Kuka unveils a new era of AI-powered automation at Nvidia GTC 2026
Nvidia GTC 2026 took place from March 16 to 19 in San Jose, California, and put the industry face to face with something many had been expecting but few had seen so clearly: AI is no longer an optional feature — it has become essential infrastructure.
Jensen Huang, Nvidia CEO, was straightforward in his keynote. According to him, artificial intelligence is no longer an isolated innovation or a specific application — it is the foundation on which companies and nations will build the future. In his words, every company will use AI and every nation will build it. It was not a speech full of vague promises — it was a declaration of how the corporate and industrial world will operate going forward, with AI at the center of everything, not on the sidelines.
And it was precisely in this setting that Kuka showed up in full force. The German company, one of the biggest global names in industrial automation, took the Nvidia GTC stage to show that it is not just keeping up with this transformation — it is helping shape it. With the launch of Kuka AMP, its new AI-powered automation management platform, the company made it clear that industrial robots are entering a new phase, moving away from machines that follow fixed instructions toward systems that understand intent and make decisions autonomously. 🚀
What is Kuka AMP and why it matters so much
Kuka AMP, short for Automation Management Platform, is Kuka‘s answer to a question the industry has been asking for a while: how do you integrate real AI on the factory floor without turning it into a years-long project full of expensive customizations and integrations that break on the first update? The platform was designed to work as an intelligent layer connecting robots, control systems, operational data, and AI algorithms in a single unified environment, allowing managers and engineers to visualize, monitor, and optimize entire operations from a centralized point.
What makes Kuka AMP different from previous solutions is the depth of its AI integration. The platform does not just collect machine data and display pretty dashboards — it processes that information in real time and generates active recommendations, identifying bottlenecks before they become problems, suggesting programming adjustments based on historical equipment behavior, and anticipating maintenance needs with a precision that traditional systems simply cannot match. This completely changes the operational dynamic of a factory, because the operator stops being a firefighter and becomes a decision-maker with quality information at their fingertips.
Christoph Schell, CEO of Kuka Group, reinforced this point during the event. According to him, robots and automation systems are evolving from programmable machines to intelligent collaborators capable of learning, adapting, and operating safely alongside humans. With open platforms like Kuka AMP that connect traditional deterministic automation — the kind based on rules and pre-programming — with intent-based automation, the path from concept to deployment becomes faster, more precise, more cost-effective, and more autonomous.
On top of that, Kuka built AMP with an open architecture, meaning it can communicate with third-party systems, including ERP platforms, quality management software, and of course, solutions built on Nvidia infrastructure. This openness is not a minor technical detail — it is strategic. In an industrial ecosystem where every factory has a different history of technology investments, forcing a complete infrastructure replacement would be a massive barrier to adoption. With AMP, Kuka enters the existing environment and makes it smarter without requiring everything to be thrown out and rebuilt from scratch.
Automation 1.0 and 2.0 — a transition, not a replacement
One of the most interesting points Schell highlighted at the conference is that Kuka is not abandoning traditional automation. Quite the opposite. The company treats so-called Automation 1.0 — rule-based, deterministic, pre-programmed systems — as the foundation that continues to support the industry, especially in high-volume, high-safety-criticality environments.
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Automation 2.0, which Kuka also calls Physical AI, works as an additional layer. It brings flexibility, adaptability, and data-driven intelligence to complement what already works well. In Schell’s words, rule-based automation continues to deliver the stability and productivity that customers need. The idea is not to replace it but to expand it with intent-based and AI capabilities. Automation 1.0 remains the backbone, while 2.0 adds new layers of flexibility.
This pragmatic approach is an important differentiator because many technology companies fall into the trap of selling the new as a total break from the old. In practice, anyone who operates factories knows that abrupt transitions are risky, expensive, and often unfeasible. Kuka is acknowledging this reality and offering a path of gradual evolution, which makes it much easier for companies that still heavily depend on conventional systems to get on board.
The partnership with Nvidia and the role of digital twins
Kuka‘s presence at Nvidia GTC was no coincidence. The company has been deepening its collaboration with Nvidia to leverage the computational power of GPUs and AI models within its automation solutions. At the conference, Nvidia introduced important developments that connect directly to what Kuka is building, such as the Physical AI Data Factory Blueprint, designed to advance world modeling, humanoid robot skills, and autonomous driving, as well as the Omniverse DSX Blueprint, focused on digital twin simulation for AI factories.
Complementing these innovations, open-source agentic frameworks like OpenClaw extend the AI stack to operational levels, enabling long-running agents that use tools, memory, and messaging interfaces to orchestrate workflows, manage data pipelines, and execute tasks on dedicated machines autonomously.
One of the most discussed points in the presentation was the use of digital twins to test and validate changes to industrial processes before applying them on the actual production line. With physics simulation accelerated by Nvidia GPUs, it is possible to run hundreds of scenarios in minutes, identifying the most efficient configuration without stopping production or putting equipment at risk. For the industry, this represents a massive shift in how process optimization is done, which historically relied on slow and expensive empirical testing in the real environment.
The collaboration also opens the door for developing AI models specific to industrial contexts, something that generalist models simply cannot cover well. An automotive assembly line has completely different dynamics than a semiconductor fab or a pharmaceutical plant. By combining Nvidia‘s hardware and frameworks with Kuka‘s deep expertise in robotics and industrial processes, the partnership creates conditions for developing verticalized models trained on real shop-floor data that understand the specific context of each operation and deliver far more accurate results than any generic solution could.
Record R&D investment and global growth
The numbers behind this strategy show that Kuka is putting its money where its mouth is. In 2025, the company invested a record 213 million euros in research and development, the highest amount in its history. This investment supports the growth categories that Schell defined as priorities: intelligent automation and software- and AI-defined infrastructure.
Financially, the results are keeping pace. Kuka Group reported profitable revenue growth of 4 percent in 2025, with an increase in order intake — a clear indicator that the market is responding positively to the company’s positioning. Schell emphasized that Kuka’s modular production platforms are leading this movement and forming a solid foundation for long-term success.
China, the world’s largest robotics market, continues to be a strategic pillar for the company. In 2025, revenue from Kuka’s Chinese business surpassed 1 billion euros for the first time ever, a milestone that reflects the importance of the region, which accounts for more than 50 percent of global robotics demand. This performance shows that Kuka is not merely present in the planet’s largest market — it is growing rapidly within it.
Global expansion and new innovation centers
Kuka‘s global presence continues to expand strategically. In Asia, the company opened new training, research, and application centers. In Vietnam, it closed a partnership with the University of Danang to develop a state-of-the-art facility. In India, one of the fastest-growing automation markets in the world, Kuka is expanding its footprint to capitalize on the country’s medium- and long-term industrial growth.
In the United States, the company established a software and AI center of excellence in Silicon Valley, led by Marc Fleischmann and Melonee Wise, an award-winning robotics pioneer. It was Wise who presented the Kuka AMP platform during Nvidia GTC, showcasing its capabilities to a global audience of decision-makers and industry experts.
This geographic expansion is not just about commercial presence. By setting up research centers in strategic markets, Kuka ensures that its products are developed with local knowledge, adapted to the specific needs of each region, and ready to scale quickly when demand arises. It is an approach that combines global vision with local execution, something few automation companies manage to do consistently.
What changes in practice for people working in industrial automation
For those in the day-to-day trenches of industrial operations — whether as process engineers, plant managers, or systems integrators — what Kuka presented at Nvidia GTC has very concrete implications. The first is the reduction of robot setup and programming time. Today, programming an industrial robot for a new task can take days or weeks, depending on the complexity of the motion and the integrations required. With AI applied to the programming process, systems like Kuka AMP can learn from demonstrations, automatically adapt trajectories, and significantly cut that time, freeing technical teams to focus on optimization instead of repetitive manual configuration.
Another direct impact is on predictive maintenance. Industrial automation has always faced the challenge of balancing equipment uptime with maintenance costs. Calendar-based preventive maintenance often results in unnecessary interventions or, worse, failures that happen between two planned maintenance cycles. With Kuka AMP‘s AI algorithms continuously analyzing sensor data — vibration patterns, temperature, energy consumption, and kinematic behavior of the robots — the system can identify signs of wear well before they evolve into failures. This is not theory — it is already being applied in Kuka pilot installations around the world, with results showing significant reductions in unplanned downtime.
And then there is the scalability factor. One of the biggest pain points for anyone operating multiple industrial plants is the difficulty of standardizing processes and ensuring that a best practice identified in one factory is quickly replicated across the others. With a centralized platform like Kuka AMP, this knowledge transfer becomes much more agile because the AI models learn in one environment and can be deployed in others with far less friction. This transforms operational intelligence from a local asset into a corporate asset, something companies with distributed operations will feel directly in their bottom line. 💡
End-to-end solutions and flexible business models
Schell made a point of emphasizing that Kuka positions itself as one of the few global providers of end-to-end industrial automation solutions. This means the company does not just deliver robots — it offers a complete ecosystem that includes hardware, software, and integrated digital systems. The portfolio spans industrial and mobile robotics, simulation, shuttle systems, cranes, warehouse systems, and even healthcare automation.
Beyond traditional solutions, Kuka also offers Robots-as-a-Service (RaaS) models, where the customer contracts robotic capacity as a service without needing to buy and maintain the equipment themselves. The company also operates entire production plants and automated contract manufacturing facilities on behalf of its clients. For companies looking to accelerate their automation journey without taking on the full risk of capital investment, this type of model is extremely attractive.
This flexibility in the business model, combined with the technological depth of Kuka AMP and the partnership with Nvidia, creates a value proposition that is hard to replicate in the current market. Kuka is not just selling technology — it is selling operational outcomes, with shared accountability for system performance.
Why this moment is a milestone for the industry
Nvidia GTC 2026 will be remembered as the event where industrial AI stopped being a future promise and became an available product, with defined use cases, established partners, and a company the size of Kuka putting its decades-long reputation behind it. It is not every day that a company with more than 50 years of history in industrial robotics makes such a clear and public bet on artificial intelligence as its central development path. This signals to the entire market that the conversation has changed, and anyone still in the phase of evaluating whether it is worth investing in AI for automation is falling behind.
The broader context matters too. The global industry faces simultaneous pressures from multiple directions: rising operational costs, shortages of skilled labor, growing demands for product customization at scale, and the need to reduce waste to meet sustainability targets. None of these pressures have simple solutions, and all of them benefit directly from smarter automation. Kuka is positioning AMP right at the intersection of these needs, as a tool that addresses multiple problems at once instead of solving one specific point and creating new bottlenecks elsewhere.
What makes all of this even more relevant is that we are watching this movement happen in real time, with real products being demonstrated to a global audience of decision-makers. Nvidia GTC is not an academic event — it is where the technology sector shows what is going to happen in the coming years. Having Kuka at the center of that conversation, alongside Nvidia, says a lot about where industrial automation is headed. Tomorrow’s robots will not just execute — they will think, adapt, and collaborate. And that transition has already begun. 🤖
