Until recently, AI was defined by large language models, or LLMs, and chatbots, but for many of us, using AI to help source and manufacture complex mechanical parts, like those used in robotics, has been in progress for over a decade. But in the corridors of modern manufacturing and logistics, the conversation has pivoted toward something much more tangible. We are entering the era of real-world physical AI. Humanoids, formerly the stuff of science fiction, are integrated into the daily work of companies like Amazon. As vice president of business development at Fictiv, I speak daily with innovators who are moving beyond the digital screen and into the physical world. Physical AI is the synthesis of neural networks with mechanical precision. It is the bridge between the logic of a machine and the physical environment with one major caveat: We must distinguish between the hype of humanoid robots and the reality of scaling hardware in a challenging global supply chain. Physical AI changes the fundamental “brain” of the machine. With computer vision, reinforcement learning, and edge computing, robots are gaining a sense of spatial intelligence. They no longer require a scripted environment; they can perceive, adapt, and learn. This is reshaping development by shortening the feedback loop. We are seeing “sim-to-real” pipelines where AI agents are trained in hyper-realistic digital twins, performing millions of iterations in hours before ever touching a physical gear. This shifts the developer’s role from “coder” to “trainer,” allowing for robots to handle high-variability tasks—such as sorting unstructured scrap metal or navigating a crowded hospital hallway—that were previously impossible to automate.

Full opinion : At Fictiv, we see the “scaling wall” as the primary hurdle for robotics companies in 2026.

For more see the OODA Company Profile on Fictiv.