Understanding Collaboration between Professional Designers and Decision-making AI: A Case Study in the Workplace

2025-09-29

AI Summary

This study addresses the lack of empirical research on human-AI decision-making collaboration, specifically examining how professional designers interact with decision-support AI—rather than generative AI—during the creative convergence phase of advertising design. Employing semi-structured interviews and a multiple-case study approach grounded in a human-AI collaboration analytical framework, it investigates the real-world integration of AI prediction systems in professional design workflows. The study uncovers designers’ trust-building logic toward decision-support AI, their dynamic dependency patterns, and strategies for mitigating “black-box” opacity and accountability ambiguity. Key benefits identified include enhanced decision efficiency and consistency; critical challenges encompass insufficient model interpretability and blurred role boundaries. Based on these findings, the study proposes actionable human-AI co-design principles, advancing theoretical understanding and offering practical guidance for embedding decision-support AI into creative processes.

Technology Category

• Humans and AI: Planning and Decision Support for Human-Machine Teams
• Cognitive Modeling & Cognitive Systems: Computational Creativity
• Philosophy and Ethics of AI: Safety, Robustness & Trustworthiness

Application Category

• Economics, Online Markets and Human Computation: Fairness and ethical considerations in crowd work and in human-in-the-loop AI systems
• User Modeling, Personalization and Recommendation: Accountability, Transparency, and Ethics for personalization
• Responsible Web: Machine-in-the-loop, human agency and autonomy

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.

Problem

• Understanding collaboration between designers and decision-making AI in creative workflows
• Exploring how designers perceive AI's impact on creative work practices
• Identifying trust, benefits, and challenges in human-AI creative collaboration

Innovation

• Case study explores decision-making AI in design
• AI predicts ad effectiveness for creative workflow
• Designers' trust and strategies for AI integration