<p>Task allocation in multi-agent systems has become an important and challenging topic due to the complexity of application domains and the inherent difficulties in decision-making, particularly in industrial environments. Autonomy in task dispatching is a critical factor, achievable primarily through the use of appropriate sensing technologies. This paper presents a method for the autonomous assignment of industrial tasks to agents (humans and robots) with suitable capabilities. An ontology-based knowledge representation approach is proposed. A Radio Frequency Identification sensor system automatically detects the various entities present in the environment. The ontology-based decision-making system autonomously assigns tasks based on the information provided by the Radio Frequency Identification system, selecting the most appropriate agent for each task. Industrial tasks are allocated considering production lines, objects, agent’s capabilities, and other relevant parameters. The proposed solution is suitable for industrial applications, as modern manufacturing increasingly requires autonomy in decision-making processes. The results presented focus on illustrating the approach and its potential effectiveness in realistic industrial scenarios.</p>