Investigating AI-induced Technostress and Coping Strategies of Professionals

Paper Title

Investigating AI-induced Technostress and Coping Strategies of Professionals

Publication Info

• Topic area: Understanding AI-induced technostress and coping mechanisms among professionals.
• Keywords: AI-induced technostress, coping strategies, professional workflows, human-centered AI, cognitive deskilling, job displacement anxiety, emotional support, problem-focused coping, emotion-focused coping.

Background and Problem

• Problem / challenge: The integration of AI into professional workflows introduces new forms of technostress, such as job displacement anxiety, cognitive deskilling, and the erosion of human distinctiveness. Existing research on technostress is largely confined to traditional ICT systems and does not fully address the unique challenges posed by AI.
• Significance: Understanding AI-induced technostress is critical for designing human-centered AI systems that mitigate psychological strain and support professionals in adapting to technological changes.
• Motivation and related work: Prior studies have explored traditional technostress and coping strategies in ICT contexts but have not sufficiently examined the unique stressors and coping mechanisms associated with AI. This study aims to fill this gap by investigating professionals' real-world experiences with AI-induced technostress and their coping strategies.

Solution

• Proposed approach: The study investigates AI-induced technostress and coping strategies through focus group interviews (FGIs) with professionals, analyzing stressors and responses using the Transactional Theory of Stress and Coping (TTSC).
• Novelty:
  1. Identification of seven AI-induced technostressors, including unique stressors like cognitive deskilling and the substitution of human connections.
  2. Development of a two-dimensional framework for coping strategies based on Coping Style (problem-focused vs. emotion-focused) and Value Orientation (AI-oriented vs. humanness-oriented).
  3. Practical design implications for AI tools to support both problem-focused and emotion-focused coping.
• Procedure and key techniques:
  • Conducted FGIs with 19 professionals across diverse fields.
  • Thematic analysis of transcripts to identify stressors and coping strategies.
  • Categorized coping strategies into a 2×2 matrix using TTSC and Value Orientation.

Results

• Concrete findings:
  • Identified seven AI-induced technostressors: job displacement anxiety, perpetual learning burden, loss of value of process and efforts, cognitive deskilling, substitution of human connections, black-box nature of AI, and sense of defeat.
  • Documented 10 coping strategies, classified into four categories: AI-oriented/problem-focused, AI-oriented/emotion-focused, humanness-oriented/problem-focused, and humanness-oriented/emotion-focused.
• Advantage over baselines: The study expands traditional technostress research by identifying stressors unique to AI and proposing a nuanced framework for coping strategies.
• Experiments / evaluation:
  • FGIs with 19 participants from diverse professions (e.g., data engineers, doctors, illustrators).
  • Analysis of stressors and coping strategies using TTSC and thematic coding.
• Limitations and future work:
  • Limited generalizability due to the Korean sample and focus on professionals.
  • Findings are tied to the technological context of 2024; future research should explore long-term changes in stress and coping.
  • Comparative studies across industries and cultural contexts are needed.

Summary

This study explores the psychological impacts of AI integration into professional workflows, identifying seven AI-induced technostressors and 10 coping strategies. Using a two-dimensional framework, the research highlights both problem-focused and emotion-focused coping mechanisms, emphasizing the need for AI tools to support emotional resilience alongside technical proficiency. The findings inform design implications for human-centered AI systems, such as enabling reflection on AI engagement, supporting active learning, and providing customizable AI tools. By addressing both stressors and coping strategies, the study contributes to the theoretical understanding of technostress and offers practical guidance for designing supportive AI technologies.