The German group, founded in 1847, does not directly produce industrial robots. Yet it lies at the heart of most modern automated systems. In 2025, Siemens generated over €79 billion in revenue, a significant portion of which comes from its industrial automation and digital activities.

Its strategy rests on a strong conviction: the future of industry does not depend solely on machines, but on their ability to be connected, controlled, and optimized in real time.

Siemens: The Brain of Industrial Robotics

If robots are the “arms” of the factory, Siemens is the central nervous system.

The group has established itself as a global leader in automation systems through several key technologies:

• Industrial programmable logic controllers (PLCs), notably the SIMATIC range
• Engineering software such as TIA Portal
• Industrial supervisory systems (SCADA)
• Control and motion control solutions

Market estimates indicate Siemens holds between 20% and 30% of the global industrial PLC market, making it one of the leaders alongside Rockwell Automation and Schneider Electric.

Siemens doesn’t sell robots;
it provides the factory’s
nervous system.

These technologies make it possible to coordinate entire production lines, integrating robots, sensors, machine tools, and logistics systems.

A Strategy Focused on Integration and Software

Unlike robot manufacturers, Siemens takes a systemic approach.

The group does not position itself as a machine builder but as a provider of technology platforms capable of integrating:

• Robotics
• Industrial Internet of Things (IIoT)
• Data systems
• Artificial intelligence

This approach transforms isolated equipment into intelligent industrial ecosystems.

The global Industry 4.0 market, estimated at over $150 billion in 2025, is expected to exceed $300 billion by 2030, with an average annual growth rate above 10%. Siemens is today one of the main beneficiaries of this transition.

The Digital Twin: A Major Transformation Lever

A cornerstone of Siemens’ strategy is the development of the digital twin.

This concept creates a virtual replica of a factory, production line, or product to:

• Simulate industrial processes
• Test robot integration
• Optimize production flows
• Anticipate failures

According to Siemens, using a digital twin can reduce production start-up costs by up to 30% and cut development times by 20–50%.

Solutions such as Siemens NX, Teamcenter, or Tecnomatix are now used by major industrial players in automotive, aerospace, and energy sectors.

A Dominant Presence in Industry 4.0

Siemens stands out for its ability to cover the entire industrial value chain:

• Product design (PLM)
• Simulation and engineering
• Production automation
• Data supervision and analysis
• Predictive maintenance

This vertical integration helps industrial companies reduce complexity and improve overall performance.

Siemens’ Digital Industries segment alone generates tens of billions of euros in revenue and posts some of the highest margins within the group.

Siemens’ Key Role in Modern Robotics

Even without producing robots, Siemens is indispensable to their operation.

Its solutions enable:

• Communication between robots and industrial systems
• Optimization of trajectories and production cycles
• Integration of robots into complex environments
• Centralization of data for real-time decision-making

In many factories, robots from different manufacturers operate on architectures controlled by Siemens technologies.

Artificial intelligence enables
more autonomous and responsive
factories.

This positions Siemens as a major player in the global robotics ecosystem.

Towards Autonomous, AI-Driven Factories

Siemens’ vision aligns with a trend toward increasingly autonomous factories.

AI integration already allows for:

• Predictive maintenance, reducing unplanned downtime by up to 50%
• Real-time process optimization
• Automation of operational decision-making

Several studies suggest that AI adoption in industry could generate more than $3 trillion in global economic value by 2030.

In this context, Siemens is heavily investing in industrial software and cloud platforms, notably through Siemens Xcelerator.

A Strategic Partner for Industrial Companies

For industrial companies, Siemens is not just a technology provider but a strategic partner.

Its solutions help:

• Accelerate digital transformation
• Reduce operational costs
• Improve quality and traceability
• Strengthen competitiveness

In an environment marked by cost pressures, energy transition, and industrial reshoring, these levers are essential.

While robotics often grabs attention, it is only part of the ongoing industrial transformation.

Players like Siemens play a fundamental role by providing the software and technological infrastructure that allows robots to operate efficiently and in coordination.

In the coming years, industrial competitiveness will depend on the ability to integrate these intelligent systems.

The question will no longer be just about choosing the right equipment, but about building an industrial architecture capable of adapting, learning, and evolving continuously.

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As a media partner, Robot Magazine will closely follow this new edition and invites its readers engineers, industrial leaders, integrators, and robotics enthusiasts to explore an event that embodies the ongoing transformation in factories and production lines.

A Comprehensive Overview of Modern Industry

Global Industrie stands out by bringing together the entire industrial value chain. While some events focus on a specific technology, Global Industrie takes a holistic approach: it connects players in robotics, production, subcontracting, and industrial digitalization.

For several days, thousands of professionals gather to discuss major technological advances that are redefining production models. The event typically hosts more than 2,000 exhibitors and tens of thousands of visitors from across Europe.

In the exhibition halls, visitors can discover:

• Next-generation industrial robots and cobots
• Advanced automation systems
• Additive manufacturing solutions
• Predictive maintenance technologies
• Innovations related to industrial artificial intelligence
• Automated logistics platforms

This diversity makes it a true barometer of European industrial innovation.

Robotics does not replace
humans; it multiplies their
potential.

Robotics at the Heart of Industrial Transformation

For Robot Magazine readers, robotics remains one of the main points of interest at the show. The stands dedicated to robotics and automation are among the most dynamic of the event.

International companies such as ABB Robotics, KUKA, Fanuc, and Universal Robots regularly showcase their latest innovations here.

Visitors can observe robots in action:

• Assembling mechanical parts
• Handling electronic components
• Collaborating with human operators
• Automating production lines

These demonstrations provide a concrete understanding of how robotic technologies are now integrated across all industrial sectors: automotive, aerospace, electronics, logistics, and food production.

Collaborative robotics, in particular, is growing in importance. Cobots allow companies of all sizes, including SMEs, to automate certain tasks while maintaining close interaction with human operators.

Industry 4.0: The Convergence of Robots, Data, and AI

Beyond robotics, Global Industrie highlights the major trends of Industry 4.0.

Today, factories are no longer just automated; they are becoming connected, intelligent, and data-driven. Industrial sensors, vision systems, AI, and software platforms play an increasingly central role in process optimization.

The show offers a concrete glimpse into this technological convergence.

Visitors can discover:

• Predictive maintenance solutions based on data analysis
• Digital twins for simulating production lines
• Industrial control platforms integrating AI
• Autonomous logistics systems using mobile robots and AGVs

This digital transformation is now a strategic challenge for European industry, which faces competitiveness, energy transition, and technological sovereignty issues.

A Hub for Industry Stakeholders

Global Industrie is not just an exhibition. It is also a space for networking and sharing experiences.

Numerous conferences and roundtables address major current industrial issues:

• Industrial reshoring
• Energy transition
• SME automation
• Technical skills shortages
• AI’s impact on industrial professions

These discussions are valuable for decision-makers seeking to anticipate sector developments and identify technologies that can enhance organizational performance.

The event also welcomes deep-tech startups developing tomorrow’s industrial technologies, offering visitors the chance to discover promising innovations that are still little known.

A Must-Attend Event for Professionals

For engineers, industrial leaders, and tech entrepreneurs, Global Industrie offers a unique opportunity to take the pulse of industrial innovation.

In just a few days, attendees can:

• Observe the latest robotic advancements
• Meet suppliers and technology partners
• Network with industry leaders
• Identify new collaboration opportunities

In a context where automation, AI, and robotics are transforming industrial models, events like this play a key role in connecting ecosystem players.

Robot Magazine explores the
technologies shaping the industry
of tomorrow.

Robot Magazine at the Heart of the Event

In a context marked by accelerating automation, the rise of industrial AI, and technological sovereignty challenges, Robot Magazine will focus on advanced robotics, factory digitalization, and the transition to a more sustainable industry. Visitors will discover demonstrations of next-generation industrial robots, collaborative cobots, predictive maintenance solutions, and AI-based industrial control platforms.

Numerous conferences and roundtables will also bring together industrial leaders, researchers, and startups to explore deep transformations in the manufacturing sector. For professionals in robotics and automation, this 2026 edition is a unique opportunity to discover the technologies that will shape the factories of tomorrow and to meet key players in the European industrial ecosystem.

As a media partner of Global Industrie, Robot Magazine will cover the show’s standout innovations.

Our teams will meet with industrialists, startups, and experts to share with our readers:

• Interviews with executives and engineers
• Analyses of robotics trends
• Technology demonstrations
• Reports from the heart of the exhibition halls

Our goal is simple: to highlight the technologies shaping tomorrow’s industry and give a voice to the actors driving this transformation.

See You at Global Industrie

Whether you are an engineer, entrepreneur, integrator, or simply passionate about industrial technologies, Global Industrie offers a unique chance to discover innovations reshaping the industrial landscape.

Robotics, AI, and automation are no longer futuristic concepts; they are at the core of industrial strategies.

And this is exactly what you will be able to observe, understand, and experience at this unmissable European industrial event.

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In this interview, Alex shares her perspective on how the global robotics and automation job market is evolving, which roles are proving hardest to hire, and what will define talent strategies in the years ahead.

How is the global job market in automation and robotics evolving right now?

The global job market in automation and robotics is clearly evolving. Activity is not evenly distributed across the sector, but demand remains strong in key growth areas, even as companies restructure and reprioritise their investments.

Today, organisations are focusing on roles that deliver direct strategic value. This includes deep technical expertise in robotics, mechatronics, autonomy, and AI, as well as commercial leaders capable of helping businesses scale responsibly and compete in increasingly crowded markets.

At the same time, hiring has become more targeted and selective. Employers are carefully balancing growth ambitions with cost optimisation and the need for operational maturity.

Which roles are currently the hardest to hire?

The most difficult roles to fill remain hands-on, senior technical positions. In particular, robotics, mechatronics, and autonomy or controls engineers with real-world deployment experience are in extremely short supply.

At the leadership level, companies also struggle to find client-facing technical leaders who combine deep engineering credibility with strong commercial and strategic capabilities. These professionals are expected to bridge innovation and execution, understand customer requirements, and clearly articulate the business value of advanced robotics solutions. That combination of technical depth, leadership, and customer orientation is exceptionally rare.

What skills make the biggest difference for candidates today?

Beyond pure technical expertise, the skills that truly differentiate candidates today are collaboration, influence, and adaptability.

Companies increasingly value professionals who can work seamlessly across engineering, product, and commercial teams, align diverse stakeholders, and adapt quickly to fast-evolving technologies and market conditions. Candidates who can operate comfortably at the intersection of technology, business, and customer engagement consistently stand out.

Are companies more open to international or remote talent than before?

Compared to the pre-COVID era, companies are unquestionably more open to international talent. Mobility and relocation are far more accepted, provided they align with the organisation’s business model and customer footprint.

Remote work, however, has become more nuanced. Fully remote roles have declined compared to the immediate post-COVID period, particularly in robotics. Where hardware, system integration, and customer proximity remain critical. That said, hybrid models and flexible arrangements are still widely used, especially for senior or highly specialised profiles.

In one sentence, what will define the robotics job market in the next five years?

The next five years in robotics hiring will be defined by the shift from automation to autonomy. Driving demand for engineers and leaders capable of scaling intelligent systems safely, reliably, and at industrial scale.

Interview published by Robot Magazine – covering the people, technologies, and decisions shaping the future of robotics and industrial automation.

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In practice, the strongest impact of AI and robotics emerges elsewhere, in what I call the invisible gaps of industry. These gaps are not technological shortcomings. They are disconnections between systems, teams, decisions, and timeframes. And it is precisely there that AI and robots quietly reshape industrial performance.

Understanding the Invisible Gaps

Most industrial environments are not lacking technology. On the contrary, they are saturated with it. ERP systems, MES platforms, quality tools, predictive maintenance software, robotics controllers each performs its role effectively in isolation. The problem arises when these systems fail to communicate meaningfully with one another.

Invisible gaps appear when:

• Data is collected but not reused beyond its original purpose.
• Quality issues are detected but not traced back to their root causes.
• Human expertise resolves incidents but is never captured or formalized.
• Decisions are taken locally without feedback loops across departments.

These gaps rarely trigger alarms. Instead, they generate friction: delays, rework, unnecessary downtime, and decision fatigue. Over time, they erode competitiveness more than any single technical failure.

The strongest impact of AI and robotics
emerges in the invisible gaps of industry,
not in what is most visible.

Why Automation Alone Is No Longer Enough

For decades, automation focused on replacing tasks. Robots took over repetitive motions; software replaced manual reporting. This approach delivered undeniable productivity gains, but it also introduced a new challenge: systemic complexity.

As automation increases, so does the volume of data, alerts, and interdependencies. Machines operate faster, but humans are left to reconcile fragmented information across multiple tools. The paradox is clear:
the more automated an industrial system becomes, the more expensive its blind spots become.

AI does not solve this by adding more intelligence. It solves it by creating connections.

Where AI Really Creates Value

The most valuable role of AI in industry is not decision-making in isolation, but interface-building between machines, people, and processes.

Connecting Machines and Humans

AI transforms raw machine signals into operational understanding. Instead of cryptic alarms, operators receive context: why a robot stopped, what pattern led to a fault, and which action is most effective. This reduces downtime and builds trust between humans and automated systems.

Connecting Departments

AI also acts as an organizational bridge. Production anomalies can inform procurement decisions. Quality deviations can be linked to specific supplier batches. Customer feedback can feed directly into design and manufacturing adjustments. Here, AI becomes connective tissue rather than a standalone analytics tool.

Connecting Timeframes

Most industrial systems operate in the present. AI links historical data, real-time signals, and predictive insights, enabling companies to shift from reactive problem-solving to proactive optimization.

Case Study 1: Closing Feedback Loops in Automotive Manufacturing

A European automotive supplier introduced collaborative robots to automate assembly tasks. While output increased, robot stoppages remained frequent. Initial investigations focused on robot performance, with limited results.

An AI-driven analysis combining robot sensor data, operator interventions, and quality outcomes revealed a hidden issue: small upstream variations in component tolerances were triggering downstream robot adjustments and stops.

By feeding these insights back into procurement and quality control, defect rates dropped by 30% and robot uptime improved significantly. The breakthrough came not from better robots, but from closing an invisible feedback loop between departments.

Case Study 2: From Detection to Decision in Quality Control

In a consumer electronics factory, AI-based computer vision systems were deployed to detect surface defects. Detection accuracy was high, but rejection rates increased, creating tension between production and quality teams.

The missing link was context. Defect data was not connected to machine settings or process parameters. Once vision outputs were integrated with production and maintenance data, recurring defects were traced to specific machine configurations.

The result was a 25% reduction in scrap and smoother collaboration across teams illustrating how AI creates value by connecting detection to actionable decisions.

Case Study 3: Reducing Cognitive Load in Predictive Maintenance

A process industry player implemented predictive maintenance using AI models capable of forecasting failures with high accuracy. Yet response times remained slow.

The issue was not prediction quality, but usability. Alerts lacked prioritization and operational context. By redesigning the system to align AI insights with human workflows clear urgency levels, recommended actions, and impact estimates maintenance teams reduced response times by 40%.

Once again, value emerged not from smarter algorithms, but from reducing cognitive load on humans.

AI is not a standalone tool;
it is the connective tissue that
turns detection into actionable
decisions.

Physical AI: When Intelligence Enters the Real World

A new layer is now emerging at the intersection of AI and robotics: Physical AI. Unlike traditional AI systems that operate primarily in digital environments optimizing data, forecasts, or workflows Physical AI is embedded directly into machines that perceive, decide, and act in the physical world. This includes robots that adapt their behavior in real time, autonomous systems that learn from human corrections, and machines capable of reasoning under uncertainty in unstructured environments.

Physical AI amplifies the importance of invisible gaps. It only delivers value if perception, decision-making, motion, and human interaction are tightly connected. A robot equipped with Physical AI that can sense anomalies but cannot explain its intent, coordinate with upstream systems, or integrate human feedback simply relocates complexity rather than reducing it. Here again, value is created not by intelligence alone, but by how seamlessly physical action is connected to organizational understanding.

From Smart Machines to Connected Systems

The future of industry will not be defined by who deploys the most advanced robots or the most powerful AI models. It will belong to organizations that systematically identify and close invisible gaps between systems, teams, and decisions.

The key question is no longer “What can AI or robots do?”
It is “What are they failing to connect today?”

When this question becomes central, AI and robotics stop being experimental technologies. They become infrastructure quietly, but decisively, creating value where it truly matters.

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So, should we see these robots as a technologically alluring trend doomed to fade, or are we witnessing the emergence of a new industrial revolution, driven by AI, advanced robotics, and a global labor shortage?

Robot Magazine investigated this trend by analyzing recent advances, persistent limitations, and the industrial stakes that will determine the future of humanoids.

Why focus on humanoids now?

Five years ago, the question barely arose. Humanoids lacked:

• Energy autonomy

• Precision in manipulation

• Onboard computing power

• Stability in locomotion

• The ability to interpret the real world

But several developments have converged over the past three years:

1. The arrival of multimodal models capable of reasoning and manipulating
   Companies like OpenAI, Figure AI, and Tesla have introduced AI systems combining vision, language, planning, and action. These AI systems can explain why they perform a task, propose solutions, or adjust movements based on context.

2. The dramatic drop in computing costs
   NVIDIA platforms (Jetson, Orin, and now Blackwell) have lowered AI inference costs, enabling complex models to run on mobile robots.

3. Massive simulation
   Digital twins (Omniverse, Isaac Sim, Mujoco, Unreal Engine) allow humanoids to be trained in millions of virtual scenarios before entering the real world.

4. A structural labor shortage
   Logistics, healthcare, agriculture, hospitality, recycling industries are looking for solutions to difficult, repetitive, or physically demanding tasks.

These factors have shifted humanoids from an imagined future to an operational one.

Humanoid robots are not designed
to replace humans but to take over
tasks that no one wants or can perform
anymore.

What can humanoids really do today?

Public demonstrations sometimes make humanoids appear clumsy. Yet in industrial settings, their real capabilities are much more impressive.

1. Versatile manipulation
   Most new humanoids can:

   • Grasp fragile objects

   • Screw, unscrew, assemble

   • Sort irregular parts

   • Adjust movements using tactile feedback

   Robotic hands are now among the most advanced components, sometimes comparable to human hands.

2. Dynamic locomotion
   Recent bipedal robots can:

   • Climb stairs

   • Overcome obstacles

   • Navigate unstructured environments

   • Avoid people in real time

   The goal is no longer just to walk, but to walk usefully.

3. Real-time 3D perception
   They use combinations of:

   • LiDAR

   • Stereo cameras

   • IMUs

   • RGB-D cameras

   • AI models for segmentation and detection

   Result: they understand their environment much more richly.

4. Collaborative work
   Humanoids can interact with humans, recognize gestures, follow voice commands, or coordinate with other robots.

Why are industries finally taking notice?

The main advantage of humanoids is not technical but economic and logistical.

1. A robot that integrates into human environments
   Unlike industrial arms, AGVs, or AMRs, a humanoid:

   • Doesn’t need a redesigned workspace

   • Doesn’t require full-line automation

   • Works with existing tools

   • Can replace or assist an operator in a specific task

   It fits into human infrastructure rather than imposing it.

2. Unprecedented versatility
   A humanoid can change roles like a temporary worker:

   • Morning: handling

   • Afternoon: sorting and inspection

   • Evening: packaging

   This flexibility reduces the ROI threshold for investment.

3. A response to labor shortages
   In logistics, hospitality, or industry, some tasks simply have no candidates. Humanoids don’t replace skilled jobs but fill unstaffed positions.

The limits: not everything is ready for industrialization

Enthusiasm is real, but obstacles remain.

1. Cost
   A humanoid costs €60,000–€150,000 today, not including maintenance.

2. Energy autonomy
   Most operate 1.5–3 hours per charge, requiring:

   • Extra batteries

   • Quick-swap stations

   • Smart cycling

3. Robustness
   Bipedal robots remain vulnerable to shocks, dust, temperature changes, and extreme humidity compared to industrial arms.

4. Regulations
   Humanoids must comply with standards:

   • CE

   • ISO 10218

   • ISO 15066

   • ISO 13482 for personal robots

   Full safety certification remains complex.

Fad or revolution? Both, actually

A clear media effect
Viral videos of robots running or folding laundry generate buzz but can misrepresent real industrial contexts. Humanoids spark imagination, leading to both hype and skepticism.

But a structural revolution is underway
The real transformation isn’t in the humanoid shape but in:

• Context-aware robots

• Able to perceive

• Understand tasks

• Adapt to variability

• Collaborate with humans

Humanoids are a vehicle for a deeper revolution: the rise of intelligent, versatile robots.

Industry adopts humanoids not out
of fascination, but necessity: available
human labor is no longer enough.

2026–2032: What will really change

1. Massive pilot deployments
   Fleets of 100–1,000 humanoids will be deployed in logistics and modular factories.

2. Industrial standardization
   Humanoids will enter CE and ISO norms with adapted certification procedures.

3. Specialized humanoids
   Expect:

   • Handling humanoids

   • Quality inspection humanoids

   • Service humanoids

   • Agricultural humanoids

4. Integration with cloud/AI ecosystems
   Humanoids will become physical agents in multicloud architectures (Microsoft, Google, AWS) with:

   • Digital twins

   • Remote supervision

   • Shared global learning

   • Continuous optimization

The humanoid form is not a gimmick it’s an emerging standard.

Humanoid robots aren’t a universal solution but offer compatibility with human-built environments.

The question isn’t whether they will replace industrial arms or AGVs but whether they will become an additional tool for non-standardized, varied, and unpredictable tasks.

In 2026, everything indicates that humanoids are both:

• A media-fueled trend

• The start of a deep industrial revolution

Reality lies in between: they won’t dominate all workshops but will become essential where versatility, adaptability, and perception matter.

Robot Magazine will continue tracking this transformation, as humanoids’ arrival in industry could redefine the very concept of automated work.

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The German manufacturer KUKA, a pioneer in industrial robotics, announces a major step forward in making automation more accessible. With its new single controller paired with the iiQKA.OS2 operating system, the company offers an integrated approach designed to simplify the commissioning and operation of robots, whether for beginners or experts.

An Integrated Approach to Simplify Robotics

Historically, programming and managing industrial robots required highly specialized technical skills, often specific to each robot type. iiQKA.OS2 aims to simplify this complexity by combining hardware and software in a unified environment. This integration allows operators to configure, program, and monitor robots from a centralized interface, with a reduced learning curve.

With iiQKA.OS2, KUKA makes industrial
robotics more accessible for beginners
and experts alike.

An Intuitive Interface for All Levels

KUKA emphasizes that iiQKA.OS2 is designed to be intuitive. The user interface, based on ergonomic principles, guides users step by step while offering advanced functions for experienced operators. This could shorten training times and improve productivity in a variety of industrial settings, from automotive assembly to precision handling.

Modularity and Industrial Compatibility

The system is also modular and compatible with current industrial standards, making it easier to integrate into existing facilities or hybrid production architectures. According to KUKA, this approach encourages faster adoption of automation, particularly among small and medium-sized enterprises (SMEs) that may hesitate due to the complexity or cost of robotic solutions.

More than a system, iiQKA.OS2 is a
gateway to flexible and reliable
automation.

Making Automation Accessible to SMEs

With iiQKA.OS2, KUKA focuses on accessibility and flexibility while maintaining the performance and reliability that define its robots. While this development may not revolutionize robotics itself. It could help democratize industrial robot usage and reduce the technical barriers that still limit many companies.

KUKA makes automation and robot control easier than ever for both beginners and experts with its single controller and all-in-one operating system.

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While Microsoft is betting on AI + Edge integration through Azure, and NVIDIA is driving the era of the “Full Digital Twin” with Omniverse and Jetson, Google is advancing with a strategy that is less publicized but extremely transformative: unifying industrial infrastructure around its cloud, its multimodal AI models, and its robotics subsidiary Intrinsic, to create robotics that is more adaptable, more autonomous, and massively scalable.

This report provides an in-depth analysis of how Google is redefining the technological foundations of Factory 5.0.

1. A Complete Vision: AI + Perception + Cloud + Simulation

While traditional robotics relies on explicit programming, autonomous robotics requires robots capable of understanding their environment, learning continuously, and optimizing their actions in real time.
It is precisely in this grey area between advanced perception, generative AI, and cognitive automation that Google is building a decisive advantage.

Google’s approach is based on three pillars:

1.1. Cloud Infrastructure: Google Cloud Vertex AI & Edge TPU

Google Cloud positions itself as a robotics platform in its own right. Thanks to:

• Vertex AI to train, deploy, and manage models both in situ and at the edge
• Edge TPUs enabling high-performance local AI execution on robots
• Anthos to orchestrate industrial workloads across cloud, on-premise, and edge
• Gemini multimodal APIs capable of processing vision, language, actions, and robotic sequences

Google transforms every robot into a cloud-native device.

Robotics is no longer a closed system: it becomes a distributed infrastructure.

1.2. Advanced Perception: 3D Vision, Multimodality & Self-Supervised Learning

Google’s long-standing leadership in computer vision deeply influences robotics:

• Large-scale 3D segmentation (from Google Maps & Street View)
• Multimodal perception models (Gemini vision-action)
• Pretrained motor skills learned from millions of robotic sequences
• Reconstruction of complex industrial environments using NeRF and 3D Gaussian Splatting

In Factory 5.0 where robots and humans collaborate this perception becomes essential: it enables anomaly detection, collision anticipation, trajectory optimization, and real-time process adaptation.

1.3. Large-Scale Simulation

Google benefits from a major but rarely highlighted advantage: its simulation engines developed by DeepMind and internal research teams.

Intrinsic, for example, uses advanced physical simulators to:

• Generate thousands of manipulation scenarios
• Optimize trajectories
• Automate calibration
• Build ultra-precise industrial digital twins

These capabilities, once restricted to research labs, are now accessible through Google Cloud.

2. Intrinsic: The Cornerstone of Robotic Industrialization

Founded in 2021 within Alphabet, Intrinsic is the tangible embodiment of Google’s robotics ambitions. Its mission: abstract the complexity of industrial robotics and make it programmable like software.

2.1. Reprogrammable Robots Without Coding

Intrinsic is developing a platform where robots are no longer programmed with low-level code but instead with:

• No-code interfaces
• Video-to-action demonstrations
• Natural-language instructions (Gemini for Robotics)
• Pretrained skills (pick, place, assemble, manipulate)

An engineer can simply show a task to a robot and let the AI automatically extract:

• trajectories
• dynamic constraints
• contact handling
• assembly sequences

This drastically lowers the barrier to automation.

2.2. Broad Compatibility With Industrial Robots

Intrinsic does not manufacture robots it integrates with existing ecosystems:

• KUKA
• Fanuc
• ABB
• Universal Robots
• Yaskawa

The goal: create a universal software layer for the entire robotics market.

2.3. The Strategic Partnership With Siemens

In 2023, Siemens and Intrinsic announced a major collaboration: integrating Intrinsic’s platform into Siemens Xcelerator for PLM and automation.

This opens the door to:

• AI-powered industrial automation programming
• Collaborative robotics in heavy industry
• Digital-twin + AI + robotics pipelines connected to Google Cloud

It is one of the most strategic alliances shaping the future of the sector.

3. Google and Factory 5.0: A New Industrial Architecture

Factory 5.0 is not only automated: it is intelligent, adaptive, and collaborative.
Google is pushing a model where:

3.1. Every Machine Becomes an Intelligent Node

Thanks to the cloud and edge, robots exchange in real time:

• perception data
• AI predictions
• sensorimotor feedback
• trajectory planning

A production line becomes a “multi-agent system” continuously orchestrated by Google Cloud.

3.2. Robots Learn From Each Other

With shared models on Vertex AI:

• A robot learning a task in one factory can transmit its “skills” to every robot in the network
• Google is creating the first distributed robotic collective memory

This is the Tesla fleet learning model transposed to industrial robotics.

3.3. Humans + Robots: Augmented Collaboration

Factory 5.0 puts humans at the center. Google provides:

• Gemini as a universal human-robot interface (language + vision)
• ARCore to guide operators with augmented reality
• Robots able to understand human context (gestures, intent, safety)

Human-robot symbiosis becomes operational reality.

4. Impact on the Global Supply Chain

The integration of Google’s AI into robotics deeply transforms supply chains:

4.1. Flexible Automation

Production lines become reconfigurable in minutes instead of weeks.

4.2. Predictive Maintenance + Energy Optimization

Google’s models trained on massive datasets make it possible to:

• predict failures
• optimize electricity consumption
• reduce downtime

4.3. Mass Customization = On-Demand Production

Factory 5.0 powered by AI + perception allows:

• micro-series
• dynamic assembly
• customer-centric production

Robots can switch tasks multiple times per day.

5. Challenges and Limits of Google’s Strategy

Despite its ambition, Google faces several obstacles.

5.1. Industrial Integration

Heavy industry is conservative.
Introducing AI into critical environments requires:

• regulatory validation
• real-time robustness
• advanced cybersecurity

5.2. Lack of Standardized Adoption

Robotics is still fragmented by proprietary standards.
Google’s push toward universality will take time.

5.3. Industrial Sovereignty

European and Asian clients may hesitate to entrust production data to an American cloud.

Google is multiplying partnerships to address this concern, but it remains a sensitive topic.

6. Google Is Creating a New Grammar of Automation

With Google Cloud, Gemini, Intrinsic, and its perception expertise, Google is profoundly reshaping industrial robotics.
The company is not merely competing with traditional robotics players: it is restructuring the industry around a new cognitive infrastructure.

In Factory 5.0:

• Perception becomes an API
• Robots learn like AI models
• Programming is replaced by demonstration
• The cloud becomes the backbone of automation
• Robots cooperate as a network

Google isn’t building robots
Google is building the global platform that will allow all robots to become truly autonomous.

This is arguably the most ambitious industrial strategy of the decade.

FAQ – Google Cloud, AI and Autonomous Robotics in Factory 5.0

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In a region with a strong industrial culture, Cetim’s presence takes on a particular significance: that of an organisation capable of making technologies often seen as “too complex” or “too futuristic” for SMEs more accessible, as highlighted by the testimony of Michael Grandidier, Operations Director at Fameca. The 2025 edition will therefore shine a spotlight on two innovations: a multi-sensor cobot cell dedicated to quality control, and IANote, an AI demonstrator capable of detecting anomalies in just a few seconds.

A Multi-Sensor Cobot Cell to Revolutionize Quality Control

The first solution presented by Cetim perfectly illustrates the rapid evolution of collaborative robotics in industry. It is a multi-sensor cobot cell designed to conduct feasibility studies for quality control under semi-industrial conditions.

Equipped with a latest-generation cobot, this cell can integrate various inspection technologies:

• material health monitoring,

• visual defect inspection,

• dimensional control,

• advanced non-destructive testing techniques,

• smart sensors and vision modules.

One of the major strengths of this demonstrator is its flexibility: manufacturers can combine several technologies, either successively or simultaneously, to identify the most relevant inspection solution for their parts and workflows.

Cetim will also present a real-world application on a welded mechanical assembly, showing how a collaborative robot can standardize and automate inspection tasks that are typically long and repetitive. The objective is clear: enhance repeatability, reduce human error, and allow operators to focus on higher-value tasks.

This cell aligns with the current evolution of French factories, where cobots no longer merely assist they optimize, secure, and enhance key processes.

IANote: An AI Demonstrator That Trains Its Models in 5 Seconds

The other innovation showcased at BE 5.0 will be presented as a premiere: the IANote demonstrator, an artificial intelligence solution dedicated to detecting anomalies on industrial parts.

While traditional systems require long and tedious training phases, IANote stands out thanks to an unprecedented capability:

ultra-fast training in just 5 seconds,
performed directly on defect-free parts,
requiring no prior database or expert configuration.

In practice, the AI instantly calibrates itself on a compliant part, then detects any surface, appearance or geometric anomaly in real time. This “zero defect, zero history” approach opens new possibilities, especially for production lines with short series or frequent product changes.

IANote reflects a major trend in industrial robotics: the rise of embedded AI fast, intuitive, field-ready, and operable directly by production teams, without the need for data scientists.

Circular Economy: Another Pillar of Industrial Transformation

Cetim’s booth will also highlight several achievements related to the circular economy a domain increasingly central to industrial strategies. Showcased items will include:

• eco-designed products,

• parts containing recycled materials,

• examples of retrofitted industrial equipment,

• demonstrators focused on extending lifespan.

These projects illustrate Cetim’s ability to support both technological modernization and the ecological transition of manufacturers.

A Conference on Connected Hydraulic Systems

One of the key highlights of the event will be a technical conference led by Nicolas Bedouin, an expert from Cetim, on Tuesday, November 25, from 10:45 to 11:15 AM (Jupiter room). The theme:

“Connected hydraulic units, IIoT and industrial monitoring.”

A topic that resonates with current industrial concerns: how to make hydraulic systems smarter, more predictive, and more energy-efficient through sensors and connectivity.

Quatrium Grand Est: An Acceleration Platform for Manufacturers

All showcased innovations come from Quatrium Grand Est, the acceleration platform located at KM0 in Mulhouse. This structure offers:

• personalized diagnostics,

• assistance in defining an action plan,

• support for selecting technical solutions,

• guidance through industrialization,

• a network of technological, financial, and training partners.

Manufacturers can test technologies on their own parts a key advantage for mitigating investment risks.

Cetim: More Central Than Ever to Industrial Transformation

With more than 1,100 experts, engineers, and PhDs, Cetim confirms at BE 5.0 its central role in modernizing French factories and integrating key technologies of the industry of the future: collaborative robotics, AI, smart sensors, monitoring, circular economy, and automation.

By focusing on concrete, testable, and rapidly deployable solutions, the institution positions itself as a strategic partner for a more efficient, sustainable, and competitive industry.

FAQ – BE 5.0 Trade Show and Cetim Innovations (2025)

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