Recently, the three-phase induction motor (IM) has been widely used in AC motor drives and in industrial applications. The IM suffers from the accuracy of controlling the speed when it operates at different loads; this problem attracts the attention of many researchers in this field. This paper presents an Intelligent Hybrid Control System using ANFIS (Adaptive Neuro-Fuzzy Inference System)-Optimization for Scalar Control (SC) of an Induction Motor. In order to obtain optimum performance of the motor and to decrease the Total Harmonics Distortion (THD) of the motor current a Voltage Source Inverter (VSI) based on the Pulse Width Modulation technique (PWM) is used to drive the motor. To improve the speed response, accuracy and the motor's performance, an improved hybrid control system involves an optimization control method in addition to an Adaptive Neuro-Fuzzy Inference System used to adjust the amplitude and the Modulation Index (MI) of the reference signal. The proposed hybrid system improves the transient stability of motor speed and reaches a steady state much faster than the traditional controller. The Matlab-Simulink results proved the remarkable effectiveness of the proposed controller when comparing the results with two other controllers, the usual PI controller and the optimization controller.