Dead time frequently appears in many industrial processes and is a challenge for control systems because of the stability and performance problems that it generates. Various approaches, including controllers based on a process model and model-free controllers, have dealt with the dead time effects. However, classic controllers such as PID can sometimes perform poorly in the presence of long or variable dead time. This study proposes implementing an intelligent Proportional Integral (iPI) controller for nonlinear processes with variable dead time, focusing on a mixing tank application. The implemented iPI controller utilizes data-driven methods and a particle swarm optimization algorithm for controller tuning. To our knowledge, no existing iPID solutions exist for systems with variable dead time, highlighting the novelty of this proposal. The performance of the iPI controller is evaluated and compared against PI and sliding mode controllers. Simulation results show that the iPI controller exhibits performance indexes, such as ISE (integral square error) and ISCO (integral squared of control output), which are better than the PI controller and comparable with sliding mode control. This behavior shows the feasibility of the iPI controller in managing systems with variable dead time, offering promising insights for future control strategies. © 2024 IEEE.