Researchers led by Nishat Tabassum of Pabna University of Science and Technology, working with colleagues from Comilla University, surveyed students at three major public institutions: the University of Dhaka, Rajshahi University, and Pabna University of Science and Technology. Using stratified random sampling, they collected responses from 150 students at each university, drawn evenly from engineering, science, social sciences, arts, and humanities faculties. The respondents, 52.2 percent male and 47.8 percent female and mostly between 18 and 25 years old, answered a structured questionnaire administered through a web survey, with the resulting data analyzed using IBM SPSS Statistics 20 and Excel.

The intellectual scaffolding of the study rests on three theories. Technological determinism, rooted in the work of sociologist Thorstein Veblen, holds that technological innovation drives social change and reshapes institutions, often faster than those institutions can adapt. Skill mismatch theory describes the gap that emerges when workers’ competencies diverge from labor market demands, whether through horizontal mismatch between education and job requirements, vertical mismatch of overqualification, or skills obsolescence caused by rapid technological turnover. Labor market theory, meanwhile, frames how shifts in the supply and demand for particular skills translate into changes in wages and employment levels. Together, the researchers argue, these frameworks explain why students expect AI to transform their careers and why they fear the education system is not keeping pace.

The headline finding is cautiously optimistic: across all three universities, a majority of students believe AI will generate more employment opportunities than it eliminates in their fields. Rajshahi University students expressed the greatest optimism, with 55.3 percent agreeing that AI will expand job opportunities, followed by PUST at 52.7 percent and Dhaka University at 43.3 percent. This pattern echoes a growing international literature suggesting that AI’s effect on employment is better characterized as job shifting than mass job loss, as automation displaces routine tasks while creating new occupations that demand advanced cognitive, digital, and socio-emotional capabilities.

Beneath that optimism, however, lies a deep vein of anxiety and institutional criticism. More than half of the students at every university surveyed agreed that AI-driven change would produce a skills mismatch, with agreement peaking at 62 percent at Rajshahi University. Even more telling, 70.7 percent of all respondents believed a gap exists between the skills they are currently learning and the skills required for AI-related jobs. And when asked whether their institutions were actively updating curricula to include AI-relevant skills, 62.7 percent disagreed overall, with dissatisfaction reaching 70 percent at Dhaka University and 69.3 percent at PUST. Only at Rajshahi University did a comparatively larger share, 37.3 percent, believe their curriculum was being meaningfully refreshed.

The study also documented institutional variation in how much AI education students are actually receiving. Rajshahi University reported the best integration, with 48.7 percent of students saying they receive adequate AI education in their programs, against 38.6 percent who disagreed. At Dhaka University the picture was more divided, with 48.6 percent disagreeing that their AI education was sufficient, and at PUST a majority, 50.6 percent, said their programs were not preparing them adequately. Correspondingly, only 12.7 percent of Dhaka students and 14.7 percent of PUST students rated the availability of AI-related courses and training at their institutions positively, compared with 24 percent at Rajshahi University. The researchers note that AI course integration appears greatest in engineering faculties and weakest in the sciences across all three institutions.

Gender and geography shaped perceptions in subtle ways. Female students at Dhaka University and PUST reported higher familiarity with AI than their male peers, at 75.6 percent and 88.4 percent agreement respectively on the relevance of AI to their fields, while at Rajshahi University males reported greater familiarity and a sizable share of female respondents, 19.4 percent, remained neutral, a pattern the authors suggest may reflect unequal access to AI-focused learning opportunities. Regional dynamics were equally revealing: Dhaka University students, situated in the capital with greater industry exposure, were the least fearful of job loss, with 56.7 percent disagreeing that AI would cause significant job losses, while roughly half of PUST and Rajshahi students expressed such fears, a disparity the researchers attribute to uneven access to technological infrastructure and employment networks outside Dhaka.

Where students agreed almost unanimously was on the enduring value of human skills. Majorities at all three institutions, ranging from 66.7 percent at Rajshahi to 73.3 percent at PUST, said jobs requiring creativity and emotional intelligence are less likely to be automated. Even more striking, between 73.3 and 84 percent of students at the three universities said AI knowledge is key to future career success. Yet this awareness did not translate into confidence: 52.7 percent of Dhaka University students took a neutral stance on their own ability to adapt to AI-driven change, compared with far lower neutrality and higher confidence at PUST, where 50.7 percent agreed they could adapt, and Rajshahi, where 55.3 percent did so.

The demand signal from students could hardly be clearer. Around 81 percent of PUST students and 82 percent of Rajshahi students, along with 72 percent of Dhaka students, called for more practical AI training in their curricula, and similar majorities wanted more hands-on AI experience and stronger collaboration between universities and industry. Confidence in government action was notably weaker: a net negative assessment of policy effectiveness emerged, with 44 percent of respondents disagreeing that government initiatives were addressing AI-era skills mismatches, against just 30 percent agreeing. This skepticism persists despite Bangladesh’s National Strategy for Artificial Intelligence, launched in 2020, and a National AI Policy adopted in 2024, suggesting a perceived gap between policy formulation and implementation on the ground.

The authors conclude that without deliberate intervention, the promise of AI-driven development in Bangladesh may remain unrealized. They recommend embedding foundation AI courses across all faculties, not just engineering; organizing workshops, seminars, and guest lectures with AI professionals to expose students to real-world applications; aligning university curricula with national AI policies; investing in faculty training and the infrastructure needed for AI teaching and research; and fostering continuous learning habits among students so their skills remain relevant throughout their careers. For a country where nearly 34 percent of young people are considered tech-savvy and the youth population is expanding rapidly, the stakes are considerable. The study suggests that Bangladesh’s students have already made up their minds about AI: they see it as an opportunity, but one their universities have not yet equipped them to seize.

Subject of Research: University students' perceptions of artificial intelligence's impact on job prospects and skill mismatch in Bangladesh

Article Title: Understanding university students’ perspective on artificial intelligence and its influence on job prospects and skills in Bangladesh

Article References: Tabassum, N., Ferdous, J., Hossain, M. S., & Haque, T. (2026). Understanding university students’ perspective on artificial intelligence and its influence on job prospects and skills in Bangladesh. Discover Global Society, 4(1), Article 237. https://doi.org/10.1007/s44282-026-00413-7

Image Credits: AI Generated

DOI: 10.1007/s44282-026-00413-7

Keywords: artificial intelligence, Bangladesh, university students, job prospects, skill mismatch, higher education, curriculum reform, labor market, AI literacy, employment, public universities, workforce readiness