Why AI Is Only As Effective As The World On Which It Trains

InnovationWhy AI Is Only As Effective As The World On Which It TrainsByAlexandre de Vigan,Forbes Councils Member.for Forbes Technology CouncilCOUNCIL POSTExpertise from Forbes Councils members, operated under license. Opinions expressed are those of the author. | Membership (fee-based)Jun 09, 2026, 10:00am EDTAlex de Vigan, CEO & Founder of Physicl, building world-ready data infrastructure powering robotics, world models, and Physical AI systems. gettyIn my last article, I wrote about the danger of building during an AI gold rush: when capital moves faster than understanding, founders can mistake momentum for foundations.That risk is now becoming especially clear in physical AI.The market is rightly excited about robots, world models and embodied systems that can understand and operate in real environments. The ambition is real. The investment is real. The demos are becoming more impressive every month.But beneath that excitement, the industry is approaching a more basic constraint: Physical AI cannot scale without the right data.AI systems are only as good as what they are trained on. For language models, the internet provided an enormous body of text, images and video. It was imperfect, but it existed. For physical AI, the equivalent training layer does not yet exist at anything close to the scale required.Robots and spatial models do not simply need more data. They need data that reflects reality: geometry, depth, materials, lighting, physics, occlusion and the countless variations that make the real world difficult to predict.That is the gap the industry now has to confront.The Real Bottleneck Is Training RealityThe phrase “synthetic data” is often used too broadly in AI discussions.For physical AI, synthetic data is only useful if it is grounded in physical consistency. It is not enough to generate visuals that look convincing to a human observer. A cup is not just a cup. It has a surface, a weight, a material, a center of gravity, a handle, a reflection, a...