  AI is widely thought to be poised to transform business, yet current
perceptions of the scope of this transformation may be myopic. Recent progress
in natural language processing involving transformer language models (TLMs)
offers a potential avenue for AI-driven business and societal transformation
that is beyond the scope of what most currently foresee. We review this recent
progress as well as recent literature utilizing text mining in top IS journals
to develop an outline for how future IS research can benefit from these new
techniques. Our review of existing IS literature reveals that suboptimal text
mining techniques are prevalent and that the more advanced TLMs could be
applied to enhance and increase IS research involving text data, and to enable
new IS research topics, thus creating more value for the research community.
This is possible because these techniques make it easier to develop very
powerful custom systems and their performance is superior to existing methods
for a wide range of tasks and applications. Further, multilingual language
models make possible higher quality text analytics for research in multiple
languages. We also identify new avenues for IS research, like language user
interfaces, that may offer even greater potential for future IS research.
