A fixed‐time event‐triggered consensus control method is proposed for uncertain nonlinear multiagent systems with actuator failures. Since actuator failures, external disturbances and control gains are time‐varying and completely unknown, the effects of these system constraints on the system are completely unknown, which makes the implementation of fixed‐time tracking control challenging. To deal with these system constraints, radial basis function neural networks (RBFNNs) are applied to approximate the uncertain dynamics, and a boundary estimation method is presented to achieve adaptive compensation for them. Furthermore, considering that the implementation of this boundary estimation method requires a large number of communication resources, an event triggering mechanism is designed to reduce the update frequency of the controller. It is theoretically confirmed that using the proposed control scheme, all the followers can track the leader with sufficient accuracy in a predetermined time, and all the closed‐loop signals are bounded. Finally, the simulation experiments verify the theoretical results.