Integrating Artificial Intelligence with the Internet of Things in Industrial Environments The integration of Artificial Intelligence (AI) with the Internet of Things (IoT) in industrial environments represents a transformative shift toward smart manufacturing and Industry 4.0. This integration involves connecting industrial devices and sensors to the internet for continuous data collection, which is then analyzed using AI algorithms to extract predictive insights and support decision-making. As a result, industrial systems become more adaptive and responsive to operational changes. One of the key benefits of this integration is predictive maintenance, where machine data is analyzed to detect potential failures before they occur, reducing downtime and operational costs. Machine learning techniques also improve product quality by monitoring production processes in real time and automatically adjusting operational parameters. Industrial platforms developed by companies such as Siemens and General Electric demonstrate practical implementations of AI-IoT integration. Furthermore, this integration enhances smart supply chain management, optimizes energy consumption, and improves workplace safety by monitoring hazardous environments through connected sensors. The large volumes of industrial data generated by IoT devices enable data-driven strategic decisions instead of relying on conventional estimates. Despite its advantages, AI-IoT integration faces challenges related to cybersecurity, data privacy, and system interoperability. Implementing such systems requires advanced digital infrastructure and skilled professionals capable of managing intelligent platforms. Nevertheless, integrating AI with IoT remains a fundamental step toward building more efficient, sustainable, and intelligent industrial ecosystems.