It’s not a secret that many of us use AI assistants like ChatGPT; and many believe we are at the very start of a revolution that will profoundly reshape human society. For the construction industry, this transformation brings both immense opportunities and critical questions, says Benedict Wallbank, Partnerships & Digital Construction Strategy Manager at Trimble.
The vast bulk of AI applied in the construction industry today is “narrow AI,” which is trained to perform a single task, often better and faster than a human can. This is the only type of AI that is currently in use, powering everything from chat bots to workflow automation. However, a more transformative change is on the horizon: AI with autonomous, agent-like behavior that can plan, make decisions, and execute complex tasks with less human input.
The next wave: Agentic AI and new business models
Greater change is on the way in the form of Artificial General Intelligence (AGI), also known as Agentic AI. Unlike narrow AI, AGI can apply previous learnings and skills to accomplish new tasks in a different context without needing to be retrained by humans. This allows it to learn and potentially perform virtually any intellectual task a human can.
Jari Heino, Vice President & GM, BIM & Engineering, Trimble Finland
This evolution will have profound economic implications. According to Jari Heino, Vice President & GM, BIM & Engineering at Trimble in Finland, our entire business model may be affected. “AI agents will eventually work somewhat independently, which opens up a whole new world,” Heino states. “Which of our tasks can—and should—AI take over?”.
Solving construction's core challenges
The interest in AI within the construction sector is significant, with many seeking to understand its practical value. The true potential of AI lies not in replacing humans, but in eliminating the tasks that humans shouldn’t be doing in the first place.
Redirecting human potential
By automating repetitive, cognitively mundane, and dangerous work, AI frees up human capital to tackle more pressing challenges. “We're confronting twin crises of labor scarcity and environmental urgency,” explains Heino. “Time spent on repetitive tasks that could be automated ultimately represents squandered human potential. AI can redirect our intellectual capital toward our most pressing challenges rather than consuming it with routine. The result isn't merely efficiency—it's a fundamental shift in what construction professionals can accomplish.”
Unlocking trapped data
One of the industry's most persistent challenges is fragmented data. A plethora of proprietary formats means that information gets trapped and value is lost at every project handover. While standards are important, forcing everyone to work the same way is not a practical solution. Instead, AI can organize data behind the scenes, allowing teams to maintain flexible work practices while achieving data harmony.
Benedict Wallbank, Partnerships & Digital Construction Strategy Manager, Trimble
Benedict Wallbank, who is also a non-executive director at NIMA (formerly the UK BIM alliance), elaborates on this potential: “I’ve been obsessed with the challenges of data interoperability and how we efficiently get to quality whole life asset data for decades. At NIMA, so many of our current discussions are on how AI will help us achieve that goal. My personal view is that Agentic AI will offer much of the solution. Do we still need classification and standards? Yes we do, but AI offers the potential ability to identify and map data currently trapped within documents, drawings, models, scans, and reality capture.”
Industry-native AI in action
While the world has seen great strides in general-purpose AI, attention is turning to industry-native solutions that speak the language of construction. These specialized tools are focused on solving practical problems, understanding context and integrating with existing workflows.
Within Trimble, AI adoption is already widespread, with developers using it to speed up code writing and enhance products across nearly all sectors to enhance operations, from design and modeling to field operations. AI enables users to modify 3D models with text prompts, automate geometry creation and classify models efficiently. It performs automated document classification, checks compliance in BIM models, analyzes change orders, identifies road defects and runs energy simulations. In the field, AI can monitor site safety by identifying PPE compliance and hazard zones, and compares scans to models to detect deviations. AI also aids in finding content, creating materials and detailing designs, providing comprehensive support for various enterprise needs.
Navigating the future with trust and responsibility
As AI becomes more autonomous, questions of trust, accountability and regulation are critical. Global approaches to regulation vary. The EU is taking a centralized approach, establishing a shared supervision and enforcement regime. The US has opted for a lighter touch, leaving regulation to existing laws and individual states to encourage innovation, while the UK has set out five key principles to be policed sector by sector.
The more we hand over tasks to autonomous systems, the more important it becomes to define when a human needs to be involved. Heino notes, “We build systems around the reality of human fallibility, yet we expect near-infallibility from automated systems. This higher standard shows that entrusting technology with life-or-death decisions requires an extraordinary degree of reliability.”
The AI genie has escaped its bottle, and it's reshaping the industry daily. The firms that thrive won't be those that race to implement every new innovation, but those that ask deeper questions: Which human capabilities should we amplify? How do we preserve the irreplaceable judgment that comes from years in the field? The organizations that navigate this transition with strategic clarity, understanding that AI serves the builder rather than replacing the craft, will forge the sustainable path forward.
