The use of artificial intelligence in robotics is entering a phase of broader industrial adoption, according to a report by technology intelligence firm ABI Research. The study, The Landscape of AI in Industrial and Collaborative Robotics, finds that AI-enabled robots are reaching a level of maturity that allows them to perform complex and adaptable tasks, expanding opportunities for manufacturers and logistics operators.
The report indicates that advances in Dynamic Policy Adjustment (DPA) and robotics foundation models are narrowing the gap between simulated and real-world robotic performance. These developments, according to ABI Research, enable more flexible automation capable of adapting to changing environments without extensive reprogramming.
While established production lines continue to rely on conventional robotic systems, the report identifies growth potential in industries with lower automation levels and high variability, such as life sciences, semiconductor manufacturing, and logistics. These sectors require systems that can manage complex handling and manipulation tasks.
The report outlines progress in several AI technologies influencing robotics, including reinforcement learning, large language model interfaces for human-robot interaction, new SLAM and world modeling techniques, agentic AI, and advanced machine vision. ABI Research lists companies involved in developing these technologies, such as InBolt, Apera, NVIDIA, Cognex, Basler, Intel RealSense, and Universal Robots, as well as developers of robotics foundation models including Google DeepMind, Covariant, Meta, and Dexterity.
ABI Research states that the main challenge for the sector is converting technical progress into commercial scalability. The firm advises vendors to emphasize usability, transparency, and measurable returns on investment to encourage adoption. The report aims to provide guidance for organizations planning to integrate embodied AI systems into their operations.
