The issue addressed in this paper refers to the improvement of methods and tools for systematic innovation in the field of marketing management. The problem of Customer Experience (CE) and Customer Understanding in the area of new technologies in marketing of Big Data, Machine Learning, and Artificial Intelligence in considered. The main objective of this paper is to reflect the actual application of TRIZ in the problem-solving process related to new categories of marketing problems. The systematic review of the literature is conducted. The database of the publications, using the search terms related to Customer Experience and TRIZ and including sources of data such as Web of Science, is formulated. The bibliometric and content analysis of the selected subsets of most relevant publications is conducted. As the results, a set of problems raised in publications in which TRIZ is used in the area of the so-called customer driven quality management was identified. In the analyzed set of publications, TRIZ is integrated with tools supporting quality management, i.e., Failure Mode and Effect Analysis (FMEA), Quality Function Deployment (OFD), SERVQUAL, Kono Model, as well as Kansei engineering (KE) or Six Sigma and Lean Management concepts. The results of the research indicate that by integrating marketing elements included in quality management, it may be possible to solve current AI-based marketing management problems using specific TRIZ methods and tools.