Activation functions are essential in artificial neural networks to optimize outputs based on calculated net inputs. Key functions include identity, binary step, bipolar step, sigmoid functions (binary and bipolar), and ramp functions. Each function serves specific purposes, influencing how networks process and transform input data for accurate results.