  Generative models (foundation models) such as LLMs (large language models)
are having a large impact on multiple fields. In this work, we propose the use
of such models for business decision making. In particular, we combine
unstructured textual data sources (e.g., news data) with multiple foundation
models (namely, GPT4, transformer-based Named Entity Recognition (NER) models
and Entailment-based Zero-shot Classifiers (ZSC)) to derive IT (information
technology) artifacts in the form of a (sequence of) signed business networks.
We posit that such artifacts can inform business stakeholders about the state
of the market and their own positioning as well as provide quantitative
insights into improving their future outlook.
