Citi: Data Scarcity and High Costs Slow Physical AI Robotics Commercialization; Locus Robotics, Dexterity Emerge as Winners

According to Citi analyst Heath Terry at the firm's robotics conference on July 7, data scarcity and high deployment costs remain the core constraints to Physical AI commercialization, despite accelerating demand. Terry noted that unlike digital AI, each new robotic scenario requires accumulating proprietary real-world data from scratch, coupled with specialized hardware and safety certification challenges.

The report identified Locus Robotics and Dexterity as the leading performers, crediting their success to focusing on high-pain-point use cases, adopting the Robot-as-a-Service (RaaS) model to lower customer barriers, and prioritizing safety over model complexity. Terry characterized Physical AI as a "decade-long marathon," with long-term value accruing to companies mastering data flywheel loops and achieving the highest safety standards.