The adoption of humanoid robots will mirror that of autonomous vehicles: focus on achievable, single-task applications first. Instead of a complex, general-purpose home robot, the market will first embrace robots trained for specific, repeatable industrial tasks like warehouse logistics or shelf stocking.

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The future of humanoid robotics is not in our homes. While they will revolutionize structured B2B environments like 'dark' factories and data centers, consumer adoption will lag significantly due to a fundamental lack of desire for robots in personal, nuanced spaces.

While consumer robots are flashy, the real robotics revolution will start in manufacturing. Specialized B2B robots offer immediate, massive ROI for companies that can afford them. The winner will be the company that addresses factories first and then adapts that technology for the home, not the other way around.

Companies developing humanoid robots, like One X, market a vision of autonomy but will initially ship a teleoperated product. This "human-in-the-loop" model allows them to enter the market and gather data while full autonomy is still in development.

Leading robotics companies are taking different paths to market. Boston Dynamics targets industrial use cases (e.g., DHL, BP). In contrast, both Figure AI and 1X are now focused on the home, but 1X is moving more aggressively by accepting consumer pre-orders first.

The current excitement for consumer humanoid robots mirrors the premature hype cycle of VR in the early 2010s. Robotics experts argue that practical, revenue-generating applications are not in the home but in specific industrial settings like warehouses and factories, where the technology is already commercially viable.

The dream of a do-everything humanoid is a top-down approach that will take a long time. Roboticist Ken Goldberg argues for a bottom-up strategy: master specific, valuable tasks like folding clothes or making coffee reliably first. General intelligence will emerge from combining these skills over time.

While 2025 saw major advancements for robots in commercial settings like autonomous driving (Waymo) and logistics (Amazon), consumer-facing humanoid robots remain impractical. They lack the fine motor skills and dexterity required for complex household chores, failing the metaphorical "laundry test."

Initially, factories seemed like the easier first market for humanoids due to structured environments. However, Figure's founder now believes the home is a more near-term opportunity. The challenge of environmental variability is now seen as a data-bound problem that can be solved with large-scale data collection programs.

The founder of robotics OS Lightberry argues that the industry's "ChatGPT moment" won't be when a robot can fold laundry. Instead, it will be when robots are commonly seen interacting with people in public roles—as shop assistants, event staff, or security—achieving social acceptance first.

Car companies are uniquely positioned to build humanoid robots. They possess deep expertise in mass manufacturing complex systems with chips and batteries, and they are already heavy users of robotics in their own factories, giving them a significant advantage in the emerging market.