Leveraging LLMs for Design Ideation: An AI Tool to Assist Creativity

Fuente: arXiv
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Main Authors: Kokate, Rutvik, Kompella, Pranati, Onkar, Prasad
Format: Preprint
Published: 2025
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author Kokate, Rutvik
Kompella, Pranati
Onkar, Prasad
author_facet Kokate, Rutvik
Kompella, Pranati
Onkar, Prasad
contents The creative potential of computers has intrigued researchers for decades. Since the emergence of Generative AI (Gen AI), computer creativity has found many new dimensions and applications. As Gen AI permeates mainstream discourse and usage, researchers are delving into how it can improve and complement what humans do. Creative potential is a highly relevant notion to design practice and research, especially in the initial stages of ideation and conceptualisation. There is scope to improve creative potential in these stages, especially using machine intelligence. We propose a structured ideation session involving inspirational stimuli and utilise Gen AI in delivering this structure to designers through ALIA: Analogical LLM Ideation Agent, a tool for small-group ideation scenarios. The tool is developed by enabling speech based interactions with a Large Language Model (LLM) for inference generation. Inspiration is drawn from the synectic ideation method and the dialectics philosophy to design the optimal stimuli in group ideation. The tool is tested in design ideation sessions to compare the output of the AI-assisted ideation sessions to that of tradi tional ideation sessions. Preliminary findings showcase that participants have rated their ideas better when assisted by ALIA and respond favourably to speech-based interactions.
format Preprint
id arxiv_https___arxiv_org_abs_2512_00010
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Leveraging LLMs for Design Ideation: An AI Tool to Assist Creativity
Kokate, Rutvik
Kompella, Pranati
Onkar, Prasad
Human-Computer Interaction
Artificial Intelligence
The creative potential of computers has intrigued researchers for decades. Since the emergence of Generative AI (Gen AI), computer creativity has found many new dimensions and applications. As Gen AI permeates mainstream discourse and usage, researchers are delving into how it can improve and complement what humans do. Creative potential is a highly relevant notion to design practice and research, especially in the initial stages of ideation and conceptualisation. There is scope to improve creative potential in these stages, especially using machine intelligence. We propose a structured ideation session involving inspirational stimuli and utilise Gen AI in delivering this structure to designers through ALIA: Analogical LLM Ideation Agent, a tool for small-group ideation scenarios. The tool is developed by enabling speech based interactions with a Large Language Model (LLM) for inference generation. Inspiration is drawn from the synectic ideation method and the dialectics philosophy to design the optimal stimuli in group ideation. The tool is tested in design ideation sessions to compare the output of the AI-assisted ideation sessions to that of tradi tional ideation sessions. Preliminary findings showcase that participants have rated their ideas better when assisted by ALIA and respond favourably to speech-based interactions.
title Leveraging LLMs for Design Ideation: An AI Tool to Assist Creativity
topic Human-Computer Interaction
Artificial Intelligence
url https://arxiv.org/abs/2512.00010