The future of physical AI isn’t humanoid; it’s task-specific and cost-efficient

The future of physical AI isn’t humanoid; it’s task-specific and cost-efficient">

Artificial intelligence has evolved significantly over the years, from perception and generation to complex workflow coordination. However, AI has largely remained confined to the digital world. That is now changing with the emergence of physical AI, which interacts directly with the real world, navigating environments, manipulating objects, and making decisions with immediate consequences.

The next phase of AI requires a different operating model, a continuous loop where sensing, reasoning, and action happen simultaneously. Machines must continuously interpret their surroundings, reason about what they observe, and act on those insights in real time, adapting instantly as conditions change. This level of autonomy and real-time decision-making requires tightly integrated, on-device intelligence, making edge compute essential.

The primary limitation in robotics today is not intelligence; it's the physical world: hardware capabilities, dexterity, energy efficiency, and cost. Building a robot that can perform a wide range of human tasks requires highly sophisticated mechanical systems. As a result, general-purpose humanoid robots are likely to remain limited to niche, high-cost applications in the near term.

Instead, most robots being deployed today are designed to do one specific task very well. Task-specific robots focus on defined use cases within controlled or semi-structured environments. These systems rely on real-time sense-think-act loops running locally on embedded AI processors, allowing them to operate autonomously without constant cloud dependency.

The future of robotics will not be defined by a small number of machines attempting to do everything. It will be defined by millions of intelligent systems, each designed for a specific purpose, operating where they create value. These systems will prioritize responsiveness, efficiency, and reliability over generality and will scale across industries that demand practical, cost-effective solutions.

According to Yaniv Sulkes, vice president for physical AI at Hailo, "The future of physical AI is about making intelligence actionable – embedded directly into the physical world, where decisions must be made instantly and performance is measured in outcomes. And in that world, the edge is not just an architectural choice. It is a requirement."