The integrated autodriller controller (IADC) is a software product by National Oilwell Varco (NOV) developed to allow an operator to drill with a constant weight on bit (WOB). The control loop has a proportional-integral (PI) controller, and PI gains are dependent on drill string compliance and response time (RT). The compliance is calculated based on the drill string length, but RT is difficult to predict. The existing IADC uses an empirical regression model to estimate RT based on the string length, which is not optimal during a formation change. This work presents an adaptive response time (ART), a machine learning model to predict RT based on the rate of penetration (ROP). ART can adapt to formation changes and gives smoother regulation of block velocity and WOB. Simulation results show a better torque and speed regulation of drill string using ART.