“Interact Analysis expects the industrial robot market here to see steady growth over the next five years, driven by reshoring initiatives and policies like tariffs, which are forcing robot makers to rethink their manufacturing strategies.

“FANUC isn’t alone in this shift. Just last year, Yaskawa attracted attention by announcing plans for US-based production for robots and motion control components. As the largest robot supplier in the U.S. by market share, FANUC’s push toward local production aligns naturally with its market leadership and customer proximity strategy.

“That said, questions remain about the depth of localisation. It is possible that the new facility will primarily support assembly instead of full-scale manufacturing. Given that FANUC produces its core motion control components in Japan, and with limited domestic supply of key parts such as precision gearboxes in the U.S., it is likely that critical components will continue to be imported, with final robot assembly conducted locally.”

For more than 200 years, manufacturing has been built upon the single principle of control. It delivered scale, efficiency, and global supply chains, but it was designed for a predictable world.

Today, as Europe’s manufacturers face energy uncertainty, labour shortages, and mounting sustainability pressures, a new industrial model is emerging: one that replaces rigid control with flexible coexistence – providing a framework in which people, machines, and the planet work together, through autonomy and collaboration, towards a shared purpose.

The limits of control

Since the Industrial Revolution, manufacturers have been working on gaining ever greater control – over their machines, processes, resources, and manpower.

The introduction of the steam engine in the late 1700s allowed factories to run machinery at a predictable, steady speed for the first time, for example, while the moving assembly line established control over the flow and pace of production. Control has powered mass production and enabled global supply chains, but it is reaching its limits.

To control a parameter, we first need to predict it. Yet, as Ikuo Tateishi, president of the Human Renaissance Institute and grandson of OMRON’s founder, Kazuma Tateishi, highlighted at Osaka Expo 2025, today’s world is anything but predictable.

Towards coexistence

As a society, we face climate volatility, energy insecurity, demographic contraction, and geopolitical fragmentation. In Europe, energy costs are high, labour is scarce, and global is competition is intense.

In this landscape, success will depend not on harnessing control to accelerate scale or speed, but on our ability to combine technology, human values, and collaboration into a more resilient model of progress. The key is replacing the pursuit of control with adaptive, co-created networks that connect people, machines and the planet.

More than 50 years ago, Kazuma Tateishi predicted that society would evolve from a focus on efficiency and optimisation, to autonomous systems that can self-organise and learn. He foresaw a so-called ‘natural society’ where humans, technology and nature coexist in balance.

We now see his theory unfolding in factories around the world. Machines that sense, decide and adapt in real time, production systems that respond dynamically to variation, and factories that share operational data to improve energy and material efficiency have all become realities.

This machine autonomy is not about removing people, but amplifying their intent. Moving from control to coexistence means enabling technology that listens, collaborates, and creates space for human creativity and purpose.

Six shifts toward a coexistence economy

Moving from control to coexistence requires a fundamental rethink of how manufacturing is designed and run. The path ahead is not a single innovation, but a connected transformation across technology, culture and collaboration.

Europe’s manufacturing future depends on six key shifts. The first is from isolated efficiency to systemic resilience – moving beyond pure productivity to systems that can adapt, predict disruption, and remain stable in volatile conditions. Manufacturers also need to move from competition to co-creation, collaborating across industries, governments and research to solve shared challenges and accelerate innovation for the greater good.

In addition, we must move from linear production to circular design, replacing take-make-dispose models with systems that reduce waste, recover materials and regenerate energy. At the same time, we must also shift from central control to distributed intelligence, enabling autonomous, connected systems that learn locally but improve globally, thereby increasing agility and resilience across the system.

As automation advances, the focus must expand from efficiency to transparency, building trust through explainable, ethical, and accountable systems that people can understand and oversee. Finally, predictability must give way to adaptability, with flexible organisations and technologies that can respond quickly to change without sacrificing stability.

Together, these six key shifts define a manufacturing model where people, technology, and the environment coexist to create sustainable, resilient value.

A realistic path forward

Every industrial revolution has been an upgrade of our collective operating system, and the upcoming step change is no exception. Yet moving from control to coexistence will not be easy.

While success will rely on industry, technology and society evolving together, the political and economic climate in many regions already favours protectionism over collaboration. Together, we must highlight our shared purpose and build an understanding of the mutual benefits of coexistence.

There are also legitimate concerns around job displacement, data security and ethical AI, all of which must be addressed sympathetically and with transparency. We need to share the message that coexistence is not about replacing people with machines, but reconnecting technology to purpose.

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Speaking on the first day of ‘The Future of Precision Engineering’ event – held at FANUC’s Coventry headquarters on 27-29 January 2026 to showcase the latest advances in injection moulding, robotics and CNC manufacturing – Andy stated: “In the plastics sector, we are seeing a shift towards the use of bio-based and recyclable materials, and a focus on sustainable manufacturing solutions. It’s no longer just ‘good to be green’ – it’s now a business necessity.

“Against a backdrop of rising operational costs, regulatory changes, supply chain challenges and an ongoing skills shortage, every penny counts. The use of automation and AI to effect cost-saving measures such as energy efficiency, increased productivity and better use of human employees is essential if UK manufacturers are to remain competitive in both the domestic and global markets.”

AI and connectivity, plus European ROBOSHOT premiere

FANUC UK’s three-day Open House event brought together leading figures in the worlds of automation, plastics and wider manufacturing to discuss the biggest topics affecting companies right now. While Day 1 focused on sustainability, Day 2 is addressed AI and connectivity, with Day 3 shining a light on education and training. Morning presentations and lively panel debates were followed each day by the opening of a packed exhibition area featuring over 30 of FANUC’s partners (including Hi-Tec, Piovan, Mold Masters, Ultrapolymers and Solinatra), delivering live automation demo cells and exciting exhibitor presentations.

The event also showcased the best of FANUC’s own robotic and automation solutions, including 6-axis robots, automated drilling machines and injection moulding machines. The highlight is the European debut of FANUC’s newest addition to the ROBOSHOT range – the 350-tonne S350C all-electric machine, bringing faster mould times and AI-assisted energy-saving functions.

BPF survey results revealed

Following Andy’s Armstrong’s keynote presentation on Day 1, the British Plastics Federation’s Member Services Director, Stephen Hunt, took to the floor to deliver the main findings from the January 2026 Business Conditions Survey. Hot off the press, Stephen revealed an improving picture for the plastics industry compared to the previous three surveys, stating: “The decline we’ve seen over the last 18 months is definitely slowing.”

Stephen also revealed that sustainability is becoming increasingly important to BPF member companies. A total of 64% of respondents confirmed that they have an ESG policy in place, with a further 21% actively working on one; while 36% already have a net zero strategy, and 31% are actively creating one.

Stephen was followed by an enlightening panel discussion featuring Jamie Riley from Robinson PLC, FANUC’s Sam Carr, Tom Reardon of Bloom-in-Box, and Solinatra’s Stephen Rundle. Sharing practical tips for incorporating sustainability into every part of the manufacturing process, and revealing the energy and cost-saving benefits that smart automation solutions can bring, they engaged in lively interactions with many attendees who were keen to share their own experiences and challenges.

Andy Armstrong adds: “Whether you’re looking to reduce cycle times, cut your energy consumption, increase your supply chain resilience, upskill your workforce or utilise AI and automation to increase your productivity, it will all be on offer this week at FANUC. We’re excited to share our technology, insights and experience with you to help drive a strong, smarter and more sustainable future for UK manufacturing.”

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As the saying goes, if you’re not moving forwards – you’re going backwards. And in a world of increasing global competition, unpredictable costs, and mounting pressure on labour and sustainability, the UK’s manufacturing sector can no longer afford to delay the adoption of robotics and automation. That’s the message from Mike Wilson, one of the UK’s leading authorities on automation, who brings over four decades of experience into his role at the MTC.

At Packaging Innovations & Empack 2026, taking place 11-12 of February at NEC Birmingham, Mike will lead the Automation in Action session. The panel will spotlight how robotics, AI and connected systems are revolutionising packaging operations. But for all the promise, he says, the UK still lags far behind its international peers.

“The truth is, not much has changed in the last 12 months in terms of actual robot adoption numbers,” Mike says. “But what is changing is the mindset. For the first time in decades, the government is signalling that manufacturing matters again.”

Culture, confidence, and the fear of complexity

The UK’s historical hesitance to automate isn’t purely down to cost, Mike argues. It’s rooted in a deeper cultural mindset: a “make do and mend” philosophy that undervalues capital investment. SMEs, which make up the vast majority of UK manufacturers, are often cautious and risk averse.

“Many businesses still have this outdated perception that robots are only for big automotive plants,” says Mike. “They think it’s too expensive, too complicated, or not suitable for what they do. But the reality is the opposite – systems are more affordable and easier to use than ever before.”

That fear is often compounded by gaps in practical knowledge. “Most SME business leaders have never been taught how to buy automation. They don’t know how to write a specification, assess suppliers, or build a business case,” he explains. “We don’t teach that in apprenticeships or business school, and if you’re unfamiliar with the tech and the salesperson across the table knows far more than you do, it’s understandable why people hesitate.”

The solution, he believes, lies in independent, trusted support – organisations like the MTC who aren’t selling systems but offering impartial guidance, helping businesses start small, upskill gradually, and grow their confidence.

The people problem: Demographics and attraction

Another ticking clock is the workforce. “The average age in UK manufacturing is now over 50,” says Mike. “In 10 years, many of those people will have retired. And the next generation doesn’t want to do the same jobs their parents did – not unless there’s exciting and engaging tech involved.”

It’s easy to see this demographic shift as a threat, but savvy businesses also recognise it as an opportunity. “Younger people are digital natives. They’ve grown up with tech and they expect to use it at work. If we want to attract them into manufacturing, we have to build the kind of workplaces they want to be part of – automated, digital, connected,” says Mike.

Automation, when done right, doesn’t replace jobs, it redefines them. From factory line programming to process monitoring, a new category of roles is emerging that blends operational oversight with digital skills. This also opens the door to a more diverse workforce.

“Historically, engineering has been male dominated. But the skillsets needed in future – analytical thinking, digital fluency, system control – are completely gender neutral. There’s no reason women shouldn’t be leading this shift too.”

Don’t automate the bottleneck

When companies finally decide to automate, Mike has a word of warning: start smart. “One of the major mistakes we see businesses make is trying to automate the hardest job first; the biggest bottleneck. But there’s a learning curve. If it’s your biggest headache now, chances are it’ll be your biggest headache in automation too.”

Instead, he advises starting with simple, repetitive tasks that free up skilled people to focus on more valuable work. Palletising, line loading, transferring – these are ideal starting points. “A robot might not be faster than a person, but it’s consistent. It doesn’t stop for lunch or lose focus at 3pm. That stability is where the gains come from.”

AI, embedded intelligence, and what’s next

AI is already making its way into automation systems. Not in the form of humanoid robots, but as embedded intelligence that improves robot performance, simplifies programming, and enables predictive maintenance. “AI’s already here. It just doesn’t wear a badge,” Mike says. “And while some of the hype – especially around humanoids – will settle down, AI will absolutely continue to play a growing role in packaging and manufacturing.”

By enhancing flexibility, improving diagnostics, and lowering the barrier to entry, AI will make automation more accessible to more businesses – but that also means strategy is critical.

“Think about your end goal. Where do you want to be in five or ten years? Build your automation roadmap around that, including the training and investment you’ll need. Don’t bolt it on as an afterthought.”

Packaging’s productivity challenge

For the packaging industry, the opportunity is especially clear. Fast-moving, high-volume, and labour-intensive by nature, packaging operations are ideal candidates for automation. And yet, the sector still faces the same barriers: skills gaps, investment fears, and cultural resistance.

“If we haven’t started to change by 2030, we’re in trouble,” Mike says. “Productivity is the route to competitiveness – it lets you pay better wages, attract talent, and justify investment. Automation is the lever that unlocks all of that.”

Mike will be chairing ‘Automation in Action: Robotics as the engine for packaging agility’ at Packaging Innovations & Empack 2026, 11-12 February at NEC Birmingham. Bringing together key voices sharing insight and perspective on today’s hottest packaging and manufacturing topics, it’s set to be an unmissable edition of the show.

Giedrė Rajuncė, CEO and co-founder of GREÏ, an AI-powered process intelligence platform for large physical sites

As industrial AI moves from hype to infrastructure, five trends are emerging that will define real operational impact in 2026, revealing why success will depend on process redesign, domain-specific intelligence, and frontline trust.

The adoption of AI in industrial contexts is still recent, with limited pilot implementations and proofs of concept despite high expectations. As AI systems move from experimentation to practical application, leaders are under pressure to demonstrate value beyond technical capabilities.

“AI will stop behaving like a side project and started behaving as infrastructure,” says Giedrė Rajuncė, CEO and co-founder of GREÏ, an AI-powered process intelligence platform for large physical sites. “But the uncomfortable truth is that most organisations are still applying AI to broken processes. In 2026, success will come from redesigning operations first, then using AI as a force multiplier.”

According to Rajuncė, leaders preparing for the next phase of AI-driven operations must start by fixing the fundamentals – simplifying workflows before introducing automation and treating AI as a co-worker rather than a replacement. This also means investing in strong data foundations, security, and governance, while favouring interoperable platforms over fragmented tool stacks.

In this context, several AI and deep-tech trends stand out as genuinely transformative for industrial operations in 2026.

1. Agentic AI systems replace dashboards with action

One of the biggest shifts in 2026 will be the rise of agentic AI systems, which autonomously execute workflows across operations. “One example that illustrates the potential of these agents is an on-site accident scenario. Rather than alerting a manager, an AI agent can initiate a work order, contact the relevant vendor, check parts availability, and coordinate scheduling, handling the operational response with minimal human involvement,” explained Rajuncė.

However, these capabilities also expose weak foundations. Gartner predicts that 40% of agentic AI projects will fail by 2027 because they are misapplied and lack a singular business issue to address. In practice, this means agentic AI amplifies both strengths and inefficiencies, forcing leaders to confront operational reality faster than ever before.

2. Physical AI and industrial robotics move to orchestration

AI is rapidly moving from software into the physical world through intelligent robotics. The World Economic Forum identifies three systems that will increasingly coexist: rule-based robotics for predictable tasks, training-based robotics for variable environments, and context-based robotics for unpredictable conditions. This shift is already delivering measurable results, with AI-orchestrated fulfilment centres achieving faster delivery times and more skilled operational roles.

While specialised systems drive current gains, humanoid robots are expected to scale rapidly over the next decade, with projections of 13 million units by 2035, as organisations begin orchestrating physical AI across machines, people, and processes in real time.

3. Domain-specific AI models overtake generic generative AI

While generic large language models continue to dominate headlines, their limitations in industrial environments are becoming increasingly clear. Lacking context about specific facilities, equipment, and safety constraints, generic models risk producing inaccurate or even dangerous outputs. By contrast, domain-specific language models tailored for manufacturing, logistics, and construction are proving far more effective. Some estimates predict that by 2028, more than half of enterprise GenAI deployments will rely on such specialized models.

“Generic GenAI is overhyped for industrial use,” says Rajuncė. “A model that doesn’t understand your HVAC system, wiring, asset history, or safety thresholds is a liability. In physical environments, context isn’t a nice-to-have; it’s the difference between insight and risk. That’s why domain-specific models are overtaking generic ones in serious industrial deployments.”

4. Multimodal AI unlocks real-time operational intelligence

By 2026, multimodal AI systems capable of processing text, images, video, sound, and sensor data simultaneously will become mainstream. For industrial operations, this enables entirely new forms of situational awareness.

For example, in manufacturing, vision systems can correlate visual defects with vibration patterns, acoustic signals, and thermal data. In construction and logistics, drone footage can be analysed alongside equipment telematics and structural sensor inputs. The result is significantly higher accuracy and faster response times than any single data source can provide.

5. Predictive maintenance and frontline usability become decisive

Predictive maintenance continues to deliver some of the clearest returns in industrial AI, with organizations reporting maintenance cost reductions of up to 40% by shifting from time‑based preventive models to data‑driven prediction. At the same time, frontline usability is emerging as a critical differentiator. World Economic Forum research shows that AI initiatives fail when frontline workers are treated as passive users rather than active knowledge contributors.

“If an AI system can’t explain why it’s recommending an action, trust disappears,” says Rajuncė. “Frontline teams want clarity. If an AI agent suggests shutting down a machine or flagging a safety issue, people need to see the reasoning behind that decision.”

AI-driven robotics

Artificial intelligence is making robots smarter, safer and faster to deploy. Through voice-controlled operation, adaptive motion control, safety-aware human-robot collaboration, and virtual commissioning via digital twins, AI is transforming industrial automation.

One of the most significant benefits of AI is its ability to accelerate deployment. By assisting with code generation, AI makes it easier and quicker for companies to implement robotic systems. Non-specialists can use natural language to programme robots to perform tasks, reducing the engineering burden on manufacturers and delivering a faster return on investment. AI-enabled robots will also allow existing production lines to be retrofitted without extensive modifications, further speeding up the rollout of automation.

AI also expands opportunities for collaborative applications. With AI-driven voice control, robots can interpret spoken instructions and autonomously generate the code needed to execute tasks. This will enable robots to work more flexibly alongside human operators, adapting in real time to changing requirements.

In addition, AI will enhance robot safety and enable closer human-robot collaboration. For example, integrated vision systems allow robots to detect obstacles in their environment. AI can then instantly recalculate motion paths in three-dimensional space, ensuring safe and efficient operation around people and equipment.

Smart and scalable automation

Automation is becoming increasingly adaptable. Smart, scalable robotic solutions that can evolve alongside changing business needs are enabling manufacturers to de-risk automation investments without compromising on quality or reliability.

Smaller, more agile automated systems are also helping manufacturers address labour challenges, particularly for low-skill or repetitive tasks such as picking, placing and palletising. At the same time, suppliers are prioritising ease of deployment through simplified teaching methods, AI-enabled voice control and intelligent technologies such as vision and force sensing. As a result, the path to automation is now faster and more accessible than ever before.

Alongside these technological advances, end-users’ attitudes towards return on investment are shifting. Rather than focusing solely on upfront purchase price, manufacturers are increasingly considering total cost of ownership (TCO), factoring in long-term considerations such as maintenance, downtime and energy consumption when making a purchasing decision.

As a result, automation solutions are becoming more flexible, affordable and user-friendly than ever. These smart and scalable systems are set to help more manufacturers overcome labour shortages, enhance product quality and consistency, and drive meaningful gains in productivity.

Open ecosystems and partnerships

The future of industrial automation is collaborative. Open platforms and partnerships between hardware and software providers are enabling more flexible, integrated solutions that accelerate innovation and adoption.

FANUC is actively collaborating with leading technology partners bringing AI solutions to market, including NVIDIA, helping to unlock the potential of physical AI. A key step in this journey is FANUC’s support for the open-source robotics platform ROS 2, which enables programming via Python. By lowering the barrier to entry, this allows developers, researchers and companies to build AI-driven robotics applications on FANUC’s proven industrial hardware.

One important benefit of this openness is a smoother transition from education into industry. ROS 2 and Python are widely taught in colleges and universities, and making these tools available on industrial equipment will allow more young engineers to apply familiar skills directly in real-world manufacturing and automation environments.

More broadly, open platforms such as ROS 2 and Python will help to stimulate a new wave of innovation, enabling companies to build, customise and scale AI-augmented robotics solutions while leveraging their own software expertise on top of FANUC’s hardware and NVIDIA’s advanced simulation infrastructure.

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Going back a few decades, PC-based vision was the norm. PCs were in control of the camera, meaning that the processing power was in the computer, not the camera itself. This evolved into the development of robots with in-built vision technology, employing solutions such as FANUC’s IR vision – a fully-integrated 2D and 3D visual detection system that enables FANUC robots to see.

More recently, however, there has been shift towards smart cameras and, in more complex scenarios, industrial PCs combined with AI. For simple applications, smart cameras are proving highly effective for enabling robots to locate parts, complete measurements, or carry out basic quality checks.

For more sophisticated tasks, the high processing requirements of high speed or very high accuracy vision systems require an industrial PC. When it comes to high-speed robotic vision applications, such as recognition of different products and different materials at speeds that can match the robot’s capabilities, it is becoming increasingly common for AI technology to be employed.

One such example is London-based recycling tech company, Recycleye. It uses proprietary AI vision technology in conjunction with FANUC 6-axis LR Mate robots to automate the detection and sorting of mixed recyclables. Previously a mostly manual process, Recycleye is generating impressive results including an increase in sorting accuracy of up to 12% and improved line output of up to 10%. Not only is this helping waste operators to boost their bottom line, it’s also providing a solution to the ongoing labour shortages in the waste management industry.

As Recycleye is proving, vision cameras are making robotic deployment in difficult tasks more reliable than ever before, validating and verifying location, product quality and part placement. Not only that, but costs have come down significantly in recent years, so much so that industrial vision is now at a price point that compares with smart sensors. As a result, inbuilt vision technology is now a standard feature of most robot systems, rather than an additional add-on at extra cost.

Latest advances in camera technology also means that today’s robotic vision systems operate more robustly and reliably in 2D and 3D applications and in environments that traditionally have been difficult for cameras to operate in. For example, in the past, vision technology used only visible light and relied on pattern matching or model matching as a means to locate or identify a part. Modern vision technology can now use different wavelengths, or stereovision to improve reliability, filtering out the challenges caused by sunlight or other environmental effects, as well as process interferences such as welding sparks.

As for the next big trend, I believe there will be a shift towards the use of industrial camera solutions for safety rather than traditional solutions such as light guards, in order to better manage robotic safety around humans in collaborative applications. Although this technology has been available for a while, it hasn’t been utilised at scale because it was prohibitively expensive for most applications. This is now changing, and affordable industrial camera solutions from companies such as SICK are set to revolutionise robot safety as we know it.

In addition, we can expect to see more and more smart camera systems as standard features on established robot models. For example, Mech-Mind’s 3D smart camera technology is already being integrated with FANUC robots, enabling end users to benefit from its ability to see even dark and reflective objects, and locate transparent parts.

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Every automation engineer knows that complexity has a cost. Multiple controllers, fieldbuses and interfaces can lead to longer commissioning times and higher maintenance demands. According to a 2024 PwC digital trends in operations survey, more than two-thirds (69 per cent) of operations and supply-chain officers reported that tech investments hadn’t fully delivered their expected results with the most-selected reason being integration complexity (30 per cent).

Traditional automation systems rely on a network of specialised devices: one for motion control, another for safety, another for data processing. Each must be configured separately and linked together through intricate communication layers. This fragmented setup means that even small design changes can add weeks to development schedules and increasing engineering hours. Multiple suppliers and different programming environments contribute to longer commissioning times and greater dependency on specialist skills.

As a result, maintenance becomes more reactive than preventative, spare parts inventories grow, and the total cost of ownership rises. For many OEMs, the complexity built into legacy control architectures directly limits their ability to respond quickly to new customer requirements.

A simpler alternative?

Beckhoff’s approach to “less complexity” lies in its PC-based control philosophy – using industrial PCs to run all automation functions in software rather than hardware. Motion, logic, safety, robotics, vision and even AI-based analytics can all be handled within the same real-time platform, known as TwinCAT. This reduces the need for multiple controllers and simplifies communication across the entire machine.

This unified architecture also allows for seamless expansion. Whether the machine has a handful of I/O points or thousands, the same control logic can scale without redesigning the system. It’s this scalability that helps manufacturers build more machines with the same engineering resources, which is a key advantage in competitive global markets.

Proof in practice

A good example of this principle in action comes from Schirmer Maschinen, a German manufacturer of machinery for processing window and door profiles. To simplify design and improve maintainability, Schirmer adopted Beckhoff’s MX-System, a modular, cabinet-free control platform that mounts directly onto the machine.

By removing conventional control cabinets, the company cut installation and wiring effort dramatically, while freeing up valuable floor space. The modular architecture also made servicing easier, with diagnostic data available directly at each module. The result was a cleaner, faster and more efficient production setup that still maintained full control performance.

For Schirmer, the MX-System “ticked all the boxes” for reliability and flexibility – a clear demonstration of how simplification can drive both innovation and practicality on the factory floor. “The MX-System is changing the face of design and installation in the world of machine building,” explained Ludger Martinschledde, managing director of Schirmer Maschinen.

In automation, adding more parts doesn’t always mean gaining more control. The opposite is often true. By reducing hardware, consolidating software and embracing open, PC-based architectures, manufacturers can build smarter, more flexible systems that evolve with their needs.

Complexity may once have been the price of sophistication, but a philosophy based on PC-based control shows that real innovation lies in making automation simpler – and that’s how engineers can achieve less complexity and more control.

From Trump to the Ukraine invasion, Covid restrictions to the growth of AI, violence in the Middle East to the rise of the far right in Europe, it’s clear that we are living in turbulent times. Amid such geopolitical uncertainty, world military expenditure has unsurprisingly rocketed, increasing by almost 10% in just one year (from 2023 to 2024) to reach $2,718 billion.

The countries with the highest military expenditures are the USA, China and Russia respectively, but even across Europe, defence stocks hit record levels in 2025. And the UK is no exception. According to the Institute for Fiscal Studies (IFS), in 2024-25 the UK spent £66 billion (2.3% of national income) on defence and, as part of a NATO agreement, has committed to increase defence spending to 3.5% of GDP by 2035.

The international race to shore up sovereign defence capabilities is on. But with multiple countries simultaneously striving to do so, prices for defence procurement are likely to increase if production capacity cannot meet global demand. So, how can the UK ensure it doesn’t get left behind?

Delivering domestic automation support

In manufacturing, automation remains the fastest and most efficient route to increasing production capacity. However, the UK currently lacks sovereign robotic OEMs or large sovereign solution providers – a gap that raises significant concerns around security and control of intellectual property.

For a nation that hosts some of the world’s leading defence and aerospace companies, including BAE Systems, Airbus and Rolls Royce, reliance on foreign automation technology presents strategic vulnerabilities that could compromise both national security and the protection of critical IP.

As one of the world’s leading robot manufacturers and with a longstanding British presence, FANUC is perfectly placed to provide domestic automation support to help shore up the UK’s defence capabilities. We understand that the European – and indeed, global – defence spending landscape is changing rapidly. By supporting not only prime and tier defence companies, but also increasing automation capacity within wider manufacturing facilities, we can bolster the full UK sovereign supply chain.

While our UK base in Coventry is leading the charge, it must be acknowledged that FANUC is a Japanese-owned company. However, there are defence programmes of work currently underway that involve both the British and Japanese governments, underlining the mutual trust and support between the two nations: for example, the Global Combat Air Programme (GCAP), a multinational initiative led by the UK, Japan and Italy to jointly develop a sixth-generation stealth fighter.

In addition, FANUC has around a 50% market share worldwide for CNC delivery to machine tool manufacturers, with a large proportion of such machines being heavily utilised in aerospace manufacturing. Knowing that they operate on a common control platform, developed and managed by a safe and trusted source, is yet another tick in FANUC’s box.

Cyber resilience as standard

Linked to this issue of mutual international trust is, of course, cybersecurity. This issue is set to rise in prominence over the next 12 months when the EU’s new Cyber Resilience Act (CRA) comes into force, beginning in September 2026 with full enforcement taking place in December 2027. Setting mandatory cybersecurity requirements for hardware and software products with a digital element, it requires manufacturers to ensure their products are secure by design, provide security updates, and report vulnerabilities and incidents throughout their lifecycle. All UK machine providers will be affected, and it will alter how equipment is risk assessed, and CE marked.

The new FANUC R50iA controller – based on the latest CNC hardware, FS500 – is already fully CRA compliant, making it easier for our customers to complete their risk assessment. Over the next two years, all our robots will feature this new controller as standard, while our oIder controllers are currently undergoing validation to ensure they also meet the new standards, well ahead of time.

FANUC customers – across defence, aerospace or any other area of manufacturing – can rest assured that they will be ahead of the cyber resilience curve, with their machines futureproofed thanks to smart, safe and compliant equipment.

Reliable and robust

With the majority of new defence and aerospace projects spanning multiple years if not decades, ensuring equipment longevity and avoiding obsolescence could not be more pertinent. These are often huge programmes involving multiple stakeholders, tens of millions of pounds, and layers of complex engineering and compliance requirements. Any equipment – including robots and other automation solutions – employed in such projects must be extremely robust, reliable and futureproofed if they are to stand any chance of success.

Here again, FANUC is at an advantage. We are renowned for having some of the most automated production facilities in the world, with robots making robots like clockwork. FANUC will provide lifetime support on our products, assuring spare parts availability and local service support worldwide. And by that, we mean as long as the customer wants to continue to use it, whether that’s for five years or 25 years – we are still servicing robots purchased more than two decades ago that are in perfect working order.

Innovation in automation

While machine reliability and longevity are critical for defence automation projects, innovation is equally crucial. By working closely with manufacturers, as well as organisations at the cutting edge of R&D, we can take things to market that the market itself needs, and respond swiftly to changing customer demands. To this end, we are proud to be one of the keystones in not just the vertical supply chain, but also the horizontal, working with universities, R&D/training institutes, High Value Manufacturing Catapults (HVMCs) and more to support and develop innovation within automation.

A prime example of this is Project Compass (Composites at Speed and Scale), an £80m investment which includes an aerospace manufacturing R&D project delivered by a consortium of companies including our system integrator partner Loop Technology, Boeing, Spirit AeroSystems and the Advanced Manufacturing Research Centre (AMRC). Three FANUC M-2000iA/1700L six-axis industrial robots are being employed as part of the project, as well as an M-2000iA 1200L and a 900L model.

We also supported Airbus with its in-house robotics strategy, developing an industrial drilling robot (the M-800iA/60) to meet the company’s specific requirement. We welcome future collaborations such as this.

Reducing project risk

As these examples show, engaging with big prime manufacturers and their first tier suppliers on a regular basis is crucial to project success in the defence and aerospace sectors. Keeping the supply chain tight helps to reduce financial risks, technical risks and security risks, as well as speed up project delivery with solutions that the market demands.

We are course also proud to continue working alongside our partners that have long supported and serviced manufacturers in the defence and aerospace sectors with automation solutions in the past.

We look forward to seeing the results of our increased focus on bolstering the UK’s defence capabilities with domestic automation solutions, and the security benefits this can deliver for all.

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“Considering the intensive competition in traditional robotics, established manufacturers like ABB will need to lead the charge in AI-driven robotics to protect their margins,” she said. “However, achieving this will require significant investment. The substantial long-term R&D costs may be a key factor behind ABB’s decision to sell its robotics business.

“This move may push ABB’s competitors, particularly the other ‘Big 4′ players, to accelerate collaborations with AI and software companies or bring in investors, ensuring they have the resources to stay competitive in the AI-driven robotics space.”

Looking at the acquisition itself, Samantha commented: “SoftBank has yet to establish a successful track record in robotics investments. This deal marks its first acquisition in the industrial robotics area, and it remains to be seen whether its IT-industry culture can effectively integrate with the industrial engineering tradition at ABB Robotics.

“The deal valued ABB Robotics at $5.4 billion, with an implied FY24 EV/EBITDA multiple of 17.2x, broadly in line with other major industrial transactions (typically 12-18x),” she added. “Midea’s 15x multiple for KUKA suggests SoftBank is paying a modest premium – negligible given the current AI robotics hype cycle, where emerging players command far higher valuations.