Wirtgen Group is actively developing automated road construction vehicles as stepping stones for full autonomy using some of the same technology stack as parent company John Deere.

During a recent demonstration of its roadbuilding machinery at the company’s North American headquarters in the US state of Tennessee, company executives outlined the benefits of its specialised heavy machinery for road building.

Demand for roads and infrastructure keeps rising while contractors juggle labour shortages, climbing material costs, tighter project timelines and shorter paving seasons.

In the US alone, the construction industry is expected to need nearly 700,000 additional workers by 2031 just to keep pace with demand.

About 40% of the four million miles of roadways across the US are currently rated in poor or mediocre condition.

“As we talked with our customers, we learned a few things about some of their business challenges, which is simply to do more with less,” said Craig Lamarque, VP and head of digital products at Wirtgen America. “Every day our customers are responsible to ensure the safety of every person on absolutely every job site”.

“And they have to do that with increasingly less skilled and less experienced personnel.”

Lamarque explained customers must complete a greater number of projects on tighter timelines to stay profitable while coping with issues with materials, sustainability pressures, labour shortages, and the need to stay on budget and on schedule.

Wirtgen Group responded by introducing digital tools to help address those challenges.

He said Wirtgen’s digital strategy centres on three pillars: connected support to maximize uptime, job site intelligence to expose inefficiencies and improve decision-making, and smart automation to boost machine performance.

Those capabilities are embedded across its road construction equipment lineup and are supported by hardware and software in collaboration with John Deere.

A legacy built on family names

The Wirtgen Group was a privately held German company before it was acquired by John Deere in 2017.

Earlier in its history, the Wirtgen Group bought asphalt paving company Vogele (in 1996) ahead of purchasing soil and asphalt compaction company Hamm three years later. Vogele was established in 1836, one year prior to John Deere.

Kleemann was acquired in 2006, which expanded Wirtgen’s reach into mineral processing with mobile crushing and screening plants.

The Wirtgen Group bought a 70% stake in Benninghoven in 2014, adding asphalt mixing plants to the ecosystem and enabling Wirtgen to offer the entire cycle of road construction equipment from mixing and paving to milling and recycling.

Wirtgen America was established in 1984 and now includes 300 employees across the Tennessee campus.

“Every one of those names of the brands is a family name, much the same as Deere,” said Wirtgen America president and CEO Jim McEvoy. “From that standpoint, we have a long legacy of being early in these markets, being leaders in these markets and being very innovative in these product spaces.”

Here’s a look at three of the roadbuilding machines and technologies showcased in Tennessee across asphalt milling, paving and compaction.

Wirtgen milling machine
The milling machine removes old asphalt or concrete surfaces while using automation and digital guidance technologies to improve precision, efficiency and performance tracking. It is designed for high-output work on freeways, highways, airports and other major infrastructure projects.

The W210XF is equipped with a 2.5 metre-wide cutter drum which removes asphalt and concrete prior to loading the material into a truck. It uses automation and digital guidance technologies across eight cameras to improve precision, efficiency and machine performance tracking.

“Simple diagnostics, intuitive instructions on the display and backup components built into the machine make it easy to keep going,” Lamarque said.

WPT Milling documents job and machine data for billing and emissions tracking. Smart Level Pro is a fully integrated differential milling system which scans the surface about to be milled.

The process begins with a high-speed survey scan of the existing road surface, either by the customer or a third-party surveyor, without closing the road. The resulting digital model is then georeferenced and logged using GNSS.

After scanning, the road profile is refined to meet specifications, then uploaded to the John Deere Operations Centre and Work Planner, where cutting depths can be checked in advance which saves time compared with milling first and verifying later.

Utilising two John Deere StarFire receivers connected by cellular service, Lamarque said the mill goes to work, “precisely milling the design depth and slope, leaving the best possible surface”.

StarFire GNSS Guidance is Deere’s satellite technology which helps machines maintain highly accurate positioning, alignment and paving guidance throughout the roadbuilding process.

Mill Assist is an automated system on the milling machine that uses real-time machine data to optimise performance, improve efficiency, and reduce fuel consumption and emissions.

Vogele asphalt paver
The asphalt pavers are packed with highly specialised automation, levelling and material handling technologies.

Smart Pave is an advanced digital control and automation system developed by Vogele for its asphalt road pavers. AutoTrac technology helps the paver hold its direction of travel and paving width with precision.  

RoadScan is Vogele’s proprietary, non-contact thermal imaging and temperature measurement system mounted directly to the asphalt paver.

Hamm asphalt roller
The double-drum asphalt roller machine compacts fresh asphalt to the target density required for long term durability, using real-time density monitoring and intelligent compaction technology to hit the mark.

It focuses on preventing over-compaction, maximising operator efficiency and providing proof of compaction quality to contractors, state and federal authorities.

The roller uses a combination of vibration and oscillation to compact material to the desired density. Smart Compact Pro and Track Assist help road crews compact more efficiently, cost-effectively and safely while also meeting intelligent compaction specifications.

Intelligent compaction is data collection of the roller using GPS compact mapping, temperature sensors which map and report asphalt surface temperature and an accelerometer sensor that reports stiffness.

From automation to autonomy
Jason Ambroson, VP and managing director of Wirtgen International, explained running the same technologies, connectivity and data sensors across the various roadbuilding machines enables customers to be more productive using fewer employees and fewer resources.

“We are moving from automation to autonomy,” he said.

That trajectory of connecting machines, data and operators into a single intelligent system was what the Tennessee demonstration was ultimately built to show.

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Vodafone Business and carmaker Geely’s European R&D division extended an existing partnership to cover adoption of a range of connectivity platforms intended to support vehicle monitoring and driver experience improvements.

The deal with Geely Technology Europe comprises Vodafone’s Internet in the Car, Mobile Private Networks and Cloud Connect products.

Vodafone noted capabilities supported by the systems include diagnostics, over the air software updates and secure data transfer between vehicles and cloud systems.

The operator is also providing connectivity across the Geely division’s operations in Germany and Sweden and for its sales teams across Europe.

Vodafone highlighted by 2030 98% of new passenger vehicles sold are expected to be connected, adding together with Geely it was “ready to help drive this expansion”.

Geely Technology Europe CEO Giovanni Lanfranchi said: “We’ve moved beyond simple transport solutions. Today, vehicles can be continuously improved through software, with data and connectivity enabling a more responsive and personalised user experience over time.”

Vodafone Business product and international business director Fanan Henriques added: “As the adoption rate of electric vehicles continues to grow, the opportunities to enhance their safety, efficiency and the user experience through digital connectivity are significant.”

“We’re supporting Geely’s growth in vehicle sales across Europe and its operations with a secure, multi-service digital infrastructure.”

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SK Telecom (SKT) partnered up with Nvidia to use the chip company’s digital twin technology for semiconductor manufacturing environments operated by SK Hynix, pushing industrial AI deployments to achieve more automated factory operations.

The operator said it used Nvidia “Omniverse libraries” to adapt digital twins for complex, large-scale manufacturing environments, following a proof-of-concept completed last year at a SK Hynix semiconductor manufacturing site. It plans to commercialise the technology in stages as SK Hynix works to establish autonomous fab operations by 2030.

Using Nvidia’s Agent Toolkit, SKT developed Agentic Digital Twin Modelling technology to automate data processing, including site equipment and spatial structures, for use in digital twin systems. It also integrated Nvidia Omniverse libraries to make large 3D factory scenes load faster, run more smoothly and use GPU and memory resources more efficiently.

The set up aims to improve data conversion, scene optimisation and performance tasks required to build and run digital twins at scale.

SKT explained digital twins act as working replicas of real factories and equipment. In semiconductor plants, they can be used to test changes to processes or equipment layouts in advance, helping reduce costly trial and error in highly complex production sites.

Mike Geyer, head of industrial digital twins at Nvidia, said semiconductor fabs are “among the most challenging manufacturing environments”, citing “massive amounts of 3D data, complex equipment structures, and the need for high-level optimisation”.

Cho Ik-hwan, head of physical AI at SKT, added the collaboration demonstrates manufacturing digital twins can move “beyond simple 3D visualisation” into systems capable of “understanding and optimising large-scale 3D manufacturing data”.

SKT added the move bolsters its plans to expand its enterprise and public sector business with AI offerings spanning infrastructure, models and services.

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Nvidia CEO Jensen Huang positioned the adoption of humanoid robots in industry as opening a multitrillion-dollar economic opportunity, as it announced a model for academics using hardware from Unitree and Sharpa intended to accelerate advances.

In an announcement made at Computex 2026 in Taipei, Taiwan, the executive backed humanoid robotics to “bring physical AI to the world’s largest industries” but indicated there were barriers to academic work to this end, which it aims to resolve by introduction of the “reference robot”.

The machine uses Nvidia compute systems and Isaac GR00T development platform, a Unitree H2 body standing at almost 6 feet tall and weighing 50 pounds in weight, and Sharpa Wave tactile five-finger hands.

“Nvidia Isaac GR00T Reference Humanoid Robot gives researchers a single, open platform to make breakthrough discoveries toward general-purpose physical intelligence,” Huang added.

During his keynote at the event Huang explained “we built this for higher education and university researchers, because for them to build this is insanely hard to do”, pointing to the complexities and expense of starting from scratch in every project.

Nvidia noted by using its “compute and open software stack” at the core “the reference design gives research teams a more unified, secure foundation for advancing humanoid robotics”.

Discussing Sharpa’s role founder David Li said “partnering with Nvidia on a humanoid robot reference design and end-to-end development solution is a meaningful step toward deploying robots that can perform real work, in real settings”.

The executive added its “vision is to make robots genuinely productive – by advancing fine manipulation skills through dexterous, tactile hardware and the AI models that power them”.

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Boldyn Networks’ US CCO Jason Caliento said the company is making good on pledges to boost the digital experience offered at Major League Soccer (MLS) venues after equipping a new stadium in the city of Miami with various connectivity technologies.

The company installed a platform of Wi-Fi 7, IPTV, audio, neutral host mobile and converged fibre infrastructure at the Nu Stadium in the Miami Freedom Park to deliver fresh services for fans and contribute to improved operation of the venue which opened in April.

Caliento highlighted an “innovative financial structure”, whereby Boldyn Networks handled the capital investment it plans to recoup through network operation and management duties.

He said the model provides “significant financial flexibility” and predicted it would become a key selling point for deals with other venues.

Boldyn Networks explained the Nu Stadium is a 26,700-seat facility located in a mixed-use development spanning 131-acres.

It installed more than 600 access points covering high-density Wi-Fi and mobile throughout the site. Cloud-based IoT platforms are providing real-time information on crowd behaviour, and the fibre element covers game streaming and display on more than 200 connected TVs.

The company highlighted mobile ticketing, from-seat refreshment ordering and access to interactive content as among the main benefits for fans.

Caliento said Boldyn Networks became an official supplier to the MLS in a deal struck in 2025.

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IoT specialist Wiliot expanded work with AT&T Business to boost its position in the physical AI field by tapping the US-based operator’s connectivity, device relationships and general expertise in data handling.

Wiliot is seeking to broaden its position in physical AI for enterprise supply chains and believes AT&T has the network connectivity, device relationships and ability in employing data to do so.

“Physical AI depends on continuous data” from the real world, VP of marketing Amir Khoshniyati said.

Deepening ties with AT&T improves Wiliot’s “ability to deploy and operate physical AI networks across large, distributed environments”.

The company is pitching a platform which handles sensing and intelligence, employing real-time data from dedicated devices. AT&T is tasked with delivering the network infrastructure, mobile connectivity and execution elements.

Certification of Wiliot gateway devices on AT&T’s network is also underway, as the company seeks more direct connectivity and standardised deployments for the enterprise space.

Wiliot stated the companies embarked on a systems integration collaboration late in 2025 covering core deployments and operational capabilities. The operator is also handling various design, installation, asset tagging and maintenance aspects.

Lee Wagner, area VP for AT&T, explained enterprises “need actionable data from the physical world” and the companies are “adding visibility at the case and asset level” to provide a fresh range of services.

Work already undertaken in retail, food and beverage, and some restaurant sectors delivered inventory accuracy improvements of 99%, Wiliot stated.

It also highlighted improvements in the time taken to ship goods to storage, a reduction in the number of staff required in receiving items and greater shipment accuracy.

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Telefonica Tech and Google Cloud partnered on a product intended to meet the needs of Spanish public bodies and companies in highly regulated sectors with strict data sovereignty requirements.

The latest tie-up between the pair brings a joint service to market in Spain which allows information held in Google Cloud to be encrypted by keys generated and stored by Telefonica in its local infrastructure.

Having the keys generated and managed by an operator in Spain provides increased protection against unauthorised access from elsewhere in the world, Telefonica noted.

It added the Data Boundary model offered by the pair would provide verifiable controls over data protection and access, enabling compliance with digital sovereignty requirements.

Telefonica Tech CEO Sofia Collado said the offering would provide organisations with the means “to define precise data residency, access control and data protection policies through encryption keys generated and managed outside public cloud environments”.

Google Cloud country manager, Iberia, Isaac Hernandez added “there should be no conflict between Spain’s digital sovereignty and its economic competitiveness”.

“By combining our cutting-edge cloud capabilities with Telefonica’s local operational control and encryption management, we are empowering businesses and public administrations to innovate securely and confidently on their own terms.”

Google Cloud Data Boundary is offered across various global markets in partnership with companies in each country.

Telefonica noted it was selected as the tech giant’s “trusted partner for data sovereignty” in its home market.

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A report by Telus Digital exposed significant security vulnerabilities across the generative AI landscape, which included finding every major model could be coaxed into unsafe behaviour under the right conditions.

In the company’s second GenAI Safety Model Benchmark, Telus Digital’s testing found some models engaged with harmful requests more than 90% of the time and stated most enterprises are dangerously underprepared to defend against them.

The testing drew on more than 620,000 adversarial tests across 34 AI models from 10 global providers: Anthropic, OpenAI, Google, Meta, Alibaba, Baidu, ByteDance, Zhipu AI, 01.AI and Mistral.

It is the most extensive AI security study Telus Digital has conducted to date, nearly doubling the scope of the first edition published in November 2025.

Attack vulnerability rates across tested models ranged from 1.3% to 93%, where a lower percentage means a safer model. 

Anthropic’s Claude models claimed five of the 10 lowest vulnerability scores, including the benchmark’s overall lowest rate, but Telus Digital noted even single-digit failure rates are unacceptable in high-stakes enterprise contexts involving money, health and reputation.

The research identified model size, reasoning capability and the creator’s overall safety approach as the strongest predictors of resilience.

Reasoning models, designed to deliberate before responding, proved significantly harder to exploit, with a 19.9% vulnerability rate compared to 55.1% for standard models which skip the reasoning step.

Smaller models are consistently the most susceptible to attacks, regardless of whether they are open-source or proprietary. The study found open source models are not inherently less safe than closed ones, with GLM 4.7 from China’s Zhipu AI outperforming many proprietary alternatives.

The benchmark also highlighted where risks cluster most sharply: privacy exploitation, fraud and cybersecurity threats remain the hardest categories for even leading models to handle.

Telus Digital also flagged a pattern called “refuse-but-engage,” where a model declines a harmful request but still provides related information which could cause harm or reputational damage.

Global AI spending is projected to reach $2.52 trillion in 2026, yet spending on AI trust, risk, and security management is projected to be just $3.4 billion, which is roughly $1 in security for every $735 spent on AI capabilities.

Meanwhile, 86% of organisations report having already experienced an AI-related security incident.

Telus Digital urges enterprises to move beyond one-time or periodic safety checks toward continuous, automated adversarial testing embedded directly into development workflows, layered with human oversight and clean data practices.

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