Generative AI and Employment Concerns Among AI Aware Respondents in Bangladesh
Generative artificial intelligence (AI) may change professional tasks, but the implications for workers depend on how technology is introduced and how people adapt. This study examines stated perceptions of task change, concern about routine work and AI-related learning in 385 adult, AI-aware questionnaire records from Bangladesh. Most respondents were recorded as law students, and the dataset does not establish that all participants were employed or young professionals. The questions do not directly measure current job security or the effects of AI exposure on employment. Individual items are therefore analysed separately using response distributions, paired endorsement comparisons and exploratory rank correlations. Of 385 respondents, 232 (60.3%) agreed that AI may reduce demand for some routine professional tasks; 307 (79.7%) agreed that learning to work effectively with AI could reduce their future job-security concerns; and 211 (54.8%) anticipated new tasks requiring human judgement and oversight. A total of 184 respondents endorsed both the routine-task concern and the potential reassurance of learning. These statements differ in meaning and do not establish whether training actually reduces insecurity. Exploratory correlations were small and should not be interpreted causally. Job demands-resources theory, psychological contract theory and career construction provide complementary lenses rather than validated models. The study distinguishes concern about tasks from concern about losing a job and identifies the need for independently verified employment status, recruitment documentation and direct measures of perceived job security in future research.
Authors
- Kazi Abdul Mannan (ORCID: https://orcid.org/0000-0002-7123-132X)
- Rafia Mahmuda Laboni (ORCID: https://orcid.org/0009-0005-9752-3370)
Publication Details
- Journal
- Preprints.org
- Published
- 2026-11-02
- DOI
- https://doi.org/10.20944/preprints202611.0010.v1
- Primary Topic
- Employment and Welfare Studies
- Type
- preprint