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# Sandvik and Rio Tinto team up for autonomous drilling
The joint effort will focus on developing autonomous capabilities for remote, multi-site and multi-rig operations.
Srivani Venna June 1, 2026
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In today's increasingly automated construction landscape, network security is no longer just an IT concern, but a critical component for business survival. As construction sites integrate more robots, automated systems, and smart sensors, the network becomes integral to project execution. A compromised network can halt operations, disrupt schedules, and lead to significant financial losses, making construction companies vulnerable to targeted attacks aimed at disrupting uptime.
The convergence of IT and operational technology (OT) in construction introduces a complex web of interconnected devices, from PLCs and HMIs to wireless equipment, each with varying levels of security and patch management. This expanded attack surface, coupled with the reliance on remote vendor access for troubleshooting and updates, creates potential entry points for malicious actors. Simple vulnerabilities like shared credentials and unmonitored remote tools can provide attackers with legitimate-looking access, making detection difficult.
Securing construction networks requires a proactive and pragmatic approach. This includes segmenting networks to limit device communication, tightly controlling remote access with multi-factor authentication and traceable sessions, maintaining a detailed inventory of all connected devices, and monitoring for unusual network behavior. Furthermore, a risk-based patching strategy that prioritizes critical systems and compensates for unpatchable devices with network restrictions is essential. By prioritizing network security, construction firms can protect their investments in automation and ensure safe, efficient project delivery.
Beike, a major player in China's real estate market, unveiled its "AI Suite" at the 3rd Smart China Expo, showcasing a comprehensive set of AI-driven tools designed to revolutionize the entire home-finding and home-improvement process. Aimed at tackling industry pain points like inefficient property matching and opaque construction processes, the suite leverages technologies like AI deep-reasoning models, 3D space rendering, and MR space computing. For construction professionals, this move signals a growing demand for digitized workflows, AI-powered design and building processes, and more transparent communication channels with clients. The ultimate goal is to provide a one-stop solution that transforms the customer experience and establishes new industry standards.
The suite includes several key applications powered by AI. "Pudding AI" intelligently matches buyers with suitable properties, while "City Heart Selection" provides 3D maps with detailed information on local amenities. The MR home-viewing system creates immersive experiences for off-plan properties, and "Zhihui +" (BIM) solutions improve home-improvement designs. Beike is also integrating AI into construction sites to manage, standardize, and visualize the entire process, including real-time monitoring and AI-driven acceptance reports. This push by Beike highlights the potential of AI to not only streamline operations but also improve construction quality by minimizing delays, reducing accidents, and ensuring adherence to design specifications.
Emerson is partnering with SiMa.ai to bring advanced AI capabilities directly to the industrial edge, a move that could significantly impact construction operations. By integrating SiMa.ai's "Physical AI" into Emerson's rugged industrial PCs, they aim to enable real-time analytics and autonomous actions in harsh and remote environments like construction sites. This integration combines programmable logic controllers (PLCs), AI-enabled industrial PCs, sensors, and Industrial IoT-ready supervisory control and data acquisition (SCADA)/human-machine interface (HMI) systems. This collaboration is designed to support on-premise analysis, allowing for immediate insights and responses without relying on cloud connectivity, even in "air-gapped" environments.
This development has significant implications for construction technology. On-device AI can facilitate real-time safety monitoring, predictive maintenance for heavy equipment, and automated control of machinery. The ability to process data locally is especially valuable in areas with limited or unreliable internet connectivity, a common challenge on construction sites. Emerson's continued expansion of AI capabilities demonstrates a consistent strategy to embed AI across its offerings, including software, test automation, and plant optimization. The projected industrial AI market is expected to reach $153.9 billion by 2030, with a compound annual growth rate of 23%, highlighting the potential for AI-driven solutions in construction and other industrial sectors.
Despite significant headwinds in the form of high construction costs, lower reimbursement rates, and shrinking margins, the healthcare construction sector is experiencing growth, according to a recent Modern Healthcare survey. This is significant for construction professionals as it signals continued opportunities in this specialized market. However, it also highlights the increasing pressure to deliver cost-effective solutions and navigate complex financial constraints. Healthcare organizations are clearly looking to do more with less.
Interestingly, the survey also reveals that designs accommodating artificial intelligence and robotics are popular requests. This trend suggests a growing demand for construction projects that incorporate advanced technologies within healthcare facilities. For the construction industry, this means a need to upskill and become proficient in integrating AI and automation infrastructure into new and renovated healthcare spaces, potentially leading to new specializations and project requirements within the sector.
In 2026, AI-powered field reporting apps are becoming indispensable tools for contractors navigating increasing project complexities, tighter regulations, and critical labor shortages. These apps, leveraging machine learning, NLP, and computer vision, automate traditionally manual processes like site updates, voice transcription, photo organization, and daily log creation. By streamlining data capture and communication, they tackle common industry pain points such as excessive administrative overhead, information errors, and slow approval workflows, ultimately helping projects stay on schedule and within budget.
The automation capabilities of these apps are particularly crucial in light of projections of a 500,000 worker shortfall in the construction industry. AI-driven features like voice-to-text reporting, automated daily logs, and real-time collaboration are transforming how field teams operate. Key players like Procore, Autodesk Construction Cloud, Raken, Fieldwire, and Benetics AI are offering solutions that enhance project transparency, minimize documentation efforts, and improve overall efficiency. The adoption of these technologies is poised to give construction firms a significant competitive advantage by streamlining operations and mitigating risks associated with traditional reporting methods.
The National Institute of Building Sciences (NIBS) Building Innovation conference highlighted the growing impact of digital tools and AI on construction processes, particularly in streamlining permitting and inspections. Speakers emphasized how technologies like AI-powered visual inspection and digital permitting systems are dramatically reducing timelines and improving efficiency. For example, Washington D.C.'s Department of Buildings has consolidated permitting workflows and created instant permits, while Procon is using visual AI to allow inspectors to virtually walk buildings before arriving on site, significantly boosting their productivity.
AI's potential extends beyond inspections, with Procore demonstrating how AI can rapidly generate disaster response strategies, compressing months of work into minutes. However, experts cautioned that AI implementation requires careful oversight. While AI can analyze vast datasets and provide rapid insights, the need for human-in-the-loop systems remains critical, preventing automated decisions without human guidance. The conference also acknowledged that digital tools can sometimes create additional administrative burdens if not implemented thoughtfully, underscoring the importance of a balanced approach to technology adoption.
Grain bin entry is a notoriously dangerous task, but Grain Weevil, a Nebraska-based robotics company, is nearing full automation of the process. Their robotic solution utilizes auger-based propulsion to navigate the grain, break up crusted surfaces, and level the grain. A new iteration, slated for release this fall, will eliminate the need for human operators altogether. This advancement will not only significantly improve worker safety by removing them from the hazardous bin environment, but also boost efficiency and reduce grain loss.
The key to the Grain Weevil's autonomous operation lies in its unique navigation system. Unlike traditional GPS-dependent robots, the Grain Weevil utilizes small, magnetic radio devices positioned outside the bin to triangulate its location in real-time. This allows the robot to map the interior, track elevation changes, avoid obstacles, and even self-dock for charging, a critical innovation for operating within enclosed steel structures where GPS and Wi-Fi signals are unreliable. The autonomous robot will also be capable of sweeping the floors of the bins, making for near complete automation.
This technology has implications that extend beyond grain handling. The challenges Grain Weevil has overcome in developing autonomous navigation within signal-denied environments are relevant to other construction applications. Confined space operations such as tunnel boring or working within large metal structures could benefit from similar localization strategies, paving the way for increased automation and safety across a broader range of construction tasks.
Indian construction firms are aggressively embracing smart manufacturing technologies, outpacing their global counterparts in investment. According to a recent report by Rockwell Automation, Indian manufacturers are spending 1.6 times more in the "high-spending" category compared to the global average, indicating a strong commitment to digital transformation. This increased investment reflects a strategic shift from simply adopting digital tools to effectively scaling them within their operations to maintain a competitive edge.
The report also highlights a significant adoption of Artificial Intelligence (AI) and Machine Learning (ML) within Indian manufacturing. Currently, 88% of Indian manufacturers are already leveraging AI and ML in their operations, with 41% of operations being AI-augmented. Projections estimate that this percentage will rise to 47% by 2027 and further to 61% by 2030. This embrace of AI and ML technologies is also impacting hiring practices, with 81% of Indian firms considering AI skills a critical requirement for new hires. This signals a growing reliance on automation and data-driven decision-making within the sector.
## AI's Impact Reshapes the Construction Workforce: Skilled Trades in High Demand
A recent report highlights a surprising shift in the labor market, with AI driving job growth in skilled trades, including construction, even as it impacts some white-collar tech roles. Citing data from LinkedIn and other sources, the report indicates significant wage growth in the skilled trades (up to 30%) coupled with a projected need for nearly 350,000 new construction workers. This trend suggests a growing demand for professionals who can integrate and maintain AI-powered equipment and systems on job sites. Up to 80% of blue-collar workers surveyed believe AI will positively impact their industries.
The rise of AI and automation technologies is not just about replacing human labor; it's also creating a demand for skilled workers who can bridge the gap between the digital and physical worlds. As AI continues to automate repetitive cognitive tasks, the need for on-site technicians, installers, and maintenance personnel to support and manage these advanced systems will only increase. This shift presents both challenges and opportunities for the construction industry, requiring a focus on training and upskilling the workforce to meet the demands of an increasingly technologically driven sector.
Sandvik has unveiled a major upgrade to its Toro LH208L loader, a workhorse for low-profile underground mining. The enhanced loader features a Volvo Penta Stage V engine option, boosting power by 14% and torque by up to 36%, promising quicker cycle times and increased productivity. Beyond performance, Sandvik has prioritized operator well-being with significant noise reduction (6 dB decrease inside the canopy) and vibration dampening. Safety is also enhanced with improved visibility, certified ROPS/FOPS protection, and advanced safety systems.
The Toro LH208L also focuses on minimizing downtime and reducing operational costs. The upgraded design offers increased hydraulic reliability and a longer bucket lifespan (up to 25%). Furthermore, the loader embraces digitalization, being connectivity-ready and compatible with Sandvik's My Sandvik platform. This allows operators to track machine performance, maintenance needs, and productivity using data-driven insights, and enables future upgrades for long-term sustainable underground operations. The Toro LH208L's data-driven capabilities offer opportunities for predictive maintenance and optimized operational efficiency.
Mining operations are facing significant challenges regarding maintenance, often spending a large portion of their operating expenses on it and struggling with unplanned downtime that impacts production and profitability. A webinar featuring experts from Talan and SAP aims to address these issues by providing a roadmap for transitioning from reactive to predictive maintenance strategies. The session will focus on leveraging AI to optimize maintenance workflows, from identifying potential problems to diagnosis, planning, and incorporating feedback. Attendees will learn how to build the necessary data, workflow, and adoption frameworks to successfully implement smart maintenance solutions.
The webinar emphasizes the strategic importance of AI and predictive maintenance in asset-intensive industries like mining. Speakers Charles Carcenac and Mark Crouse will share their experience with organizations who have previously stalled with this type of digital transformation. By understanding where AI can add value, mining operations can significantly improve reliability and reduce costs. The insights offered will equip COOs, VPs of Operations, CFOs, and Plant Managers with a practical first step toward implementing a more efficient and proactive maintenance model, ultimately enhancing operational resilience and competitiveness.
ADNOC is ramping up its use of robotics and AI in its gas operations, a move with potentially significant implications for construction professionals. The energy giant recently deployed a heavy-duty inspection robot at its Taweelah Gas Compression Plant in the UAE. This robot, developed by Taurob, leverages advanced technology like 3D LiDAR, thermal imaging, and 360-degree cameras to autonomously identify gas leaks, heat anomalies, and other hazards. This reduces the need for personnel to enter potentially dangerous environments, improving safety and efficiency.
Beyond inspection, ADNOC is co-developing a next-generation "operator" robot designed to perform physical tasks like lifting, valve operation, and maintenance in high-risk settings. This ambitious project, involving collaboration with companies like Equinor, Petrobras, and TotalEnergies, aims for deployment by the end of 2026. This robot is designed for harsh environments, operating in temperatures ranging from -20°C to 60°C, and will offer both remote-controlled and autonomous functionality. ADNOC's broader strategy includes integrating AI-enabled monitoring systems and autonomous systems across its operations to improve safety and streamline workflows across both land and offshore assets.
Tvasta Manufacturing Solutions, in partnership with 14Trees, has launched Cedar, a new large-format 3D concrete printer poised to revolutionize the construction industry. Designed and manufactured in India, Cedar aims to make automated construction more accessible and cost-effective on a global scale. The system utilizes standard concrete mixes, a major departure from current systems that rely on expensive proprietary materials, leading to potential material cost reductions of up to 5x. With a large printing volume, Cedar can support a wide range of projects, from residential and commercial buildings to industrial facilities and infrastructure components, with printing heights up to 10 meters and an extendable footprint of up to 240 square meters.
Cedar incorporates AI-driven material optimization through the 14Trees AI Companion. This digital intelligence layer analyzes thousands of concrete mix designs, using locally available resources to optimize material performance, balance cost efficiency, ensure structural performance, and promote sustainability. The platform is designed for industrial-scale deployment while ensuring consistent quality, operational reliability, and rapid implementation across diverse construction environments. With integrated end-to-end support services including design optimization, materials development, operational training, and on-site project delivery provided by 14Trees, Cedar represents a major step toward industrializing construction through automation and digital technologies.
Burns & McDonnell is prioritizing the integration of tradesworkers into their preconstruction teams to leverage their field experience, a move that is becoming increasingly vital as project owners demand faster deliveries and cost certainty. According to Brett Poulos, National Director of Preconstruction and Estimating, incorporating individuals with hands-on jobsite experience brings an unparalleled level of understanding to the preconstruction phase, enhancing the accuracy of cost estimates, schedules, and construction methods. This strategy acknowledges that those who've physically built projects possess unique insights into crew sizes, equipment needs, and optimal execution strategies, ultimately leading to stronger project delivery.
A key aspect of this initiative is the role of tradesworkers in vetting AI-generated suggestions within the preconstruction process. Burns & McDonnell utilizes large language models and discipline-specific AI agents, emphasizing the importance of human oversight. Tradespeople with field experience are well-positioned to challenge AI outputs, ensuring that the technology's recommendations align with real-world feasibility and practical construction knowledge. By combining AI tools with the expertise of seasoned tradesworkers, Burns & McDonnell aims to refine its cost modeling, schedule development, and procurement processes, solidifying AI's role in future technology investments and maintaining a competitive edge in the industry.
EACON, a leader in autonomous haulage systems (AHS), is rapidly expanding its footprint in the mining sector, signaling a significant shift towards large-scale autonomous operations. The company is commissioning a fleet of retrofitted Komatsu HD1500 trucks with its AHS technology at Norton Gold Fields' Havana Pit in Australia, marking a crucial step in deploying the technology under real-world mining conditions. This move highlights the growing confidence in AHS as it transitions from pilot projects to full-scale production environments. EACON boasts an impressive track record with over 2,500 autonomous trucks deployed across 30 active projects and 120 million autonomous kilometers traveled.
The expansion extends beyond Australia, with substantial growth in China's mining sector. Multiple projects have seen the implementation of EACON's AHS, including unmanned wide-body trucks at the Zhanihe open-pit coal mine and a fleet of 50 autonomous trucks at the Yankuang Qineng No. 4 open-pit coal mine. Notably, at the Shitoumei No. 1 open-pit coal mine, over 90 unmanned mining trucks operate using a 5G private network and intelligent scheduling supported by EACON's AHS. These deployments demonstrate the increasing integration of AI-powered automation in mining operations, leading to improved safety, efficiency, and optimized resource utilization. Even in extreme winter conditions, EACON's AHS has proven reliable, with hundreds of unmanned trucks ensuring consistent material transportation.
A new study by Rockwell Automation reveals that digital transformation has become a critical imperative for manufacturers worldwide. According to their "2026 State of Smart Manufacturing" report, a staggering 90% of manufacturers believe that embracing digital technologies is essential to remaining competitive. This marks a significant shift, with companies now prioritizing the execution and scaling of digital solutions over simply piloting them. The study points to a clear move away from experimentation and towards the active deployment of smart manufacturing technologies in daily operations, a trend that should resonate deeply with construction equipment manufacturers who rely on these suppliers.
One key area of focus is the integration of Artificial Intelligence (AI). The report indicates that AI currently augments 34% of manufacturing operations, supporting critical functions like quality control, cybersecurity, and process optimization. Moreover, manufacturers anticipate that over half of their operations will be AI-supported by 2030, highlighting the growing importance of AI as a core operational capability. However, the study also reveals that only 43% of collected data is being used effectively, suggesting that harnessing the full potential of AI requires improved data management and analytical capabilities. A notable 46% of manufacturers also experienced a cyber incident in the past year, emphasizing the need for robust cybersecurity measures to protect increasingly connected and autonomous operations. These trends have important implications for the construction industry, particularly in how equipment manufacturers innovate to improve productivity and safety with digital technology.
Xpanner, a construction automation company, has secured $18 million in Series B funding, signaling a major push to scale its AI-powered solutions across the US market. Led by Korea Investment Partners, this investment brings Xpanner's total funding to $38 million and will fuel the expansion of its subscription-based automation model. This funding comes at a crucial time, with surging demand for data centers, battery storage, and solar farms creating unprecedented construction needs and exacerbating existing labor shortages. Xpanner aims to bridge this gap by offering tangible productivity gains through its technology, allowing construction firms to meet deadlines and budgets more effectively.
At the heart of Xpanner's offering is its "software-defined machinery" (SDM) approach. The company's flagship product, the X1 Kit, retrofits existing construction equipment with software and hardware, enabling automation for specific tasks like piling and material handling. Instead of requiring massive upfront investments in new machinery, Xpanner offers an "Automation-as-a-Service" (AaaS) subscription model, providing a more accessible entry point for companies looking to leverage AI and automation. With significant traction in the solar energy sector, Xpanner is positioning itself to capitalize on the broader construction technology revolution.
Xpanner's success highlights a critical shift in the industry: leveraging software and AI to enhance existing equipment and tackle labor challenges. The company's subscription-based model aligns perfectly with the construction industry's increasing focus on flexibility and cost-effectiveness. With major players like Mortenson and Black & Veatch already on board, Xpanner is proving that AI-powered automation isn't just a future concept, but a viable solution for today's construction demands.