Too Much, Too Fast: Understanding Ai Fatigue In The Digital Acceleration Era

As artificial intelligence (AI) becomes deeply embedded in work, education, and everyday decision-making, a growing psychosocial challenge has emerged: AI fatigue. This paper conceptualises AI fatigue as a multidimensional condition arising from the interplay of technostress, cognitive overload, and emotional exhaustion, driven not only by constant AI use but also by the relentless pace, opacity, and unevenness of AI integration. Drawing on Technostress Theory and Cognitive Load Theory, the study differentiates AI fatigue from broader digital burnout while highlighting their intersections in cognitive, emotional, and organisational domains. Using a narrative literature review with thematic synthesis, the paper identifies key drivers of AI fatigue, including poor design, ethical opacity, organisational misalignment, and structural inequality. It argues that AI fatigue is not merely an individual adaptation issue but a systemic outcome of current digital transformation practices. To address this emerging condition, the paper outlines strategies for human-centred AI design, policy safeguards, and organisational wellbeing interventions, advocating a shift from productivity-first to psychological sustainability-first approaches. The study concludes by calling for empirical, longitudinal, and cross-sector research to better understand and mitigate AI fatigue as a structural feature of life in the algorithmic era.

Authors

Publication Details

Journal
International Journal of Arts Humanities & Social Science
Published
2025-08-16
DOI
https://doi.org/10.56734/ijahss.v6n8a7
Citations
1
Primary Topic
CCD and CMOS Imaging Sensors
Type
article
Field-Weighted Citation Impact
0.73
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Too Much, Too Fast: Understanding Ai Fatigue In The Digital Acceleration Era

Mahlatse Ragolane, Shahiem Patel
1 citations
International Journal of Arts Humanities & Social Science
CCD and CMOS Imaging Sensors
0.73
article

Too Much, Too Fast: Understanding Ai Fatigue In The Digital Acceleration Era

Mahlatse Ragolane, Shahiem Patel
article en
1 citations

Abstract

As artificial intelligence (AI) becomes deeply embedded in work, education, and everyday decision-making, a growing psychosocial challenge has emerged: AI fatigue. This paper conceptualises AI fatigue as a multidimensional condition arising from the interplay of technostress, cognitive overload, and emotional exhaustion, driven not only by constant AI use but also by the relentless pace, opacity, and unevenness of AI integration. Drawing on Technostress Theory and Cognitive Load Theory, the study differentiates AI fatigue from broader digital burnout while highlighting their intersections in cognitive, emotional, and organisational domains. Using a narrative literature review with thematic synthesis, the paper identifies key drivers of AI fatigue, including poor design, ethical opacity, organisational misalignment, and structural inequality. It argues that AI fatigue is not merely an individual adaptation issue but a systemic outcome of current digital transformation practices. To address this emerging condition, the paper outlines strategies for human-centred AI design, policy safeguards, and organisational wellbeing interventions, advocating a shift from productivity-first to psychological sustainability-first approaches. The study concludes by calling for empirical, longitudinal, and cross-sector research to better understand and mitigate AI fatigue as a structural feature of life in the algorithmic era.

International Journal of Arts Humanities & Social ScienceVol. 06(08)
Openalex Percentile: Top 24%
CCD and CMOS Imaging Sensors
0.73
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Too Much, Too Fast: Understanding Ai Fatigue In The Digital Acceleration Era — Mahlatse Ragolane, Shahiem Patel · International Journal of Arts Humanities & Social Science (2025) | TGRS Research Map | TGRS