The voltage profile of different buses and the rotor dynamics of generators are adversely affected by a generator outage. Generator outages can be minimized using a variety of strategies and algorithms. An AI-based knowledge discovery approach has been reported in this article. This article proposes a technique for identifying sensitive loads and the amount of active and reactive power curtailment for rotor speed regulation and voltage management at the terminals. The MATLAB®/Simulink environment verifies and tests the method’s practicality on an IEEE-10-machine-39-bus system. Active power shedding is considered for rotor angle stability, while reactive power is also shedded for maintaining the terminal voltage at the loads. A sequential outage is considered to simulate a scenario where the two generators with the highest active and reactive power are taken out of service. The generator’s rotor speed, terminal voltage, and load are measured with and without load restriction. In all situations, the rotor and center of inertia speed are 1 p.u. The average steady-state load terminal voltage is 0.967 V. The average terminal voltage of all load buses improves from 0.933 to 0.972 and 0.936 to 0.971, case-wise. The reported results confirm and validate the effectiveness and applicability of the proposed technique.