Ternar, Dan-Alexandru, Denisova, ALENA orcid.org/0000-0002-1497-5808, Cunha, João Miguel et al. (2 more authors) (2026) Generative AI in Game Development:A Qualitative Research Synthesis. In: 2026 CHI Conference on Human Factors in Computing Systems:Proceedings. 2026 CHI Conference on Human Factors in Computing Systems, 13-17 Apr 2026 Human factors in computing systems. ACM, ESP. (In Press)
Abstract
Generative Artificial Intelligence (GenAI) is currently reshaping game development practices, production pipelines, and value networks in an unprecedentedly pervasive manner with cascading consequences remaining unclear. In the last five years since GenAI’s inception, a growing body of qualitative research has explored these early transformations from different settings and demographic angles. However, these studies often contextualise and consolidate their findings weakly with related work; for research to keep up with and support stakeholders in this development, the current moment calls for a synthesis of the findings emerged thus far. Here, we address this need through a qualitative research synthesis via meta-ethnography. We followed PRISMA-S to systematically search the relevant literature from 2020-2025, including major HCI and games research databases. We then synthesised the ten eligible studies, conducting reciprocal translation and line-of-argument synthesis guided by eMERGe, informed by CASP quality appraisal. We identified nine overarching themes, provide recommendations, and contextualise our insights in wider game production trajectories. With this work, we seek to provide practitioners, researchers and policy-makers with grounded insights to guide practice, research and governance.
Metadata
| Item Type: | Proceedings Paper |
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| Authors/Creators: |
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| Copyright, Publisher and Additional Information: | © 2026 Copyright held by the owner/author(s). |
| Dates: |
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| Institution: | The University of York |
| Academic Units: | The University of York > Faculty of Sciences (York) > Computer Science (York) |
| Date Deposited: | 19 Mar 2026 00:07 |
| Last Modified: | 19 Mar 2026 00:07 |
| Published Version: | https://doi.org/10.1145/3772318.3791206 |
| Status: | In Press |
| Publisher: | ACM |
| Series Name: | Human factors in computing systems |
| Identification Number: | 10.1145/3772318.3791206 |
| Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:239293 |

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