Exploring the Impact of AI-generated Image Tools on Professional and Non-professional Users in the Art and Design Fields
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Abstract (arXiv)
The rapid proliferation of AI-generated image tools is transforming the art and design fields, challenging traditional notions of creativity and impacting both professional and non-professional users. For the purposes of this paper, we define 'professional users' as individuals who self-identified in our survey as 'artists,' 'designers,' 'filmmakers,' or 'art and design students,' and 'non-professional users' as individuals who self-identified as 'others.' This study explores how AI-generated image tools influence these different user groups. Through an online survey (N=380) comprising 173 professional users and 207 non-professional users, we examine differences in the utilization of AI tools, user satisfaction and challenges, applications in creative processes, perceptions and impacts, and acceptance levels. Our findings indicate persistent concerns about image quality, cost, and copyright issues. Additionally, the usage patterns of non-professional users suggest that AI tools have the potential to democratize creative processes, making art and design tasks more accessible to individuals without traditional expertise. This study provides insights into the needs of different user groups and offers recommendations for developing more user-centered AI tools, contributing to the broader discussion on the future of AI in the art and design fields.
Key facts. Cited by 10 papers in the map (data through 14 Oct 2026). First posted on arXiv 15 Jun 2024.
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Citing papers per year: 2024: 1; 2025: 7; 2026: 2.
10 papers.
- 2025Co-Writing with AI, on Human Terms: Aligning Research with User Demands Across the Writing Processcited by 14
- 2025On the Limitations of Vision-Language Models in Understanding Image Transformscited by 13
- 2025SAGI: Semantically Aligned and Uncertainty Guided AI Image Inpaintingcited by 10
- 2025Expertise elevates AI usage: experimental evidence comparing laypeople and professional artistscited by 4
- 2026"Unlimited Realm of Exploration and Experimentation": Methods and Motivations of AI-Generated Sexual Content Creatorscited by 3
- 2025A Picture is Worth a Thousand Prompts? Efficacy of Iterative Human-Driven Prompt Refinement in Image Regeneration Taskscited by 2
- 2025TechImage-Bench: Rubric-Based Evaluation for Technical Image Generationcited by 2
- 2026Position: Natural Language Should Not Fully Replace Formal Languagescited by 1
- 2024MANTA -- Model Adapter Native generations that's Affordablecited by 0
- 2025Future of AI Models: A Computational perspective on Model collapsecited by 0
- 2026Position: Natural Language Should Not Fully Replace Formal Languages10 May 2026
- 2026"Unlimited Realm of Exploration and Experimentation": Methods and Motivations of AI-Generated Sexual Content Creators28 Jan 2026
- 2025TechImage-Bench: Rubric-Based Evaluation for Technical Image Generation13 Dec 2025
- 2025Future of AI Models: A Computational perspective on Model collapse29 Oct 2025
- 2025A Picture is Worth a Thousand Prompts? Efficacy of Iterative Human-Driven Prompt Refinement in Image Regeneration Tasks29 Apr 2025
- 2025Co-Writing with AI, on Human Terms: Aligning Research with User Demands Across the Writing Process16 Apr 2025
- 2025On the Limitations of Vision-Language Models in Understanding Image Transforms12 Mar 2025
- 2025SAGI: Semantically Aligned and Uncertainty Guided AI Image Inpainting10 Feb 2025
- 2025Expertise elevates AI usage: experimental evidence comparing laypeople and professional artists21 Jan 2025
- 2024MANTA -- Model Adapter Native generations that's Affordable22 Sep 2024