This month’s findings suggest leaders are judging the value of AI tools by the tangible benefits they offer. When asked what impact losing the AI tools they use today would have on their day-to-day work, nearly a third (29%) said it would make no difference.

The data also suggests leaders are not seeing AI tools reduce complexity or work pressures. Only 24% said work would become more complicated without them, while 22% said it would become more stressful. One in six said they would not have enough hours in the day to complete their work without their current AI tools, with the same proportion saying valuable data would be lost.

At an organisational level, leaders are increasingly judging AI by its role in business projects such as process automation, predictive maintenance, data-led decision-making and responsible deployment at scale.

Jeff Hoyle, MD UK at Expleo, said: “Leaders may be among the first to apply more scrutiny to AI because they can see how it is performing across the organisation. They can see where AI is improving the delivery of business projects, where it is improving access to data or strengthening decision-making, and where the benefits are still difficult to prove at scale.

“If leaders are not seeing clear evidence that AI is improving how projects are delivered, that is likely to shape decision-making and future investment in the technology. This makes it increasingly important for AI-led projects to demonstrate how they are improving quality, speed and capability.”

The wider AI Pulse data for July reinforces the emergence of a confidence gap. Excitement fell by two points to 63% and confidence by six points to 62%, both tracker lows. Leaders were less worried about AI transforming their organisations, but concern about its impact on their own jobs rose by four points to 40%.

Trust in organisations to use AI ethically remained at 69%, while concern about AI-related cybersecurity risks edged up to 58%.

Hoyle added: “AI Pulse tracks the sentiment that shapes strategy and investment decisions. This month’s results suggest the AI confidence gap is widening, which could make leaders more selective about where AI investment goes next.

“The strongest AI projects will be able to show where the technology is reducing pressure, improving decisions, protecting data and creating measurable value. That evidence will be crucial to closing the confidence gap and unlocking the next phase of AI investment.”

expleo.com

The R-noid launch includes five solution categories: Restaurant sssistant, packer, Picker, folder, and host, deployed across six industry verticals including industrial, logistics, healthcare, food services, lodging, and experiential. 

CEO and co-founder, Felipe Chavez Cortes, stated: "The future of work isn't fewer people. It's people freed from the parts of the job that grind them down, doing more of what they're good at."

R-noid features dual 7-degree-of-freedom arms, a 4-DoF articulated torso with 0 to 1.9m vertical reach, and a holonomic mobile base. The robot runs on Physical Intelligence's π0.7 vision-language-action model for generalist manipulation across packing, picking, and folding tasks.

Robot.com partnered with Yukai Engineering for design and R-soul, an expression system designed to earn trust. The company also works with FieldAI on Field Foundation Models and uses NVIDIA's robotics stack including Jetson modules and Isaac Sim.

At launch, R-noid performs 19 deployable tasks. Lighthouse deployments are underway, including a live Packer deployment at a golf course handling on-site order operations and movement toward production at a major food manufacturing facility.

www.robot.com

Under the partnership, McLaren will deploy autonomous quadruped robots, initially to capture 360° site imagery, generate point cloud data and support progress verification, model-to-site deviation analysis, safety compliance patrols and quality assurance. The range of tasks will grow over time, adding value to the robots already on site with each new capability.

‍Regular automated scans by FieldAI robots will create a visual and spatial record of work as it is installed. AI-enabled deviation analysis will compare site data against the design model, reducing the time between install and identification of on-site quality issues. This capability will support correct installation at the point of delivery, ensuring true quality control, tolerance management and a reduction in rework. 

The partnership marks FieldAI's entry into the UK market and extends construction deployments that already span hundreds of sites across Europe, Asia, and North America. The two companies will work together to meet UK regulatory and data security requirements as deployments scale up.

At the core of the deployment are FieldAI's Field Foundation Models, which combine data-driven AI with physics-based reasoning and uncertainty quantification to unlock environments that are otherwise too complex and unpredictable for robots. One universal “brain” enables robots of all shapes and sizes to perform a widening range of tasks in unstructured environments they have never seen before. Because the software does not depend on prior maps, supporting infrastructure or pre-planned routes, the robots can be deployed quickly and adapt as a site changes.

McLaren expects the partnership to deliver more reliable project monitoring, earlier identification of installation issues and a stronger evidence base for compliance and quality assurance. Over time, the collaboration will also provide practical lessons that can inform wider deployment of robotics within the business.

McLaren Construction’s group pre-construction director, Adam Nicholson, explains: “The significance of this deployment for the construction industry is that we can move beyond machines that are remote controlled or pre-programmed for a limited range of tasks and routes. Instead, we now have autonomous robots navigating stairs, doors and other obstacles and constantly working with our human teams to support productivity, safety and quality.”

Patrick Purwin, VP of Sales at FieldAI, comments: “One of the impactful features of this partnership is McLaren's willingness to expand use cases as general-purpose robots grow more capable. The work starts with monitoring and modelling missions and expands across the full spectrum of physical work,including site logistics, dexterous manipulation and multi-robot coordination.”

www.mclarengroup.com

This initiative aims to promote the development of a collaborative control platform that ensures sovereignty by bridging the digital and physical worlds and integrating NVIDIA’s open physical AI technologies. By accelerating the societal implementation of physical AI across various industrial sectors – including manufacturing, logistics, and healthcare – Fujitsu seeks to realise a society where humans and robots coexist and collaborate, and strengthen Japan’s industrial competitiveness.

In recent years, various industrial sectors, particularly manufacturing, have faced growing challenges such as labour shortages due to Japan’s declining birthrate and aging population, a decline in the number of skilled technicians, and intensifying global competition. To resolve these challenges and achieve sustainable growth, the promotion of digital transformation (DX) is essential. In particular, expectations are rising for physical AI, where AI recognises and analyses real-world information and executes it as physical actions.

Physical AI enables the automation of tasks, improved productivity, stable quality, and the creation of new services by allowing robots and various pieces of equipment to assess situations and autonomously determine and execute optimal actions. However, realising this requires advanced robot control technology and an AI infrastructure that leverages high-quality on-site data, as well as a collaborative control platform that integrates these elements to bridge the digital and physical worlds. Yet, there are limits to what a single company can achieve in terms of development and widespread adoption.

Given this situation, as a technology company, Fujitsu will promote the societal implementation of physical AI through collaboration with leading robotics companies—FANUC, Yaskawa Electric, and Kawasaki Heavy Industries, while simultaneously working to standardise and open up the collaborative control platform.

Overview

Social implementation utilising physical AI

These explorations will cover the social implementation of physical AI in the following industrial sectors with plans to expand into other sectors in the future in place.

• Factory solutions: By optimising the planning of overall factory production activities,taking into account factors affecting production fluctuations and on-site conditions, and enabling autonomous on-site adaptation, Fujitsu will help the manufacturing industry achieve further productivity gains and flexibility.
• Solutions for retail and logistics: By automating material handling operations based on logistics plans that incorporate real-time sales and inventory data, Fujitsu will achieve labour-saving and automation in logistics.
• Healthcare solutions: Based on optimised plans triggered by instructions from hospital operational systems, robots autonomously execute tasks to automate the in-hospital transport of pharmaceuticals and specimens, as well as outpatient reception and guidance services.

Fujitsu will develop software platforms and hardware interfaces that serve as a common foundation for physical AI by first gaining a deep understanding the cutting-edge technologies – such as AI, robotics, control systems, simulation, and data analysis – held by each company. These technologies will facilitate collaboration among various robots and equipment, and help to realise more advanced autonomous control systems. At the same time, as the scope of robot applications expands and collaboration with other equipment increases, risks such as cyberattacks, system-wide downtime or malfunctions, and leaks of confidential information also rise. Therefore, Fujitsu will develop a sovereign collaborative control infrastructure which will be provided as an open platform for participating companies and research institutions, thereby promoting the implementation of physical AI across the entire industry.

Collaboration with NVIDIA

Through this initiative, Fujitsu will lead business discussions with the companies and leverage the AI, world model, simulation, and robotics technologies underpinning NVIDIA’s physical AI platform. By doing so, it will further enhance the sovereign collaborative control platform and accelerate the social implementation of physical AI in industrial domains.

• Fujitsu will leverage the NVIDIA Cosmos global foundation model in its socio-physical simulations to enhance its ability to understand and predict events in real-world environments. Furthermore, it will accelerate the development and real-world implementation of physical AI solutions across diverse sectors, including manufacturing, logistics, and healthcare.
• Fujitsu will leverage libraries such as NVIDIA Omniverse, the NVIDIA Isaac open platform, and the Newton physics engine to streamline Sim2Real as well as robot learning, verification, and optimisation.

Future plans

Starting with business discussions with these companies, Fujitsu will formulate a roadmap for concrete technology development and business expansion. As the robotics market expands, Fujitsu is confident that establishing a framework to provide an AI infrastructure, leveraging Japan’s world-class robot control technology and high-quality on-site data, will be a crucial step toward Japan leading the global robotics market. Through the societal implementation of physical AI, Fujitsu will contribute to the realisation of a safe and prosperous society where humans and robots coexist and collaborate, as well as to the strengthening of Japan’s industrial competitiveness.

global.fujitsu

Manufacturers are facing a growing disconnect between strategy and execution. Many have invested in digital tools that fail to deliver adoption, or consulting programmes that lack the real-time data needed to sustain change. This collaboration is designed to address both challenges.

OFS provides real-time machine data, operator feedback and performance visibility across the shop floor, while Performance Solutions by Milliken applies its operational excellence framework, governance and behavioural change expertise to ensure that insight translates into action. Together, the two organisations offer a joined-up approach to performance improvement, combining visibility with execution.

Jonathan Newton, GM Europe at OFS, said: “Manufacturers do not need more data. They need the ability to act on it with confidence. This collaboration is about connecting what is happening on the factory floor with the systems, behaviours and leadership needed to improve performance in a sustained way.”

Darren O’Connor, business development director at Performance Solutions by Milliken, said: “Our focus has always been on helping organisations embed operational excellence in a way that delivers lasting results. By working alongside OFS, we can strengthen that approach with real-time insight, giving teams the clarity they need to prioritise and act.”

OFS is deployed across thousands of manufacturing sites in 35 countries and is used by more than 30,000 people each day. Its customers include organisations such as AB Foods, Aryzta Bakeries, Campari, Electrolux and Asahi.

Performance Solutions by Milliken applies its performance system across its own global manufacturing network and has supported hundreds of client sites worldwide.

In practice, the collaboration is designed to be flexible. Engagements may be led by either organisation or delivered jointly, depending on client needs. Both teams take a consultative approach, working closely with manufacturers to understand operational challenges and design coordinated programmes that improve performance, reduce risk and increase return on investment.

The collaboration also opens up opportunities for joint activity including roundtables, webinars and thought leadership focused on the future of manufacturing performance.

www.ofsystems.com

At the conference, AGIBOT underscored its commitment to building a sustainable embodied AI ecosystem in the UK and Europe. The event brought together product innovation, flexible commercial models, and local deployment practices, with highlights including the European debut of AGIBOT A3, the introduction of a UK Robot-as-a-Service (RaaS) model and the company's continued collaboration with local partners to explore real-world applications in the UK.

"The UK is a strategically important market for AGIBOT's global expansion," said William Shi, president of EU and US markets at AGIBOT. "It has a strong innovation ecosystem, a mature partner network, and diverse real-world scenarios where embodied AI can create value. Through UK APC2026, we hope to work more closely with local partners to bring AGIBOT's technologies, products, and service capabilities into practical applications, and to use the UK as an important starting point for broader deployment across Europe."

"AGIBOT is one of the most dynamic companies in the global humanoid robotics industry, with a strong product portfolio and a clear focus on real-world deployment," said Shyen Kotecha, head of robotics and connectivity at Scancom. "We are pleased to work with AGIBOT to bring these technologies closer to UK customers. By combining AGIBOT's robotics capabilities with Scancom's local channels, customer access, logistics, and service support, we believe we can help accelerate the practical adoption of embodied AI robots across education, retail, commercial services, logistics, and other real-world scenarios."

AGIBOT A3 makes European debut 

As one of the key highlights of UK APC2026, AGIBOT marked the European debut of AGIBOT A3, its new-generation humanoid robot. AGIBOT A3 features a lightweight 55 kg body supported by magnesium alloy and titanium alloy reinforcement, a dual-battery system that delivers up to 10 hours of nominal battery life, and 10-second battery swapping for extended operation. Standing 173cm tall with a 1:9 head-to-body ratio, AGIBOT A3 is designed to combine stronger motion performance, longer operating time, and a more natural appearance.

Built for practical deployment, AGIBOT A3 supports dynamic movements, multimodal interaction, shoulder touch sensing, and UWB centimeter-level positioning for multi-robot formation and group performance without additional hardware modification. It also supports single-person carry, autonomous unpacking, and transportation in a standard SUV, making AGIBOT A3 suitable for education, entertainment, exhibitions, customer engagement, guided services, commercial facilities, and other public-facing applications.

Making robots more accessible in the UK through RaaS

A key part of AGIBOT's UK strategy is the introduction of a local Robot-as-a-Service (RaaS) model developed together with its UK partners. Designed to make advanced embodied AI robots more accessible without requiring large upfront investment, the model combines AGIBOT's robot products and embodied AI capabilities with local partners' logistics, service, technical support, and customer delivery resources. In the UK, AGIBOT humanoid robots will be available for rent starting from £1,999 per day for humanoid robot, while quadruped robots will be available starting from £899 per day, with localized deployment and operational support.

The RaaS model is designed for a wide range of real-world scenarios, including education, university research, exhibitions, customer engagement, commercial services, logistics, and facility operations. By working with local partners to provide flexible rental options and on-the-ground support, AGIBOT aims to help schools, universities, developers, service providers, industrial customers, and enterprise users test, validate, and scale embodied AI applications more efficiently in the UK.

Retail deployment in the UK

AGIBOT has already begun local retail deployment and scenario showcases in the UK, including at Smart City, a retail venue in Milton Keynes operated by Smart City Consultancy, where visitors can experience AGIBOT robots in consumer-facing environments. AGIBOT has set up a dedicated area featuring AGIBOT A3, AGIBOT X2, AGIBOT A2, and the AGIBOT D1 quadruped robot, bringing embodied AI robots into a real public-facing retail environment.

The deployment is designed to explore how AGIBOT robots can support customer attraction, traffic engagement, reception, guided interaction, brand promotion, and smart retail experiences in shopping malls and commercial spaces. By working with local partners in real-world retail environments, AGIBOT is testing how embodied AI robots can create more interactive, flexible, and service-oriented customer experiences in the UK.

Beyond the UK, AGIBOT has been expanding its European presence across key markets including Italy, Germany, and Spain, building local partnerships around scenario adaptation, localized services, distribution, and flexible deployment models.

The UK APC2026 builds on this foundation and marks an important step in AGIBOT's long-term strategy to advance real-world deployment of embodied AI across Europe. Moving forward, AGIBOT will continue working with local partners and industry customers to explore scalable deployment pathways across education, commercial services, logistics, and other scenarios.

www.agibot.com

Under the agreement, IFS technology will be embedded across Chelsea's operations over a multi-year period. Initially deploying Finance and Procurement solutions, IFS and Chelsea FC will look to extend the use across a broad range of Industrial AI capabilities including asset management and facility operations. IFS technology will be central to the operational foundations of the business and will use next-generation IFS.ai tooling to enhance performance, drive efficiency and uncover opportunities for future growth. 

In this initial phase, IFS technology will give Chelsea real-time visibility across its finance operations and automate manual processes, alongside a guided, end-to-end procurement process covering supplier onboarding, contract management and spend visibility.

The phased rollout reflects Chelsea's ambition to become one of the most operationally advanced club in world football, with IFS Industrial AI setting a new standard for what world-class operational technology looks like in elite sport.

IFS already manages $2.4 trillion in critical assets for customers globally across energy, manufacturing, and aerospace. The same Industrial AI that keeps turbines running and factories online will now be applied Chelsea FC today and in the future.

Mark Moffat, chief executive officer at IFS commented: “Chelsea FC operates in a world where performance, precision and pressure are non‑negotiable. That’s exactly the kind of environment where IFS Industrial AI thrives and delivers. This partnership will demonstrate to the world what's possible when elite ambition meets industrial-grade AI.”

Adriel Lares, chief financial officer at Chelsea Football Club said: “Advanced technology is transforming the way businesses operate and we are excited to be moving into the next phase of our partnership with IFS to realise the opportunities AI software presents.”

www.ifs.com

THE UK’S legally binding commitment to reach net zero by 2050 places increasing pressure on industrial operators to reduce emissions in both direct and indirect energy use. According to the Carbon Trust, an independent organisation that helps businesses reduce carbon emissions, industry alone currently produces around 48 million tonnes of CO₂ annually, making it the nation’s third-largest emitting sector.

Within industrial systems, electric motors and gear systems sit at the centre of countless driven applications including conveyors, mixers and pumps. Even small efficiency improvements can compound across thousands of operating hours, cutting the amount of energy needed to run industrial equipment.

In industrial systems, small improvements can add up quickly. Reducing friction, improving lubrication and correcting alignment can help machinery waste less energy over time.

In fact, research published in Advances in Mechanical Engineering found that by adopting advanced surface, material and lubrication technologies, energy losses due to friction and wear in industrial machinery could be reduced by as much as 18 per cent within eight years. In mechanical systems, these improvements often come from identifying and reducing frictional losses. 

Where friction losses occur

Tribology provides the scientific framework for understanding where energy losses occur inside mechanical systems. In geared equipment, energy losses typically arise from sliding friction in gear meshes and bearings, lubricant churning and windage caused by air resistance. In each case, useful mechanical energy is converted into heat, reducing overall efficiency.

These losses are typically divided into load-dependent and no-load losses, both of which can significantly affect long-term operating performance. Because tribological contacts account for such a significant share of global energy use, even small reductions matter. 

This is where contact mechanics becomes particularly valuable. By analysing how forces transfer between gear surfaces, engineers can identify areas of excessive stress, micro-slip and insufficient lubrication film thickness, all key contributors to friction and wear. This can mean lower operating temperatures, reduced component wear, longer equipment life and improved energy efficiency. Understanding these microscopic interactions helps engineers reduce friction, heat and wear across the system.

Practical ways to improve efficiency

In practice, gear efficiency is influenced by several interacting factors, including alignment, lubrication quality, surface condition and gearbox design. Monitoring power draw, operating temperature and lubricant condition can help engineers find inefficiencies and check whether changes are working.

The benefits extend beyond energy reduction alone. Lower friction can reduce unplanned downtime, extend service intervals and decrease spare parts consumption, cutting waste as well as operating cost.

Despite this, several misconceptions persist. Many organisations assume equipment replacement is the only route to lower emissions, when optimising existing assets can often deliver faster and more cost-effective results. Others underestimate the cumulative impact of incremental efficiency gains across large fleets of machinery.

The value of optimising existing systems rather than replacing them is something Technidrive has seen first-hand. When Kerry Agribusiness needed to improve efficiency at its feed mill in Ireland, the solution was not a wholesale equipment overhaul. Instead, Technidrive engineered an automated drive system using a WEG CFW11 variable speed drive to take precise control of the feeder motor, replacing a manual process that had been wasting energy through inconsistent speed settings. The result was a 29 per cent increase in throughput, achieved by controlling existing machinery more intelligently, not by replacing it.

The net zero takeaway

Optimising gear systems is one of the most practical and scientifically measurable ways to reduce industrial energy consumption. By applying a structured, contact-mechanics-led approach, organisations can achieve measurable efficiency gains today without waiting for large-scale equipment replacements. For businesses aiming to accelerate their net zero progress, understanding the friction within existing machinery may offer one of the most immediate opportunities for long-term impact.

technidrive.co.uk

The first capability available inside Nulogy Intelligence is Nora, a manufacturing AI assistant embedded in Nulogy’s Smart Factory and Maintenance solutions. Nora gives plant floor teams instant answers on production performance, downtime, and maintenance, without leaving their workflow.

Manufacturing teams spend hours each week hunting for answers. Dashboards, spreadsheets, and reports rarely line up. Nora changes that. Plant operators, shift supervisors, maintenance leads, and plant managers can ask Nora questions in plain English and use the solution to automate tasks, such as creating maintenance orders. “What was OEE on Line 3 yesterday?” or “Show me overdue maintenance orders” return clear answers from live production data in seconds. Nora is also available inside Nulogy’s new user-to-user chat experience, putting answers in the same workflow teams use to communicate.

Nora connects production performance, downtime events, maintenance orders, and CMMS schedules. Users can ask Nora to visually display data in charts and graphs, making it even easier for teams to interpret information and act quickly. When a supervisor asks why a line keeps going down, Nora pulls the downtime data, and checks for open maintenance orders on the same assets. The solution flags whether the issue is being addressed. A 45-minute investigation becomes a 90-second conversation.

“Plant teams shouldn’t have to be data analysts to do their jobs well,” said Bryan Sapot, executive vice president at Nulogy. “Nora gives them a direct line to the answers they need, in the language they already use. The goal isn’t to replace expertise on the plant floor. It’s to make that expertise faster and easier to apply.”

Nora is built for the realities of manufacturing operations. The solution never fabricates data, adapts to customer-specific terminology like line names and part numbers, and is scoped to read production data and create or update tasks and maintenance orders.

“Nulogy Intelligence is one of several ways we’re bringing AI to manufacturing in a way that’s practical, trustworthy, and built for the people behind every product,” said Bill Ryan, CEO of Nulogy. “Our customers can expect Nulogy Intelligence to continue expanding as we find new ways to help manufacturers improve operational performance and win more business.”

Nulogy.com

Yet while the results reveal a sector that sees robotics and autonomous production as the key priorities, the survey also uncovered that for the greatest commercial edge, these technologies must interconnect rather than be deployed in isolation.

The findings come following a recent poll of more than 100 engineering and manufacturing professionals who were asked where they believe industrial automation investment will deliver the greatest competitive advantage for their business over the next five years.

Robotics and autonomous production topped the poll at 41%, followed by smart/connected factories at 33%. Meanwhile, AI-driven predictive maintenance was selected by 14%, and sustainability-focused investment completed the picture with 12%.

Respondents also highlighted that these four investment areas are deeply interconnected. Several pointed to the role of data and AI as an essential layer that underpins the value of every other investment, from enabling predictive maintenance that tackles unplanned downtime to making connected factories genuinely intelligent rather than simply networked. Others framed the four areas as a value chain, with each contributing to an overall reduction in total cost of ownership and linked the trajectory to the broader shift from Industry 4.0 into Industry 5.0 production environments.

The results highlight the continued pressure on manufacturers to increase output, improve efficiency and maintain flexibility while operating with leaner teams and tighter cost controls.

Daniel Coetzee, vice president: growth, industrial automation for IMI, comments: "What stands out from these results isn't just that robotics leads the poll, it's that several technologies need to work together to truly drive commercial benefits. Our customers are telling us that the competitive advantage won't come from any single investment, but from the intelligence and connectivity built around it.

"That aligns with what we see across our customer base. The businesses making the most progress aren't necessarily those making the largest capital commitments; they're the ones taking a more targeted approach, using smarter components, better data and more connected systems to unlock meaningful, measurable gains from their existing operations. A good example is the impact of linking the performance insight produced by technologies such as sensors and actuators as part of an engineered system to the potential of AI to derive increased value from plant devices.

"For many industrial businesses, the opportunity isn't a wholesale transformation, it's about making incremental, well-judged improvements that compound over time. That's where we see the greatest competitive advantage being built right now."

IMI’s Industrial Automation sector works with customers globally to develop application-specific automation solutions that help improve productivity, efficiency and responsiveness, helping businesses realise the benefits of smarter automation without unnecessary complexity or disruption.

www.norgren.com/en