---
title: "Asking the database in plain language (research idea)"
description: "Text-to-SQL, table question answering and semantic parsing appear on only 12 recent papers, all in AI journals, none in business ones. Firms are rolling out assistants that turn managers' questions into database queries. How often do the queries return the wrong numbers, and would a manager notice?"
url: https://scholar4ai.com/ideas/text-to-sql-for-business-data
markdown_url: https://scholar4ai.com/ideas/text-to-sql-for-business-data.md
license: CC BY-NC 4.0 (https://creativecommons.org/licenses/by-nc/4.0/)
share_text: "Asking the database in plain language (research idea): Text-to-SQL, table question answering and semantic parsing appear on only 12 recent papers, all in AI journals, none in business ones."
date: "2026-10-26"
updated: "2026-10-26"
status: "seed"
tags: ["ai", "data", "decision-making"]
keywords: ["text-to-SQL", "semantic parsing"]
---

# Asking the database in plain language

Text-to-SQL, table question answering and semantic parsing appear on only 12 recent papers, all in AI journals, none in business ones. Firms are rolling out assistants that turn managers' questions into database queries. How often do the queries return the wrong numbers, and would a manager notice?

## What prompted this

Since October 2025, 12 papers carry a text-to-SQL, table-question-answering, semantic-parsing or natural-language-interface keyword, all in AI journals: "text-to-SQL" on 4, "table question answering" on 4, "semantic parsing" on 4. None appears in the management, accounting or operations research journals, where the users of business data publish.

## Questions

- On real company databases (many tables, ambiguous column names, business definitions such as "active customer"), how often do language models write queries that run but return the wrong answer?
- Which errors are most common: wrong joins, wrong filters, wrong definitions of a business term?
- Do managers who receive a number from an assistant check it, and does showing the query or a plain-language explanation change that?

## Data that could help

Public benchmarks (Spider, BIRD) and, more importantly, query logs and gold answers from a company data warehouse, plus user experiments.

## Next step

Build a test set of 200 business questions with gold answers on an anonymized company database and measure how often several models return a wrong but plausible number.

## Related research activity

*The keywords this note follows, in the tracked finance, accounting, economics, management, operations research and AI journals as of 2026-10-26*

| Keyword | Papers, last 30 days | Rank | Papers per month, Oct 23 – Oct 26* | Papers, last 36 months |
|---|---:|---:|---|---:|
| text-to-SQL | 0 | – | 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 2, 1, 0, 0, 0, 1, 0, 1, 1, 0, 1, 0, 0, 1, 4, 0, 0, 0, 1, 0, 1, 0, 0, 0 | 15 |
| semantic parsing | 0 | – | 0, 0, 0, 0, 0, 0, 0, 2, 0, 0, 2, 0, 0, 1, 0, 0, 1, 0, 1, 1, 0, 0, 1, 0, 0, 0, 1, 2, 0, 1, 0, 0, 0, 2, 0, 0, 0 | 15 |

## Cite this page

Scholar4AI. (2026). Asking the database in plain language. Journal Research Rankings. Retrieved October 26, 2026, from https://scholar4ai.com/ideas/text-to-sql-for-business-data

```bibtex
@misc{scholar4ai-ideas-text-to-sql-for-business-data,
  author = {{Scholar4AI}},
  title = {Asking the database in plain language},
  year = {2026},
  howpublished = {\url{https://scholar4ai.com/ideas/text-to-sql-for-business-data}},
  urldate = {2026-10-26},
  note = {Journal Research Rankings; data from OpenAlex (CC0); licensed CC BY-NC 4.0}
}
```

License: CC BY-NC 4.0 (https://creativecommons.org/licenses/by-nc/4.0/).