13 Global Construction AI Companies Powering Projects in 2025

Construction AI companies are changing how real projects get delivered. Bouygues used AI to cut 140 tonnes of steel on a metro build. STRABAG forecasts delays with OpenAI models. Mastt gives project owners instant risk alerts and AI-powered dashboards across their entire portfolio.

These are real results, not pilot tests. Real projects, running faster, with fewer delays and surprises. If you're looking for construction companies using artificial intelligence in 2025, start here.

To understand the bigger shift behind these tools, explore how AI in construction is changing the way we build.

1. Mastt: AI Construction Platform for Owners and Consultants

Mastt is one of the few construction AI companies built specifically for project owners, consultants, and client-side managers. Its platform uses artificial intelligence to automate reporting, predict risks, control budgets, and simplify contract management across capital works portfolios.

On a $250 million terminal upgrade, Newcastle Airport’s team used Mastt to replace spreadsheets and manual reports. They cut reporting time by over 10%, gained live progress visibility, and reduced admin effort by hours each week.

Instead of chasing data from multiple sources, project leaders used Mastt’s AI-powered dashboards to track budget, risk, and performance in one place. Here’s how Mastt uses AI to support owner-side project delivery:

• Automated dashboards that generate visual reports in minutes using real-time project data
• AI-powered risk tracking that flags delays, cost shifts, or early warning signs based on live inputs
• Predictive forecasting that shows future schedule and cost overruns before they hit
• Contract automation that manages claims, certificates, and compliance without manual work

CARAS used Mastt across 70+ projects to automate portfolio reporting. Instead of siloed spreadsheets, their entire capital program was visible in one unified view. The platform auto-generated reports, flagged issues, and helped meet compliance faster.

On a $32 million school project, Oakhill College used Mastt’s cost and risk tools to manage complex risks and avoid budget blowouts. They tracked forecasts daily, and the AI helped them catch potential problems before they escalated.

Mastt also integrates with tools like Power BI, SAP, Procore, Primavera P6, and Oracle. This means your financials, schedules, and contracts sync into one AI-enhanced reporting engine - purpose-built for construction owners, not general contractors.

If you're running capital programs or managing multiple live projects, Mastt replaces slow, error-prone reporting with a smart, automated system that gives you full control.

2. Bouygues Construction: AI-Powered Design and Scheduling

Bouygues Construction uses AI to optimize design, reduce waste, and plan complex builds faster. On the Bagneux metro station project in Paris, their team used AI-driven engineering to redesign a retaining wall. That change cut 140 tonnes of steel, lowering both cost and embodied carbon before construction even started.

They also deploy ALICE Technologies, an AI scheduling platform that runs millions of build sequence simulations. Teams use it to test crew sizes, shift timing, and resource plans across high-risk civil works.

Instead of relying on fixed schedules, Bouygues can adjust delivery strategies early using AI to see which option gets the job done quicker and cheaper. Bouygues applies AI across real construction phases:

• Using AI in design engineering to reduce materials and optimize structural forms
• Running AI-driven schedule simulations to improve speed and reduce delivery risk
• Supporting tendering with validated construction logic and risk-tested build plans
• Adjusting live schedules based on crew availability, site conditions, and equipment timing

This AI-driven approach helps Bouygues cut waste, control costs, and deliver high-stakes infrastructure with more certainty. Whether it’s a rail project, tunnel, or city precinct, their teams use AI to make better decisions long before boots hit the ground.

3. STRABAG SE: Risk Forecasting with OpenAI

STRABAG SE uses artificial intelligence to forecast project risks before work starts. Their AI system, built with Microsoft Azure and OpenAI, compares upcoming projects to thousands of completed ones. It analyzes early-phase data to detect where delays, cost issues, or safety concerns are most likely to appear.

On live infrastructure and tunnel jobs, STRABAG’s teams use this model to test risk across design types, locations, and delivery strategies. The system reaches up to 80% prediction accuracy using only a few months of planning data.

It also brings in external sources like wind speeds, rainfall patterns, and site-specific logistics to catch problems before they escalate. The AI supports better planning, safer execution, and smarter bidding across high-risk civil works.

• Forecasting time and cost risks by matching against historical project outcomes
• Using OpenAI to evaluate risk across location, scope, and delivery strategy
• Identifying crane downtime or logistics delays caused by local weather data
• Helping teams avoid high-risk bids by testing real scenarios in early stages

Teams also use the AI model after construction bidding to reassess project risk based on changing inputs. It updates live as more data becomes available so planners can adjust before risk turns into rework. That gives STRABAG tighter control during both preconstruction and delivery.

4. China State Construction: AI Safety on Smart Sites

China State Construction uses AI across large-scale infrastructure projects to improve safety, track progress, and reduce on-site risk. Their 5G smart site system integrates AI with cameras, sensors, and mobile devices to monitor real-time activity and automate supervision.

On multiple metro, tower, and industrial projects, CSCEC deployed computer vision AI to detect PPE violations, trip hazards, and zone breaches without needing human spotters. The system feeds into a central platform, giving managers live updates across the entire jobsite from a single dashboard.

These AI tools are built directly into daily site operations, not just pilot programs.

• Monitoring worker behavior to detect missing hardhats, harnesses, and vests
• Scanning zones for unauthorized access or unsafe conditions using vision AI
• Linking BIM with site footage to verify build accuracy in real time
• Supporting remote inspections through smart glasses and AI overlays

CSCEC also uses AI-powered radar analysis to map underground utilities before digging. This helps avoid strikes and keeps complex projects on schedule. With full data visibility from mobile to control room, their smart sites make oversight faster, safer, and more precise.

5. Bechtel – Neural Scheduling for Megaprojects

Bechtel uses artificial intelligence to plan and manage large-scale, high-risk infrastructure projects. Their teams developed a spatial neural network model that simulates complex construction schedules, using AI to identify faster and more efficient sequences across thousands of interdependent tasks.

On a petrochemical facility, the AI analyzed piping, steel, and modular workflows as 3D components. It found a more efficient construction path that reduced total build time without adding labor or cost. The neural engine treated scheduling like a puzzle, testing millions of sequencing options before selecting the best.

This model powers smarter planning and gives Bechtel tighter control over time, labor, and delivery risk.

• Running neural-network scheduling simulations to test millions of task sequences
• Predicting risk in large builds using machine learning models trained on real project data
• Optimizing modular construction by identifying off-site opportunities based on logistics
• Using predictive analytics to detect early warning signs in productivity and schedule

Bechtel also partners with nPlan and IBM Watson to scale these tools across megaproject portfolios. On a recent semiconductor facility, the AI flagged a risk in trade sequencing weeks in advance, giving planners time to shift crews and avoid disruption. These systems continue learning from each project to make the next one more predictable.

6. Vinci Construction: AI for Site Capture and Utilities

Vinci Construction uses AI to speed up site tracking, improve quality, and map underground utilities with precision. They rolled out OpenSpace, a tool that uses 360° cameras and computer vision to capture site progress. No one needs to take photos manually. You walk the site, and the AI does the rest - mapping, tagging, and comparing work to plans.

Across 25 projects in the UK, Vinci saved over 5,200 work-hours just by automating progress photos. Engineers now check the site remotely, see what’s done, and spot what’s missing without walking through mud or scaffolding.

But Vinci didn’t stop there. They also use AI to:

• Compare live site images to BIM models and flag mismatches
• Detect incomplete or faulty installations
• Track work across time for claims, QA, or audits
• Map underground services using AI-driven radar interpretation

On civil works, Vinci partnered with Exodigo to scan sites for hidden pipes and cables. The AI processes radar, electromagnetic, and LiDAR data to show what’s buried - no digging required! That prevents strikes, redesigns, and surprises.

7. Larsen & Toubro: AI in Resource and Safety Efficiency

Larsen & Toubro uses AI to reduce waste, improve safety, and track resources across more than 300 construction sites. They built their own digital platform with AI tools to monitor how materials like steel, fuel, and cement are used on live jobs.

One tool cuts steel waste by predicting the most efficient way to cut rebar based on design specs. The system plans where to cut each piece, minimizing leftover scrap.

On multiple high-rise projects, this reduced steel use by several percentage points - a major cost and carbon win at L&T’s scale. They also track diesel with IoT and AI. If fuel use spikes, the system checks for leaks, theft, or equipment misuse. This keeps budgets tight and machines running clean.

Here’s where their AI makes a real difference:

• Steel optimization reduces scrap before cutting starts
• Fuel tracking detects waste and flags suspicious burn rates
• Safety cameras spot missing gloves, helmets, or harnesses using computer vision
• Drone data feeds AI models for accurate progress tracking and reporting

All of this runs through one centralized system. Over 200 L&T projects now use it for BIM, materials, site data, and safety. For teams managing busy construction programs, this AI ecosystem gives you full visibility and cuts waste without slowing down the job.

8. ALICE Technologies: AI Simulation for Scheduling

ALICE Technologies helps construction teams plan better by running millions of AI-generated schedules before a job starts. The software takes your BIM model, site constraints, and construction methods and then uses AI to test every possible sequence. It shows which plan will finish faster, cost less, or lower risk.

On the HS2 high-speed rail project in the UK, the Align JV (Bouygues, Sir Robert McAlpine, VolkerFitzpatrick) used ALICE to plan the Colne Valley Viaduct. The team simulated different crew setups, shifts, and sequencing strategies. One AI-generated change (adding a second pile cap crew) helped them reduce risk and increase float without extending the timeline.

Contractors use ALICE AI to:

• Explore what-if scenarios in minutes during preconstruction
• Test resource tradeoffs like crane counts, shift timing, or crew size
• Re-sequence work instantly when delays or design changes hit
• Submit bids with proven delivery logic instead of guesswork

Bouygues Construction also uses ALICE across global infrastructure bids. On one tunnel project, they used it to test the impact of adding a second tunnel boring machine. The AI measured time saved, cost impact, and downstream effects, all before a shovel hit the ground.

9. Turner Construction: Smart Cranes and Field Analytics

Turner Construction uses AI on active jobsites to track progress, manage crane operations, and boost field productivity. They partnered with Versatile AI to deploy CraneView, an AI-powered sensor that attaches to the crane hook. It records every lift, then uses computer vision and machine learning to classify what’s being picked, how long it takes, and how efficiently the crane is used.

On the Manchester Pacific Gateway project in San Diego, Turner used CraneView on two tower cranes. The AI showed when cranes were sitting idle or lifting uneven loads. With that insight, the team adjusted crew schedules, balanced the work, and demobilized one crane earlier than planned. That saved both time and cost.

Here’s how Turner applies AI on real projects:

• Tracks crane usage to improve equipment planning and reduce downtime
• Analyzes lifting cycles to optimize trade coordination and workflow
• Detects trends in site productivity through automated lift classification
• Enhances safety by flagging risky lifting patterns and equipment strain

They’ve also piloted AI systems that scan site cameras for safety violations. These tools automatically check if workers wear PPE, enter restricted zones, or move through unsafe paths. Instead of waiting for manual reports, superintendents get real-time alerts.

10. Buildots: AI for Progress Tracking

Buildots uses computer vision and AI to automate progress tracking on construction sites. Workers wear a 360° camera during routine site walks. The AI matches those images to the BIM model and schedule, then checks what’s been built and what’s still pending down to the last duct, pipe, or partition.

On a project with NCC, a leading Nordic contractor, Buildots helped increase task completion by 230%. The platform highlighted delays, tracked each trade’s output, and reduced the time spent reporting by 70%. Instead of walking the site with a clipboard, managers reviewed AI-verified progress through the dashboard.

Buildots gives construction teams tools to:

• Detect missing or incorrect installations in real time
• Compare actual site conditions to planned models
• Track each trade’s progress using visual data
• Flag slowdowns or delays before they affect downstream work

UK contractor Sir Robert McAlpine used Buildots across over 260,000 square meters of live projects. They used it not just for tracking, but for billing and QA. The AI records a time-stamped, visual audit trail—so if a subcontractor claims a task is done, the system can confirm it instantly.

11. Doxel: AI-Driven Site and Cost Insight

Doxel uses AI, LiDAR, and computer vision to give construction teams real-time feedback on cost, progress, and productivity. Their platform scans job sites using autonomous robots or handheld devices, then compares that data to the BIM model and the schedule. The system shows exactly what’s been installed, how fast it’s happening, and what it means for cost and delivery.

Corscale, a U.S. data center developer, used Doxel on major projects in Virginia. Their team relied on Doxel’s AI to speed up delivery timelines and reduce waste. The platform helped them adjust crews and catch schedule slips before they snowballed into delays.

Doxel’s AI tracks and analyzes:

• Work-in-place using 3D laser scans and visual data
• Weekly installation rates per trade for productivity insights
• Discrepancies between billed work and actual progress
• Risks in cost, time, or scope by comparing planned vs actual

On one healthcare project, Doxel flagged a slowdown in wall framing. The GC brought in a second crew and avoided a three-week delay. On another site, Doxel’s scan caught a slab deviation before rebar went in, avoiding costly rework.

12. Dusty Robotics: Robotic Layout with AI

Dusty Robotics builds AI-powered layout robots that print digital plans directly onto the construction floor. Their flagship tool, the FieldPrinter, takes the BIM model and uses it to mark walls, doors, hangers, and sleeves (everything) at full scale on concrete slabs. No tape, no chalk, no human error.

Contractors like McCarthy Building Companies and Weitz used Dusty Robotics on large healthcare and industrial builds. Layout that once took a crew a week was finished in a day or two.

On one hospital tower project, the robot printed every hanger location from the coordinated BIM model, ensuring the next trade got it right without rework. Dusty’s robot uses AI and sensors to:

• Navigate active sites safely and precisely
• Convert digital models into print paths on the fly
• Detect obstacles and reroute in real time
• Maintain millimeter-level accuracy across large floorplates

It also logs every layout it prints. That record becomes a reference point for site teams, inspectors, and quality checks.

One Skanska team in Finland noted that the printed layouts were so clear and accurate, crews finished rough-ins faster and with fewer questions. That kind of speed and clarity save days and keep trades moving in sync.

13. Obayashi Corporation: Generative Design and AI Robotics

Obayashi Corporation uses AI to speed up design, cut down labor pressure, and automate repetitive site work. In 2022, they launched AiCorb, a generative design tool built with SRI International.

AiCorb lets designers input simple massing or sketches, and then the AI instantly creates a range of façade options. Once a design is chosen, the system auto-generates a 3D BIM model, ready for review or coordination.

Teams used AiCorb on live building proposals. On one commercial job, Obayashi’s designers tested dozens of façade concepts in minutes, instead of spending weeks in early design. Then they pushed the selected design straight into modeling.

Obayashi also invests heavily in AI-driven robotics:

• Partnered with SafeAI to retrofit a Caterpillar 725 dump truck with autonomous navigation and an electric powertrain
• Built in-house robots for concrete finishing, rebar layout, and inspection tasks
• Used drone-AI tools to scan progress on remote dam projects
• Applied image recognition to detect cracks and concrete defects before handover

In 2023, their test site in California ran a fully autonomous haul cycle using the retrofitted dump truck. The vehicle navigated, dumped, and returned on its own - no driver involved. That same year, Obayashi opened a Construction-Tech Lab in Singapore focused on developing and scaling AI and robotics across Asia.

Construction AI is Ready - Are You?

AI in construction is already part of the job. These companies are using it to track progress, control costs, flag risks early, and keep work moving without delays or guesswork.

If you're managing projects or reporting across a portfolio, now’s a good time to look closer. These tools are built for real teams, solving real problems. You don’t need a full digital overhaul. You just need to know where AI can take weight off your shoulders.