FROM AUTOMATION TO AUTONOMY

START SMALL, SCALE UP

“There seems to be a shift of focus from when we were going all-in on autonomy to taking a series of steps to get more automation that one day will lead to autonomy,” says Ian Welch, Trimble’s engineering director with civil construction field systems.

“Human intelligence is not just data. It is our intuition,” says Burcin Kaplanoglu, PhD, head of Oracle Industry Labs. “It’s hard to beat someone who has spent two decades in construction. But that is the promise. AI is coming and we are embedding those things as features into our products.”

JOHN DEERE REVEALED THEIR AUTONOMOUS ARTICULATED DUMP TRUCKS (ADT) AT THE RECENT CONSUMER ELECTRONIC SHOW 2025 IN LAS VEGAS, US

The goal itself is simple and not unlike the goal of GPS/GNSS guided earthmoving; to make less-skilled operators better and skilled operators faster and to do the job safer, better, and greener.

AI will play a role in figuring out to optimise a process, says Welch. “That’s step one in the journey,” he says. Step two is more difficult. “What do you do when things don’t go as planned?” AI will need to make real-time decisions, and I think we’re still a way off from that.”

PHASED APPROACH Neil Williams, president Machine Control Division, Hexagon’s Geosystems division, says the construction industry has transitioned from the initial hype around fully autonomous construction equipment to a more practical, phased approach. This includes five levels of autonomy:

MANUAL OPERATION – Full human control with minimal digital assistance.

ASSISTED CONTROL – Automation aids operators with guidance and automatic blade control.

PARTIAL AUTOMATION – Machines handle some tasks autonomously but need operator oversight. CONDITIONAL AUTONOMY – Machines operate mainly independently in specific conditions with minimal human intervention.

BURCIN KAPLANOGLU, PHD, HEAD OF ORACLE INDUSTRY LABS

DAVID VEASY, JOHN DEERE’S SENIOR PRODUCT MANAGER OF AUTONOMY

FULL AUTONOMY – Equipment functions entirely on its own, adapting in real-time (not yet an industry standard).

Currently, the industry is progressing through Levels two to four, while keeping operators in control, says Williams.

Instead of full machine autonomy, the industry is moving toward more semi-autonomous workflows, where machines collaborate more seamlessly with operators and leverage AI to enhance productivity and reduce errors.

This makes automation a foundational tool that transforms operations, setting the stage for full autonomy in the future while delivering tangible benefits now, says Williams. These include enhanced machine control, AI-driven analytics; and realtime data integration to streamline workflows, boost safety, and cut waste.

According to Hexagon’s 2023 Autonomous Construction Tech Outlook, 84% of technology decision-makers at general contracting firms in North America, the UK, and Australia had adopted some form of autonomous technology in the previous year.

Autonomy isn’t a distant goal, comments David Veasy, John Deere’s senior product manager of autonomy. But it will come in focused autonomous operations. These autonomous operations will be simple at first, such as hauling material from point A to point B, and grow in scale over time, focusing on minimising the amount of interaction needed to keep the machine in the autonomous mode.

John Deere revealed their autonomous articulated dump trucks (ADT) at the recent Consumer Electronic Show 2025 in Las Vegas, US. ADTs in a quarry application carry material from point A to point B and repeat that route without too much variation, making it one of the ideal applications for an autonomous machine. Given a shortage of skilled workers, the autonomous ADT eliminates the operator and enables customers to use that person for more complex tasks and equipment.

SIMPLE MACHINES FIRST

The machines most likely to incorporate autonomy in the future will be the ones with the simplest applications, says Welch. Several years ago, Trimble developed the software and sensors for a semi-autonomous compactor the company frequently demonstrates.

CATERPILLAR SAYS THAT IT HAS HAULED MORE THAN 8.6 BILLION TONNES OF MATERIAL WITH ITS AUTONOMOUS TRUCKS

Compactors were the logical choice because they only do one thing, and it is easy to proscribe that path and optimise that process, he says.

An excavator is more complex and is also called on to do many different tasks in different conditions, says Welch. Likewise with dozers. “We are a way off from automating those machines now but there are a lot of people working on it. We’ll see more of it happen as we see digital construction become more widespread. But without that we can’t really train the machine.”

“You can get to 90% autonomy, but that last 10% is hard to achieve,” says Kaplanoglu. And we, as humans, have a very low tolerance for machine failure and fault. We are tolerant towards human mistakes, but not machine mistakes. Consistency, reliability and accuracy is pretty important in the construction space.”

TO SEE AND THEN DO

At the Oracle Industry Lab, the team uses OCI Vision Services to analyse photos and images and then trains the software to recognise elements in the images and compile the information needed to utilise that asset.

A hypothetical example he cites is when an HVAC (heating, ventilation and air conditioning) unit shows up on a jobsite without documentation. A quick photo sent to the cloud can identify the unit, and if properly trained, the software will not only also conjure up the specs, installation instructions and any other relevant information. Enhanced by AI learning the software will produce all the information required, integrated into one response, without the worker having to go to multiple websites or open multiple screens of information to get what they need.

AUTONOMOUS MACHINES WILL NEED TO BE CONSTANTLY MONITORED

IMAGE: ADOBE STOCK

Some companies are taking that visual learning model a step further and programming robots to ‘see’ a particular action, learn it, and then repeat it. The tech term for this is ‘imitation.’ Kaplanoglu cites an example where a robot records professional athletes and then recreates those movements itself.

The implication is that it may be possible in the future for a dozer to record another dozer performing a task, store that information in the cloud and then use that information to duplicate the task without an operator in the seat. “That, I think, is the biggest promise,” says Kaplanoglu. “That is where it’s heading and there are tons of money and research going into this space.”

UPSKILLING YOUR CREW

“Automation is skilling jobs, not killing them,” says Williams. By taking over repetitive tasks, technologies allow workers to focus on highervalue tasks, from decision-making to process optimisation. This not only improves efficiency but also makes jobs more engaging and helps bridge the skills gap. Companies that embrace

"AUTOMATION IS SKILLING JOBS, NOT KILLING THEM”

FOR FURTHER CONSIDERATION:

Hexagon’s 'The Digital Twin Industry Report’ from 2024 and the 'Autonomous Construction Tech Outlook’ from 2023 provide insight into the trajectory of autonomy as it pertains to construction.

Here you can find a list of customer stories showing examples of construction companies adopting full or partial autonomy.

automation aren’t cutting workers – they’re making them more valuable, he asserts.

As machines and jobsites evolve to incorporate more autonomy, the operator’s job may transition to becoming a technology manager, says Welch.

KHL’s Andy Brown, head of Content, Construction and Engagement, discusses the “crawl, walk, run” approach to automation at the most recent Trimble Dimensions Conference

Skilled operators are still going to be needed to teach the machines how to perform certain tasks. “And you will get to a point where there are really hard, really complex tasks, with lots of inputs that only a human can manage. So, it will be many years before we can do everything without a human in the cab,” he says.

SWARMING MICRO MACHINES

It is also possible, maybe even likely, that autonomy could change the design of earthmoving machines other than eliminating the cab, or changing the number or size of machines to do a particular job, says Welch. “There is some interesting research looking at whether it would be more efficient to have two large machines or ten small robotic machines that work together.”

Trimble calls this ‘multi-machine coordination’ says Welch. Instead of two big dozers it might be more like ten mini dozers all working as a swarm at the same time. OEMs will drive this development, but technology, software and machine learning will play a big part.

Autonomy will also enable a single operator to control more than one machine, says Deere’s Veasy. The trend over time will be that autonomous equipment will require less and less operator engagement to operate and manage it.

THE IMPACT OF AI

Automation existed long before AI was a household name. However, AI is now the hottest ticket in town and is building on the success of GPS/GNSS machine control.

AI has unlocked the ability to create productive autonomous solutions that previously would have taken much longer to develop and would have had several limitations to their usefulness, says Veasy. For example, using computer vision to decipher between objects and types of objects is only achievable in a commercial way because of the advancement in AI.

Williams says that AI hasn’t changed Hexagon’s direction but has enhanced what the company is already doing. Machine learning, digital twins and automation have been improving precision, efficiency, and decision-making for years. What’s evolving now is AI’s ability to scale, process data faster, and provide more actionable insights in real-time.

While the future of AI and automation are cutting edge, there’s no reason to take a waitand-see approach. Incremental improvements with real world benefits are happening almost every day.

“We’re integrating AI to refine machine control, automate data processing in surveying and reality capture, and enhance site monitoring and progress tracking – not to replace operators, but to help them work more efficiently with greater confidence,” says Williams.

In the final analysis, the rate of adoption will vary by the technology and benefit. “We have seen customers adopt technology at a high rate, when the value provided outweighs the costs,” says Veasy. The historical example he cites is GPS/GNSS grade control.

“Once customers experience that they can get to grade in one pass, the time savings and efficiency outweighs the initial cost investment,” Veasy continues.

“We expect that as the cost for advanced tech is reduced and the need for more productive equipment increases, technology adoption will scale accordingly.”

AN INCREASING NUMBER OF MACHINES HAVE AUTOMATED SAFETY FEATURES, SUCH AS WACKER NEUSON’S ACTIVE SENSE CONTROL