City Research Online

Abstract

Purpose – This paper examines how generative AI (GenAI) systems can be assimilated into idea generation (ideation) work so that human–GenAI collaboration augments creativity. It asks which seeding configurations with GenAI improve novelty, utility and feasibility, and examines preliminary process evidence regarding human contribution to joint search.

Design/methodology/approach – Drawing on a search-based view of creativity, we conceptualise GenAI as an information system that structures individuals’ search and evaluation of information. We test four configurations with 400 professionals: human-only ideation, unstructured human–GenAI collaboration, GenAI seeding and a TC-based GenAI configuration. Expert evaluators rate novelty, utility and feasibility.

Findings – Statistically reliable improvements in novelty, utility, or feasibility were not detected for either unstructured human–GenAI collaboration or conventional GenAI seeding. The TC-based GenAI configuration, by contrast, significantly improves novelty relative to unstructured collaboration and conventional seeding. Statistically significant differences in utility were not detected relative to either GenAI comparison condition, while feasibility was lower relative to conventional seeding.

Originality/value – The study advances information systems research on AI assimilation and human–AI collaboration by showing that creative augmentation is not automatic and depends on how GenAI is configured to structure joint search. It identifies the TC-based GenAI configuration as a concrete way to enhance novelty in human–GenAI ideation.

Practical implications – Organisations should not assume that simply enabling GenAI in ideation tools will improve creative outcomes. When seeking to promote novelty, organisations may consider the full TC-based GenAI configuration tested here, combining a short TC orientation with TC-based GenAI-generated seeds.

Publication Type:	Article
Additional Information:	© 2026, Emerald Publishing Limited. This is the accepted manuscript of an article published by Emerald. Please refer to the publisher’s terms and conditions for information on re-use.
Publisher Keywords:	Artificial Intelligence (AI), Generative AI, assimilation, human–AI collaboration, ideation, creativity, seeding
Subjects:	H Social Sciences > HD Industries. Land use. Labor H Social Sciences > HM Sociology H Social Sciences > HN Social history and conditions. Social problems. Social reform Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Departments:	Bayes Business School Bayes Business School > Faculty of Management
SWORD Depositor:	Symplectic Administrator

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