Understanding Collaboration between Professional Designers and Decision-making AI: A Case Study in the Workplace
Nami Ogawa, Yuki Okafuji, Yuji Hatada, Jun Baba
Abstract
The rapid development of artificial intelligence (AI) has fundamentally transformed creative work practices in the design industry. Existing studies have identified both opportunities and challenges for creative practitioners in their collaboration with generative AI and explored ways to facilitate effective human-AI co-creation. However, there is still a limited understanding of designers' collaboration with AI that supports creative processes distinct from generative AI. To address these gaps, this study focuses on understanding designers' collaboration with decision-making AI, which supports the convergence process in the creative workflow, as opposed to the divergent process supported by generative AI. Specifically, we conducted a case study at an online advertising design company to explore how professional graphic designers at the company perceive the impact of decision-making AI on their creative work practices. The case company incorporated an AI system that predicts the effectiveness of advertising design into the design workflow as a decision-making support tool. Findings from interviews with 12 designers identified how designers trust and rely on AI, its perceived benefits and challenges, and their strategies for navigating the challenges. Based on the findings, we discuss design recommendations for integrating decision-making AI into the creative design workflow.
Ask about this paper
Your agent reads all of it.
Lune indexed this paper to the last equation, along with the top-tier papers that cite it. Ask a question and the answer quotes them.
Your agent calls
Luneget_paper_fulltext
Free to start. No credit card required.
Terminal
Install the CLIlune papers fulltext 5effed74-e66b-43e4-826d-39a733edbe7eCited by top-tier papers1
Ask how each one uses itBuilds on26
- Understanding Design Collaboration Between Designers and Artificial Intelligence: A Systematic Literature ReviewYang Shi, Tian Gao, Xiaohan Jiao, Nan CaoCSCW 2023 · 170 citations
- FashionQ: An AI-Driven Creativity Support Tool for Facilitating Ideation in Fashion DesignYoungseung Jeon, Seungwan Jin, Patrick C. Shih, Kyungsik HanCHI 2021 · 143 citations
- Human-AI Collaboration via Conditional Delegation: A Case Study of Content ModerationVivian Lai, Samuel Carton, Rajat Bhatnagar, Q. Vera Liao et al.CHI 2022 · 135 citations
- Human-LLM Collaborative Annotation Through Effective Verification of LLM LabelsXinru Wang, Hannah Kim, Sajjadur Rahman, Kushan Mitra et al.CHI 2024 · 127 citations
- Machine Learning Uncertainty as a Design Material: A Post-Phenomenological InquiryJesse Josua Benjamin, Arne Berger, Nick Merrill, James PierceCHI 2021 · 125 citations
Related papers
- Decoupling of Usefulness and Novelty: Evaluating the Impact of Generative AI on Design Outputs and Novice Designers' Creative ThinkingYue Fu, Tony Zhou, Bin Han, Marx Wang et al.CHI 2026 · 2 citations
- When Teams Embrace AI: Human Collaboration Strategies in Generative Prompting in a Creative Design TaskYuanning Han, Ziyi Qiu, Jiale Cheng, Ray LCCHI 2024 · 103 citations
- DesignManager: An Agent-Powered Copilot for Designers to Integrate AI Design Tools into Creative WorkflowsWeitao You, Yinyu Lu, Zirui Ma, Nan Li et al.SIGGRAPH 2025 · 9 citations
- Exploring the Impact of AI-powered Creativity Support Tools on Professional Creative WorkflowsCaterina Moruzzi, Charlotte Bird, Laura Mariah HermanCSCW 2026
- AIDED: Augmenting Interior Design with Human Experience Data for Designer-AI Co-DesignYang Chen Lin, Chen-Ying Chien, Kai-Hsin Hou, Hung-Yu Chen et al.CHI 2026 · 2 citations
