Finding from scratch a new molecule with sought properties remains a challenge. In this chapter, we propose a presentation of the research challenges of molecular generation using methods from the artificial intelligence domain. This objective can be separated into three fundamental subproblems. The first problem is the representation of molecules. There is no universal molecular representation. It is, therefore, necessary to choose a representation adapted to the objective to be addressed. The second problem consists in guiding and evaluating generative methods. The role of the objective function is to orient the generation procedure toward solutions that address the problem. It is also possible to define assessment functions, whose purpose is to evaluate a set of solutions proposed by a method, beyond the criterion formulated by the objective function. The third problem consists in designing molecular generation methods. Many methods have been proposed in the last 30 years. We choose to present the methods according to the way they generate solutions and explore the molecular space. We highlight in this chapter the crucial role and interlocking nature of those three subproblems.