The Final Correcting Element (FCE) in a process control loop is either a control valve or variable speed drive (VSD) varying the speed of a motor driving a pump. The FCE regulates the amount of fluid in the process loop to maintain the set point of the controller. The more common FCE is the control valve which the chapter discusses briefly. They are part of almost every control loop in industries that includes, but not limited to, manufacturing, military, paper, food, electricity generation, and water management. This is achieved through the output of the controller adjusting the position of the control valve. Conventional control systems rely on manual settings and the control parameters within the controller, on a basic Single Input Single Output (SISO) controller. At the next, intermediate level of control, concepts like cascade, split range, and ratio control strategies are adopted. However, the integration of Artificial Intelligence (AI) and Machine Learning (ML) offers significant advances in the performance, reliability, and efficiency of control valves. Initially, simple valves were manually operated mechanical devices that required the human element factor to regulate the process flow. Thereafter, control valves were introduced, to merely regulate the flow of the process medium, automatically. Later, valve positioners and converters were introduced to optimise the response time of the valve, be able to invert the action of the valve and incorporate integrated control strategies. This was possible with the advent of digital control, reducing human intervention, with limitations such as fixed control algorithms and reactive maintenance strategies. AI and ML introduce a transformative approach to control valves, thereby facilitating the evolution of control valves from reactive to predictive and adaptive systems. The chapter firstly discusses the control valve, and its role in the control loop, thereafter, discusses the main aspects related to AI and ML in control valve systems, discussing historical developments, current advancements, practical applications, challenges, and prospects (Krishna Reddy, J Crit Rev 8:534, 2021).