This paper proposes a novel beamforming design for integrated sensing, communications, and computation that incorporates integrated sensing and communication and over the-air computation (AirComp). Specifically, we formulate an optimization problem aimed at minimizing the mean squared error (MSE) of AirComp, subject to constraints that satisfy for sensing quality requirement and power budget. The problem is addressed through alternating optimization, where either the receive or transmit beamforming is fixed during each iteration. Specifically, after deriving the closed-form solution for receive beamforming, we propose an iterative algorithm to optimize transmit beamforming. Additionally, we take into account the scenario of imperfect channel state information availability in the design of the proposed beamformers. The numerical results show the convergence, MSE reduction, and improved sensing quality of the proposed algorithm.