Key takeaways from the conversation

• AI is reshaping the jobsite. Contractors are using real-time data to improve project planning, utilisation and safety.
• Every site is unique. AI’s ability to process unstructured data makes it ideal for dynamic, ever-changing construction environments.
• Predictive insights reduce risk. From safety monitoring to emissions tracking, AI helps contractors detect issues before they escalate.
• Data is the foundation. Companies that structure and share site data today will be best positioned to scale AI tomorrow.

Understanding the contractor’s reality

No two construction sites are alike, and that, according to Mikkel Dalgas, is exactly what makes artificial intelligence such a powerful fit for the industry.

“In construction, everything changes all the time. Every site is unique,” said Dalgas. “AI gives us a new way to understand what’s happening and to make better, faster decisions.”

Unlike repetitive industrial environments, contractors manage constant variation from terrain and weather to team composition and equipment mix. Traditional tools struggle to interpret that level of change, but AI can extract patterns from unstructured data to reveal trends that humans might miss.

From data to decisions

Dalgas emphasised that AI in construction depends on the right data foundations. With Trackunit collecting machine and tool data from hundreds of thousands of connected sites globally, the next step is training AI systems that can recognise site-specific challenges and opportunities.

“To make an AI make a difference, you need a lot of data,” Dalgas explained. “When we train domain-specific models, we can benchmark utilisation, predict progress and even recommend next steps.”

This shift from data collection to prediction aligns with broader industry trends. McKinsey & Company notes that AI is rapidly advancing beyond experimentation to deliver tangible value across project management and construction planning, helping companies reduce uncertainty and improve productivity.

“To make an AI make a difference, you need a lot of data,” Dalgas explained. “When we train domain-specific models, we can benchmark utilisation, predict progress and even recommend next steps.”

This shift from data collection to prediction aligns with wider trends in the industry. A recent McKinsey & Company report on AI in engineering and construction found that machine learning models can improve project schedule accuracy by up to 20 percent when combined with real-time site data.

Predicting progress. Preventing delays

For contractors, the ability to compare live utilisation data against thousands of similar projects is a game-changer. “AI will help us detect deviations early, benchmark progress and even get recommendations on what to do next,” said Dalgas.

By continuously analysing data from machines, tools and workers, AI can flag performance issues before they impact timelines. The BuiltWorlds 2025 AI Benchmarking Report found that nearly two-thirds of construction firms rate their AI maturity as “average” or better, yet only 27% have made it central to their strategy – showing how much opportunity remains for proactive adopters.

Meanwhile, Engineering News-Record (ENR) reports that the industry is finally “moving beyond hype” and integrating AI directly into site workflows such as safety monitoring and equipment placement, evidence that adoption is accelerating at the operational level.

Making sites safer and more sustainable

AI is not just about productivity; it is also a safety and sustainability tool. With vision-based systems improving rapidly, Dalgas sees AI assisting contractors in detecting hazards and monitoring compliance in real time.

“We will soon see AI with near-human levels of vision, detecting risks and preventing accidents before they happen — Mikkel Dalgas, CTO at Trackunit.

Beyond safety, Dalgas pointed to the opportunity to reduce idle time, energy use and emissions. Machines left running unnecessarily or deployed inefficiently drive both carbon impact and cost.

“AI can make fine-grained optimisations where each adjustment is small, but the combined impact on emissions and performance is huge,” said Dalgas.

These insights align with findings from PBC Today, which note that 70% of construction professionals believe AI will drive sustainability improvements, yet fewer than half have implemented tools to measure progress.

Preparing for the AI-enabled jobsite

When asked how contractors can begin their AI journey, Dalgas’s answer was clear: focus on data.

“Think about what structured data you already have. The companies who start collecting and contextualising their data today will be the ones leading in a few years,” he advised.

He expects to see AI become an everyday assistant on the jobsite, built into machines, phones and platforms that guide workers, reduce waste and optimise performance.

For contractors, the message is simple: start small, stay practical and use AI to enhance, not replace, the human expertise that defines great construction.

About the series: AI in Construction

AI is changing the game for the construction industry, unlocking new possibilities in efficiency, safety, and collaboration. In this series, industry leaders and experts dive into how AI is being integrated across workflows, overcoming key challenges and paving the way for more intelligent, innovative construction practices. Whether it’s predictive maintenance, workforce transformation, or data-driven decision-making, we’ll uncover how AI is driving progress and shaping what’s next for construction.