Investors increasingly ask not just what a dataset covers, but whether it is built with AI, whether it plugs into their own models, and what that is worth. This intelligence piece maps how vendors across the Neudata catalogue use AI and the impact it has on price and client demand. The short answer: adoption is broad but shallow, and the value sits with a small generative-AI cohort that has raised prices and won clients while the wider market has shed them.

Background and methodology

More than 3 years after LLMs entered mainstream professional workflows in early 2023, data strategists and quant researchers are asking how the technology has reshaped the data ecosystem, specifically the supply side serving institutional investors and corporates. Which datasets have gained an edge or become easier to adopt? And which new data features now command premium pricing?

To explore these questions, in early July 2026, we used an LLM tool to read and semantically analyse the Neudata-authored product descriptions and data-processing workflow explanations for 4,339 datasets listed on our Scout and Ranger platforms (together, ‘the catalogue’) We worked from the descriptive text of our Scout reports rather than the platform’s dataset-type filters and tags, because some of the dimensions we wanted to study are not yet captured in structured fields. This report is intended as an indicative, directional read on how LLM technology is affecting investor-oriented data services. It reflects the Neudata platform only and is shaped by our coverage focus on institutional-grade data; it is not a full-market census of AI adoption.