The delta between a consumer’s stated behavior and their actual behavior is no more obvious than in the process of seniors selecting a Medicare Advantage plan. With primary research historically serving as the single source of market preferences, Insurers have only a narrow lens into the true drivers of the market. This often leads to insufficient investment for significant benefits, exclusion of table stakes benefits, and over-investment into those which do not correlate with enrollment or member retention.

Adding to this complexity, Product Managers often struggle to accurately predict the impact on downstream metrics, specifically enrollment, as a result of benefit design changes.

Explainable AI, or xAI for short, is the new age solution to combat these deficiencies. xAI is the method by which data scientists translate complex artificial intelligence outcomes into results that can be understood and applied by practitioners. This contrasts traditional “black box” machine learning models where the results of the AI cannot be clearly understood or leveraged.411