Artificial intelligence and corporate ideation systems
(2026) In Journal of Product Innovation Management 43(1). p.160-185- Abstract
Many companies leverage the creativity of their employees to gather ideas for innovations. These ideas are collected, saved, and evaluated via platforms known as corporate ideation systems. Moderated ideation systems (ideation 2.0) emerged as a solution to address the limitations of traditional, rather passive ideation systems (ideation 1.0). In this study, we apply a qualitative mixed-method approach (literature review, company case studies, expert interviews, and focus group workshops) to examine how artificial intelligence (AI) technology may relieve the remaining pains of stakeholders in collaborative, moderated ideation systems. This leads to a new framework of corporate ideation systems, termed AI-based ideation systems (ideation... (More)
Many companies leverage the creativity of their employees to gather ideas for innovations. These ideas are collected, saved, and evaluated via platforms known as corporate ideation systems. Moderated ideation systems (ideation 2.0) emerged as a solution to address the limitations of traditional, rather passive ideation systems (ideation 1.0). In this study, we apply a qualitative mixed-method approach (literature review, company case studies, expert interviews, and focus group workshops) to examine how artificial intelligence (AI) technology may relieve the remaining pains of stakeholders in collaborative, moderated ideation systems. This leads to a new framework of corporate ideation systems, termed AI-based ideation systems (ideation 3.0). We identify five major pains suffered by stakeholders in today's moderated ideation systems: creativity pain, content formulation pain, search pain, analytical pain, and administration pain. We find that AI agents act as pain relievers when serving five supporting functions: inspirer, stylist, matchmaker, analyst, and organizer. The interconnected nature of pains means that employing AI agents in certain functions within corporate ideation systems can create positive externalities across the entire system. Practical insights into AI agent implementation and application in corporate ideation systems are provided by six mini-case studies, which lead to the proposition of two organizational principles: the contextualization of AI usage and the generalization of AI implementation as the requirements for successful ideation 3.0.
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- author
- Lehmann, Selina L. ; Dahlke, Johannes ; Pianta, Valentina and Ebersberger, Bernd LU
- organization
- publishing date
- 2026-01
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- artificial intelligence, corporate ideation, employee creativity, employee innovation, idea management
- in
- Journal of Product Innovation Management
- volume
- 43
- issue
- 1
- pages
- 26 pages
- publisher
- Wiley-Blackwell
- external identifiers
-
- scopus:105000268271
- ISSN
- 0737-6782
- DOI
- 10.1111/jpim.12782
- language
- English
- LU publication?
- yes
- id
- 2727b000-f640-42f8-8d67-d501afa998e5
- date added to LUP
- 2025-12-19 13:31:30
- date last changed
- 2025-12-19 13:32:11
@article{2727b000-f640-42f8-8d67-d501afa998e5,
abstract = {{<p>Many companies leverage the creativity of their employees to gather ideas for innovations. These ideas are collected, saved, and evaluated via platforms known as corporate ideation systems. Moderated ideation systems (ideation 2.0) emerged as a solution to address the limitations of traditional, rather passive ideation systems (ideation 1.0). In this study, we apply a qualitative mixed-method approach (literature review, company case studies, expert interviews, and focus group workshops) to examine how artificial intelligence (AI) technology may relieve the remaining pains of stakeholders in collaborative, moderated ideation systems. This leads to a new framework of corporate ideation systems, termed AI-based ideation systems (ideation 3.0). We identify five major pains suffered by stakeholders in today's moderated ideation systems: creativity pain, content formulation pain, search pain, analytical pain, and administration pain. We find that AI agents act as pain relievers when serving five supporting functions: inspirer, stylist, matchmaker, analyst, and organizer. The interconnected nature of pains means that employing AI agents in certain functions within corporate ideation systems can create positive externalities across the entire system. Practical insights into AI agent implementation and application in corporate ideation systems are provided by six mini-case studies, which lead to the proposition of two organizational principles: the contextualization of AI usage and the generalization of AI implementation as the requirements for successful ideation 3.0.</p>}},
author = {{Lehmann, Selina L. and Dahlke, Johannes and Pianta, Valentina and Ebersberger, Bernd}},
issn = {{0737-6782}},
keywords = {{artificial intelligence; corporate ideation; employee creativity; employee innovation; idea management}},
language = {{eng}},
number = {{1}},
pages = {{160--185}},
publisher = {{Wiley-Blackwell}},
series = {{Journal of Product Innovation Management}},
title = {{Artificial intelligence and corporate ideation systems}},
url = {{http://dx.doi.org/10.1111/jpim.12782}},
doi = {{10.1111/jpim.12782}},
volume = {{43}},
year = {{2026}},
}