![]() Embodied AI Market Projected to Reach $23.06 billion by 2030The embodied AI market is projected to reach USD 23.06 billion in 2030 from USD 4.44 billion in 2025, growing at a CAGR of 39.0%.
By: MarketsandMarkets By level of embodiment, the Level 2: Intermediate Embodiment segment is projected to hold the largest market share in 2025. Level 2: Intermediate Embodiment leads the embodied AI market, driven by the adoption of AI agents that perceive their environment, learn from data, and adapt to changing tasks. These systems balance autonomy and controllability, making them ideal for logistics, manufacturing, and healthcare, where real-time adaptability is critical. Use cases like smart robots in warehouses, surgical assistants in hospitals, and adaptive inspection bots in factories propel demand for this level of embodiment. Integration of machine learning and edge AI enhances responsiveness and intelligence. Companies like ABB, KUKA, Agility Robotics, and Boston Dynamics are deploying learning-enabled robots for context-aware behavior and operational optimization. Innovations in reinforcement learning, real-time path planning, and sensor fusion expand the application scope of intermediate embodied AI. As enterprises prioritize operational flexibility and human-robot collaboration, Level 2 systems are preferred for scalable deployment, driving market growth during the forecast period. The Logistics & Supply Chain vertical is expected to register the highest CAGR in the embodied ai market during the forecast period. The logistics & supply chain vertical is expected to grow at the highest CAGR in the embodied AI market, driven by the accelerating need for autonomous material handling, inventory optimization, and last-mile delivery efficiency. As global supply chains become increasingly complex and consumer demand for faster fulfillment rises, companies are adopting embodied AI solutions such as autonomous mobile robots (AMRs), AI-enabled sorting systems, and collaborative picking robots. These intelligent systems combine perception, motion planning, and AI-driven decision-making to navigate dynamic environments, improve order accuracy, and reduce reliance on manual labor. For more info: https://www.prnewswire.com/ End
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