Economic testimony occupies a unique intersection of
economics, law, and empirical rigor. The work of expert
witnesses, especially in high-stakes commercial litigation,
demands a careful blend of analytic precision, domain
knowledge, and persuasive communication. Traditionally, this
effort has depended on teams of analysts, associates, and
support staff, with the expert serving as both architect and
final author of the damages model or valuation opinion.
The rapid emergence of generative artificial intelligence
(AI), particularly large language models (LLMs), presents a
profound disruption to this paradigm. While not themselves
experts, LLMs can perform a growing array of linguistic,
mathematical, and logical tasks. This has led to their
adoption as “junior associates” in a variety of legal and
financial settings. In the realm of expert testimony, these
tools offer real opportunities for increased efficiency but
also present risks of overreliance, lack of methodological
transparency, and confusion about how evidence or
knowledge is interpreted and validated.