Best use cases for Artificial Intelligence (AI) applications often involve one of the following two key elements: complexity and volume. But what is complex data? Data consisting of handwritten text is a good example. Heterogenous data from different systems can also be more complex to aggregate and thus leverage such as a longitudinal study from subjects enrolled in a clinical trial for a new class of vaccine. Highly multiplex data at the gene, protein, and cell levels for multiple subjects can be collected. Each data type by itself is substantially complex; imagine trying to combine all that data together, especially since the data do not have equal impact! AI can substantially accelerate the pace and the comprehensiveness of the data processing and analysis, making it a great tool for biomarker discovery.