the jobsite—there’s not going to be a slowdown in capturing photo and image and video of your jobsite. It’s only going to accelerate. We’re going to see more wearables with cameras in them. We’re only going to see more and more digital capture of the jobsite through photo and video than we’ve ever seen before.

So as just a general statement, whether it’s drones, whether it’s agents, I think we do have to be more aware of where the data is going, especially based on the project. You need to be a good steward of the data for the project, for the owners, for the others that are involved and for your own company.

How will the development of construction technology affect the broader construction economy in 2026?

These high-tech industries, which are investing a tremendous amount in building right now, are really pulling the industry forward. It’s megaprojects, it’s battery plants, it’s data centers. All of these things are providing more backlog than most companies ever had. That’s why I think the confidence is there because there is a tremendous amount of investment in that infrastructure.

The technology that is coming to our industry is finally coming into its own in many ways; it’s going to start to pay down some of what we talk about in The Future State of Construction report: How do we actually influence the productivity of our industry? How do we finally make a dent in that 28% of rework? I think people are feeling good about what they’re seeing with construction technology that we’re actually starting to take a big bite out of that apple.

SEE ALSO: HOW TO BUILD A PROPER CONSTRUCTION-TARGETED TECH STACH

The post Contech for Christmas: What Technologies Contractors Are Seeking Most at Year’s End first appeared on Construction Executive.

If a construction company is just starting to build their tech stack, what should they look for first?

In our industry, the gold standard foundation is an end-to-end field service management platform. These systems bring scheduling, dispatch, invoicing, payments and reporting into one hub. For smaller contractors, an FSM ensures day-to-day operations are efficient and cash flow is healthy. For larger or more complex firms, that FSM foundation often needs to connect into an ERP or accounting-first platform that can scale with multiple divisions, entities or business units. Without that strong base of clean, centralized data, every other tool—AI, estimating, project management or marketing—will struggle to deliver real ROI.

How should construction companies build out their tech stack—everything at once or product by product?

It’s tempting to go all-in, but the most successful companies roll out product by product, in phases. Start with the most business-critical area (usually job management or accounting). Once adoption is strong and workflows are documented, move into complementary tools like CRM, estimating or marketing automation. Layering systems this way avoids overwhelming the team and ensures each tool is fully utilized before moving on.

Where should companies look for quality tech solutions beyond the big brand names?

It’s easy to get overwhelmed by all the tech noise in the market. The most important step is to start with a clear understanding of your business needs and what your primary FSM platform already offers. From there, you can identify true gaps or areas where enhancements will drive ROI.

Once you have that clarity, evaluating third-party integrations becomes much simpler. Look to your FSM’s partner marketplace first, since those tools are designed to integrate natively. Beyond that, industry associations, peer groups and distributor networks can be excellent sources of vetted solutions. Smaller, field-built tools often offer faster support and flexibility, but they should be layered in only where they enhance your FSM foundation, not distract from it.

For companies with existing stacks, what are signs they need to upgrade?

Look for red flags like:

• Teams running spreadsheets or shadow systems outside the core platform
• Duplicate data entry across systems
• Frequent complaints from field teams about usability
• Reporting that’s delayed or inaccurate

These are all signals that your tools aren’t keeping up with how your business is operating today.

Which products usually need to be upgraded first/most frequently?

We most often see upgrades needed in:

• Accounting/ERP (to handle scale, multi-entity or job costing)
• CRM/estimating tools (as sales and project pipelines grow)
• Communication tools (to keep office and field aligned)
• Field apps and marketing platforms also evolve quickly, so staying current there matters

How does evolving your tech stack improve longevity?

Technology isn’t just a cost, it’s an asset that compounds. Each upgrade makes the company more efficient, more attractive to employees who want modern tools, and more appealing to investors or acquirers who value clean, centralized data. Evolving your stack ensures the business can pivot with market shifts rather than getting locked into outdated workflows.

How can a smaller company keep up financially with the pace of changing tech?

Focus on ROI-driven priorities. Start with tools that generate or protect revenue—job costing, invoicing, payment processing or lead management. Many platforms offer modular pricing so you can add functionality as you grow. Also, explore rebates or co-op dollars from manufacturers and distributors who often subsidize tech adoption.

What should their priorities be for best ROI if they must pick and choose?

• Cash-flow tools first: payment processing, AR automation, or scheduling/dispatch
• Customer-facing tools second: CRM, estimating, communication apps
• Efficiency tools third: automation, integrations, or BI dashboards

The key is to invest where technology will have the fastest and most visible payback, then reinvest those gains into expanding the stack.

SEE ALSO: EXECUTIVE INSIGHTS 2025: LEADERS IN CONSTRUCTION TECHNOLOGY II

The post How to Build a Proper Construction-Targeted Tech Stack first appeared on Construction Executive.