The Rise of Intelligent Robotics: A Vision for Industrial and Humanoid Automation

Explore what is driving Qualcomm to jump into robotics, including their vision in the industrial sector and why robotic automation and physical AI will dominate over the next 5 years.

The Wrap Up!

This ExecChat launched at #CES2026 explores the rapid emergence of industrial, autonomous mobile, and humanoid robotics, with a focus on Qualcomm’s strategic role in enabling “physical AI” at the edge. As AI, sensors, and compute converge, robotics is moving from highly specialized automation toward general-purpose, intelligent systems capable of perception, reasoning, and safe interaction with humans.
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Qualcomm Technologies’ Executive Vice President and Group General Manager of Automotive, Industrial and Embedded IoT, and Robotics outlines how the company’s long-standing investments in edge AI, semiconductors, safety-critical systems, and automotive autonomy uniquely position it to scale robotics beginning in 2026. The discussion highlights that robotics is fundamentally an edge-first, real-time application, requiring low latency, multimodal sensor fusion, power efficiency, and safety; areas where Qualcomm already operates at scale.
A central theme is physical AI: the ability for machines to sense, understand, plan, and act in the physical world. This includes locomotion, object manipulation, dexterity, and reasoning—capabilities that are now converging due to advances in AI models, data availability, and edge compute. While mobility and navigation are largely solved (drawing parallels to autonomous driving), generalized manipulation and skill transferability represent the next major breakthrough.

The conversation also addresses human–robot collaboration, emphasizing safety, awareness, and guardrails as robots increasingly share environments with people. Rather than displacing workers, robotics is positioned as a response to labor shortages, declining workforce participation, and productivity demands, particularly in manufacturing, logistics, healthcare, hospitality, security, and enterprise services.
Finally, the discussion underscores that successful adoption depends on clear utility value, social acceptance, and scalable platforms. Robotics adoption will accelerate first in environments where value is obvious and risk is manageable, before expanding more broadly. Over the next 5–10 years, platforms that support multiple skills, continuous learning, and broad deployment across industries are expected to drive widespread adoption.

Key Takeaway: Robotics is entering a decisive scaling phase. By leveraging edge AI, automotive autonomy learnings, and safety-first semiconductor design, Qualcomm aims to enable the next generation of intelligent, adaptable robots that enhance productivity, safety, and human collaboration across industries.

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