  This paper reviews and proposes concerns in adopting, fielding, and
maintaining artificial intelligence (AI) systems. While the AI community has
made rapid progress, there are challenges in certifying AI systems. Using
procedures from design and operational test and evaluation, there are
opportunities towards determining performance bounds to manage expectations of
intended use. A notional use case is presented with image data fusion to
support AI object recognition certifiability considering precision versus
distance.
