Intel and CODESYS Partner to Bring Advanced AI to Industrial Edge PLCs, Revolutionizing Manufacturing Automation

Intel and CODESYS have announced a strategic partnership aimed at embedding advanced AI capabilities directly into industrial Programmable Logic Controllers (PLCs). This initiative seeks to revolutionize manufacturing automation by enabling PLCs to leverage AI for real-time data analysis, predictive maintenance, and optimized operational control. The collaboration will be further explored in a fireside chat webinar on October 14, 2026, titled “Artificial Intelligence on the Edge,” where both companies will discuss the technical requirements, challenges, and future of edge AI in manufacturing. This development is crucial for practitioners in the industrial sector, particularly those involved in operational technology (OT) and automation. The ability to integrate AI directly into PLCs means that complex analytical tasks and decision-making processes can occur at the very edge of the network, close to the machinery and sensors generating the data. This significantly reduces reliance on centralized cloud infrastructure for immediate insights, leading to lower latency, enhanced security, and improved operational resilience. For engineers, this translates into more intelligent control systems that can adapt to changing conditions, predict potential failures, and optimize production lines with greater autonomy. The partnership also addresses the growing demand for data-driven decision-making in manufacturing, enabling more efficient resource utilization and higher quality output. The move by Intel and CODESYS aligns with the broader trend of pushing computational intelligence closer to the data source, a fundamental principle of edge computing. In the wider cloud and DevOps landscape, this mirrors the shift towards distributed architectures and the increasing adoption of edge AI for various applications, from smart cities to autonomous vehicles. The integration of AI into industrial control systems is a natural progression, building on established trends in IoT adoption and the need for real-time processing in critical infrastructure. Other developments, such as the increasing demand for edge servers, AI chips, and real-time data processing in industries like financial services, retail, and healthcare, underscore the pervasive nature of this shift. In practice, this partnership means that manufacturing engineers and automation specialists should begin to familiarize themselves with AI/ML concepts and their application within PLC programming environments. The webinar on "Artificial Intelligence on the Edge" will be a valuable resource for understanding the technical implications and practical deployment strategies. Practitioners should also consider the implications for their existing infrastructure, including network capabilities and data governance, as more intelligence moves to the edge. The long-term impact will likely include a demand for new skill sets in OT teams, blending traditional control engineering with data science and AI expertise. This collaboration signals a future where industrial automation is not just reactive but proactively intelligent, driven by AI at the very heart of operations.