I’ve been paying close attention to an interesting investment thesis lately: AI is fundamentally reshaping the robotics industry. This isn’t just a simple technical upgrade—it’s an accelerated turning point for the entire sector.

Over the past decade, robotics applications in industrial, defense, medical, logistics, and other fields have been growing steadily, but the real inflection point has appeared in the last five years. The key catalyst is the explosive growth of generative AI. Machine learning and computer vision are enabling robots to move beyond rigid, pre-programmed systems into intelligent agents that can learn, reason, and operate autonomously. The pace of breakthroughs is now completely different: developers no longer need to manually program every action—instead, they can quickly train robots on millions of scenarios in a virtual environment. Natural-language interaction has also significantly lowered the deployment threshold. That’s why I believe this track is worth focusing on.

Let’s look at a few companies that directly benefit. Tesla’s most underestimated aspect is right here—many people only see its electric vehicles, but in fact, it has long been a robotics company. Its autonomous driving system is already a mobile robot operating in real-world environments, powered by neural networks trained on billions of miles of driving data. Likewise, the same underlying AI is now driving the Optimus humanoid robot project. Optimus can perform repetitive and hazardous tasks in factories, warehouses, and even homes. Musk has said that, in the long run, this project could be more important than the car business—the goal is to produce millions of units per year, with consumer prices controlled at $20,000–$30,000. Recently, Tesla also announced it would shut down the high-end Model S and X production lines to free up capacity specifically for Optimus assembly lines. This strategic shift alone says a lot.

Next is NVIDIA. Everyone knows it’s the biggest beneficiary of AI chips, but its role in robotics runs even deeper. Modern robots need massive computing power to process perception, localization, mapping, and decision-making. The Jetson platform is tailor-made for edge AI, widely used in robot and drone systems to process visual and sensor data locally and enable low-latency decision-making. Its Isaac development platform allows engineers to simulate robot systems in highly realistic virtual environments, greatly accelerating innovation cycles while reducing risk and cost. NVIDIA isn’t just participating in robotics growth—it’s empowering the entire industry.

The transformation of Deere, the agricultural giant, is especially noteworthy. On the surface, it looks like a traditional heavy machinery company, but in reality it has become a data-driven automation platform. Its 8R tractors can operate fully autonomously, using AI vision and high-precision GPS navigation to work the fields. After acquiring Blue River, it launched the See & Spray system, which uses machine learning to distinguish crops from weeds in real time, precisely spraying herbicide rather than blindly coating everything. Behind these robotics applications is AI making decisions. The John Deere Operations Center integrates farm data to provide predictive analytics and optimize decisions around planting, harvesting, and maintenance. The potential to improve agricultural efficiency is still far from fully realized.

Teradyne sits in another critical position. As AI chips become increasingly complex and performance requirements keep rising, testing demands become even more stringent. Teradyne’s automated test equipment verifies the advanced chips needed for data centers, autonomous systems, and robotics applications. Last year’s Q4 earnings showed EPS of $1.80, far exceeding expectations; revenue rose 44% year over year to $1.08 billion, with AI-related demand accounting for the bulk. It also has a collaborative robotics business, manufacturing industrial robotic arms and mobile robots—systems that are increasingly integrating AI to enhance flexibility in factories and logistics centers. This is a typical “tooling” investment: it can benefit from chip testing during the automation wave, and also benefit from AI-enabled robot solutions.

Intuitive Surgical is a pioneer in the medical field. The da Vinci surgical system has already changed the precision of minimally invasive surgery. Now, AI is further deepening this advantage. It’s not just a hardware manufacturer—it’s building an intelligent surgical ecosystem. AI algorithms analyze data from surgeries in real time, enhance imaging clarity, and provide decision support for surgeons. The Ion endoluminal system uses AI vision to precisely navigate to hard-to-reach lung nodules, compensating for differences between preoperative imaging and real-time anatomy to improve diagnostic accuracy and patient outcomes. As global installation volumes increase, the accumulation of surgical data will continuously strengthen AI models—creating a flywheel effect that will gradually widen competitive barriers.

Overall, robots themselves aren’t new; what’s new is the speed of innovation. AI is compressing development cycles, improving adaptability, and expanding the scope of commercial applications. From autonomous driving to agriculture, from chip testing to the operating room, AI is acting as a multiplier. From an investment perspective, the main theme isn’t just robotics adoption—it’s the acceleration of AI-driven robotics. These five companies are at the forefront of this shift, because intelligence is now embedded directly into the machines themselves.