AI Tools

When people talk about “AI tools” today, they are usually referring to generative language models. However, artificial intelligence encompasses much more, such as image recognition, forecasting systems, and recommendation systems. Generative AI is the umbrella term for systems that generate new content such as text, images, music, or videos; large language models (LLMs) are a subset of this that specializes in language.

There are now countless generative language models for research, teaching, and administration—but which one is best suited for what? This page features carefully selected overviews from other universities and institutions that organize and categorize these tools by activity.

Many tools raise privacy concerns: Therefore, personal or confidential data should not be entered, and results should always be critically evaluated.

Through KI:Connect, HHU provides all employees and students with access to various large language models (LLMs). You can find more in the following collection:

Duisburg-Essen University Library – AI Tools for Literature Research and Academic Writing
A comprehensive, regularly updated collection from the University Library: research and writing tools, each described in terms of its intended use, target audience, subject areas, data sources, and costs, supplemented by in-depth information on the limitations of AI, data protection, source verification, and citation.

Tübingen University Library – Literature Research with AI
This page explains which subjects and search queries the tools are already suitable for—or are not yet suitable for—and includes a summary table of many other AI tools for academic work. It distinguishes between two types of tools: “Finders” (search by keyword or question) and “Connectors” (search based on a publication that has already been found). The comparative PDF overview is licensed under CC BY 4.0 and is current as of May 2026. Particularly useful for the humanities and social sciences.

UB Bielefeld – Literature Research with AI Tools
Organizes the tools by research phase. It points out that the data sources are often opaque, that most tools are primarily suited for the natural sciences and English-language research, and that connector tools are particularly well-suited for the humanities.

VK:KIWA – Virtual Competence Center for AI and Academic Work
An inter-university initiative of experts based at Kiel University of Applied Sciences. The list is organized by activity. The categories are: literature search, text comprehension, text production, text editing/correction, feedback tools, text classification, and cross-functional assistance systems. It thus aligns very well with your idea of “tools for specific tasks.” However, it is more of a list of links without detailed evaluations. Regarding AI detectors, it explicitly warns of high error rates.

Ithaka S+R – Generative AI Product Tracker
An internationally renowned, English-language tracker of AI products for universities. The University Library of Tübingen recommends it in its overviews of AI tools for academic purposes.