Towards AI-Supported Research: a Vision of the TIB AIssistant

• URL: http://arxiv.org/abs/2512.16447v1
• Date: Thu, 18 Dec 2025 12:08:46 GMT
• Title: Towards AI-Supported Research: a Vision of the TIB AIssistant
• Authors: Sören Auer, Allard Oelen, Mohamad Yaser Jaradeh, Mutahira Khalid, Farhana Keya, Sasi Kiran Gaddipati, Jennifer D'Souza, Lorenz Schlüter, Amirreza Alasti, Gollam Rabby, Azanzi Jiomekong, Oliver Karras,
• Abstract summary: We present the vision of the TIB AIssistant, a domain-agnostic human-machine collaborative platform designed to support researchers across disciplines in scientific discovery.<n>We describe the conceptual framework, system architecture, and implementation of an early prototype that demonstrates the feasibility and potential impact of our approach.
• Score: 6.36260975777314
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: The rapid advancements in Generative AI and Large Language Models promise to transform the way research is conducted, potentially offering unprecedented opportunities to augment scholarly workflows. However, effectively integrating AI into research remains a challenge due to varying domain requirements, limited AI literacy, the complexity of coordinating tools and agents, and the unclear accuracy of Generative AI in research. We present the vision of the TIB AIssistant, a domain-agnostic human-machine collaborative platform designed to support researchers across disciplines in scientific discovery, with AI assistants supporting tasks across the research life cycle. The platform offers modular components - including prompt and tool libraries, a shared data store, and a flexible orchestration framework - that collectively facilitate ideation, literature analysis, methodology development, data analysis, and scholarly writing. We describe the conceptual framework, system architecture, and implementation of an early prototype that demonstrates the feasibility and potential impact of our approach.

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