Structured PREreview of Automating Business Intelligence Requirements with Generative AI and Semantic Search

Does the introduction explain the objective of the research presented in the preprint?

Yes

The paper clearly sets out the problem: BI requirements gathering is manual, slow, and error-prone. The objective is to automate this using generative AI + semantic search.

Are the methods well-suited for this research?

Somewhat appropriate

They propose a pipeline combining LLM-based natural language processing with semantic search over schema metadata.

Are the conclusions supported by the data?

Somewhat supported

Conclusions (that AI + semantic search reduce BI requirement effort) are supported by experiments, but tested in controlled settings, not in full enterprise BI projects.

Are the data presentations, including visualizations, well-suited to represent the data?

Somewhat appropriate and clear

Figures are okay, but some diagrams could be clearer for non-technical BI audiences.

How clearly do the authors discuss, explain, and interpret their findings and potential next steps for the research?

Somewhat clearly

They suggest extending to larger datasets and real BI implementations. This is clear but could be deeper.

Is the preprint likely to advance academic knowledge?

Somewhat likely

Yes, this is a novel angle (generative AI for BI requirements).

Would it benefit from language editing?

Yes

Understandable but has some awkward phrasing.

Would you recommend this preprint to others?

Yes, but it needs to be improved

Worth reading but still needs refinement.

Is it ready for attention from an editor, publisher or broader audience?

Yes, after minor changes

Ready for attention after minor changes.

Competing interests

The author declares that they have no competing interests.