Investigating AI-induced Technostress and Coping Strategies of Professionals
Heesung Kwon, Jeesun Oh, Suyoun Lee, Sunok Lee, Sangsu Lee
Abstract
While the rise of AI has benefited professionals, it also induces technostress that threatens their expertise and jobs. To ensure the human-centered advancement of technology, a deep understanding of users technostress and how to cope with it is essential. Despite technostress having long been discussed, the growing integration of AI tools into professionals' everyday work amplifies these challenges and calls for further exploration. Accordingly, this is a timely moment to examine their real-world experiences and voices. Thus, our study aims to investigate AI-induced technostress experienced by professionals, and the coping strategies they employ. Through focus group interviews with 19 professionals from diverse fields, we identified seven AI-induced technostressors and examined their coping strategies along two dimensions: stress Coping Style (problem-focused and emotion-focused) and Value Orientation (AI-oriented and humanness-oriented). Drawing on professionals' coping strategies, we suggest practical implications to support users in coping with AI-induced technostress.
• Human-centered computing → Empirical studies in HCI; User studies.
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 9afefddc-a4a1-4ee6-8b6c-fb99200b08fcBuilds on9
- The Impact of Generative AI on Critical Thinking: Self-Reported Reductions in Cognitive Effort and Confidence Effects From a Survey of Knowledge WorkersHao-Ping (Hank) Lee, Advait Sarkar, Lev Tankelevitch, Ian Drosos et al.CHI 2025 · 690 citations
- Re-examining Whether, Why, and How Human-AI Interaction Is Uniquely Difficult to DesignQian Yang, Aaron Steinfeld, Carolyn P. Rosé, John ZimmermanCHI 2020 · 604 citations
- How Knowledge Workers Think Generative AI Will (Not) Transform Their IndustriesAllison Woodruff, Renee Shelby, Patrick Gage Kelley, Steven Rousso-Schindler et al.CHI 2024 · 109 citations
- Generative AI in the Wild: Prospects, Challenges, and StrategiesYuan Sun, Eunchae Jang, Fenglong Ma, Ting WangCHI 2024 · 63 citations
- How Do Analysts Understand and Verify AI-Assisted Data Analyses?Ken Gu, Ruoxi Shang, Tim Althoff, Chenglong Wang et al.CHI 2024 · 36 citations
Related papers
- How Tech Workers Contend with Hazards of Humanlikeness in Generative AIMark Diaz, Renee Shelby, Eric Corbett, Andrew SmartCHI 2026 · 1 citation
- Emotion AI at Work: Implications for Workplace Surveillance, Emotional Labor, and Emotional PrivacyKat Roemmich, Florian Schaub, Nazanin AndalibiCHI 2023 · 123 citations
- AI Rivalry as a Craft: How Resisting and Embracing Generative AI Are Reshaping the Writing ProfessionRama Adithya Varanasi, Batia Mishan Wiesenfeld, Oded NovCHI 2025 · 16 citations
- Beyond Automation: How Designers Perceive AI as a Creative Partner in the Divergent Thinking Stages of UI/UX DesignAbidullah Khan, Atefeh Shokrizadeh, Jinghui ChengCHI 2025 · 29 citations
- "It Might be Technically Impressive, But It's Practically Useless to us": Motivations, Practices, Challenges, and Opportunities for Cross-Functional Collaboration around AI within the News IndustryQing Xiao, Xianzhe Fan, Felix Marvin Simon, Bingbing Zhang et al.CHI 2025 · 25 citations
