Reduced costs in maximization indicate how much the objective function will decrease if a decision variable is increased from zero. If the reduced cost is positive, it means that increasing that variable will not improve the objective, while a negative reduced cost suggests that increasing the variable can enhance the objective function. This helps identify which variables could potentially improve the solution if they are allowed to take on non-zero values.