In industries, the induction motor are more popular due to their brushless structure, low cost, low maintenance, and robust performance. However, the use of induction motor as AC drives becomes complex as it is a highly cross coupled machine. Over the decades various types of control methods are proposed for induction motor drives classified as scalar control and vector control techniques. The vector control technique enhances the performance of an AC Induction motor drive similar to that of a DC motor drive both under dynamic and steady state operating condition. The only issue that the vector control technique requires is coordinate transformation. In recent years, the development of Direct Torque Control (DTC) drive motors are gaining popularity due to its fast dynamic, response, and simple control structure. In order to enhance the performance of the DTC drives, the paper focuses on tuning the gains of the PI speed controller using the optimization techniques, namely the Genetic Algorithm; Ant Colony, and Bacterial Foraging Optimization. The results obtained using the tuned gain values by the above optimization techniques have been compared for speed control, reduction in torque ripples, and stator flux with respect to peak overshoot and settling time.