Finally, the AI analysis also enables to plan meaningful catalyst physical characterization campaigns, since it tells which techniques are the most crucial ones. Out of the 55 parameters initially considered in our study, only 6 appear in the expressions for the yields of the value-added products olefins and oxygenates. These key parameters were derived from N2 adsorption, XPS, and NAP-XPS techniques. However, there is always a combination of key parameters involved and these parameters might be related to each other. Therefore, the synthesis of an improved catalyst based on the knowledge gained by the approach presented here is still a challenging task, which could likewise be accelerated by support of AI.