  The COVID-19 pandemic has been a major challenge to humanity, with 12.7
million confirmed cases as of July 13th, 2020 [1]. In previous work, we
described how Artificial Intelligence can be used to tackle the pandemic with
applications at the molecular, clinical, and societal scales [2]. In the
present follow-up article, we review these three research directions, and
assess the level of maturity and feasibility of the approaches used, as well as
their potential for operationalization. We also summarize some commonly
encountered risks and practical pitfalls, as well as guidelines and best
practices for formulating and deploying AI applications at different scales.
