Artificial intelligence and corporate ideation systems

dc.contributor.authorLehmann, Selina L.
dc.contributor.authorDahlke, Johannes
dc.contributor.authorPianta, Valentina
dc.contributor.authorEbersberger, Bernd
dc.contributor.corporateLehmann, Selina L.; University of Hohenheim, Stuttgart, Germany
dc.contributor.corporateDahlke, Johannes; University of Twente, Enschede, The Netherlands
dc.contributor.corporatePianta, Valentina; University of Hohenheim, Stuttgart, Germany
dc.contributor.corporateEbersberger, Bernd; University of Hohenheim, Stuttgart, Germany
dc.date.accessioned2026-01-29T12:27:13Z
dc.date.available2026-01-29T12:27:13Z
dc.date.issued2026
dc.date.updated2026-01-23T13:55:55Z
dc.description.abstractMany 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.en
dc.identifier.urihttps://doi.org/10.1111/jpim.12782
dc.identifier.urihttps://hohpublica.uni-hohenheim.de/handle/123456789/18790
dc.language.isoeng
dc.rights.licensecc_by
dc.subjectArtificial intelligence
dc.subjectCorporate ideation
dc.subjectEmployee creativity
dc.subjectEmployee innovation
dc.subjectIdea management
dc.subject.ddc650
dc.titleArtificial intelligence and corporate ideation systemsen
dc.type.diniArticle
dcterms.bibliographicCitationJournal of product innovation management, 43 (206), 1, 160-185. https://doi.org/10.1111/jpim.12782. ISSN: 1540-5885 ISSN: 0737-6782
dcterms.bibliographicCitation.issn0737-6782
dcterms.bibliographicCitation.issn1540-5885
dcterms.bibliographicCitation.issue1
dcterms.bibliographicCitation.journaltitleJournal of product innovation managementen
dcterms.bibliographicCitation.pageend185
dcterms.bibliographicCitation.pagestart160
dcterms.bibliographicCitation.volume43
local.export.bibtex@article{Lehmann2026, doi = {10.1111/jpim.12782}, author = {Lehmann, Selina L. and Dahlke, Johannes and Pianta, Valentina et al.}, title = {Artificial intelligence and corporate ideation systems}, journal = {Journal of product innovation management}, year = {2026}, volume = {43}, number = {1}, pages = {160--185}, }
local.subject.sdg8
local.subject.sdg9
local.title.fullArtificial intelligence and corporate ideation systems
local.university.bibliographyhttps://hohcampus.verw.uni-hohenheim.de/qisserver/a/fs.res.frontend/pub/view/46332

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