ABSTRACT

As digital transformation accelerates, artificial intelligence (AI) technologies are fundamentally reshaping the world of work and the higher education ecosystem. This inevitable transformation deeply affects the future employability perceptions and career orientations of university students as prospective employees. The present study aims to examine, through a qualitative approach, university students’ perceptions of AI, their existential anxieties, and their expectations regarding current higher education. Participants were asked about their thoughts on AI, their self-assessed digital skill levels, and their AI-related expectations and criticisms of the existing education system. The subjective accounts of 64 students from diverse disciplines, who provided detailed responses to open-ended questions, were analyzed using an inductive thematic content analysis method. The findings reveal that participants simultaneously perceive AI as an evolutionary step and a professional assistant that enhances productivity, and as a profound risk factor in terms of technological unemployment, mechanization, and the displacement of human labor. The comparative analysis indicates that individuals who self-reported high digital skill levels (4–5) tend to view AI innovations as an opportunity and a tool, whereas those with low to moderate digital skills (1–3) exhibit markedly heightened concerns about technological unemployment and displacement within the framework of sociotechnical blindness. A further noteworthy finding is that students explicitly express the inadequacy of the current rote-based education system in keeping pace with the speed and dynamics of the AI era. It appears that students turn to AI tools as informal instructors to fill this structural gap. To address these structural deficiencies and update the educational ecosystem, four key strategic transformation areas are proposed: expanding practice-based curricula, enhancing the professional competence of educators, strengthening industry integration aligned with sectoral needs, and establishing transparent ethical oversight mechanisms.

Keywords: Artificial Intelligence Perception, Artificial Intelligence Anxiety, Digital Skill Level, Transformation in Higher Education, Qualitative Research.

INTRODUCTION

The increasing capacity of artificial intelligence systems in data analysis and decision-making processes brings about significant changes in global labor markets (Haenlein & Kaplan, 2019). While past industrial revolutions primarily provided alternatives to physical human labor, AI-based developments also affect cognitive processes, holding the potential to reshape the role of intellectual labor (Tuomi, 2018). For university students at the beginning of their career journeys, this transformation process opens new professional doors on one hand, while on the other, it can lead to various anxieties regarding employment contraction and technological unemployment (Mutascu, 2021; Nguyen & Vo, 2022).

Today, mismatches are occasionally observed between the theoretical framework offered by higher education institutions and the expectations of rapidly digitalizing sectors. This situation can directly affect students’ employability perceptions (Fugate et al., 2004) and their beliefs in their career goals. Education models where static knowledge is transferred through traditional methods may fall short of meeting students’ expectations in the face of AI’s data processing speed.

The main starting point of this research is to examine how prospective employees make sense of this rapidly changing technology ecosystem and whether they view this technology as a tool supporting their careers or as a threat to their professions. Since the acceptance of technology is largely related to individuals’ technical equipment, it is important to examine these perceptions according to digital skill levels. Accordingly, the main questions of the research are determined as follows:

·        What are the students’ perceptions and anxieties regarding artificial intelligence?

·        How do these perceptions and anxieties differ according to students’ self-reported digital skill levels?

·        What are their expectations and criticisms regarding the current education system in the context of artificial intelligence?

LITERATURE REVIEW

AI Anxiety and Employment Concerns

In the literature, AI anxiety is defined as the sense of uncertainty, loss of control, and professional inadequacy individuals experience during the integration of these technologies into professional and daily life (Johnson & Verdicchio, 2017). Wang and Wang (2022) addressed this anxiety in four dimensions: learning, job replacement, sociotechnical blindness, and configuration.

Current studies conducted in the context of Turkey çalışmalar (Akkaya et al., 2021; Kaya et al., 2024; Kaya, 2023; Pehlivanoğlu & Civelek, 2023) show that technology-induced unemployment concerns in areas susceptible to automation complicate the career planning of young people (Akçakanat, 2024; Uçar et al., 2024). The concept of sociotechnical blindness refers to an anxiety state arising from individuals perceiving AI as an incomprehensible and uncontrollable structure (Wang et al., 2024).

The Relationship Between Digital Competence and Technology Acceptance

 Individuals’ attitudes toward new technologies are closely related to their digital competencies and career decidedness (Yaşar & Karagucuk, 2025). Individuals with developed digital skills feel a higher self-efficacy toward working with technology and are inclined to position AI as an opportunity within the framework of human-machine collaboration (Chen et al., 2025; Li et al., 2025). It is also observed that candidates with high AI awareness have relatively higher career resilience (Kong et al., 2024; Kong et al., 2021).

On the other hand, the fear of technological displacement can be felt more prominently in some public institutions where technology adaptation may progress slower  (Wirtz et al., 2019) or among individuals with relatively low digital literacy who target areas such as the service sector (Belber & Özmen, 2024; Li, 2023).

Transformation in Higher Education and the Need for Digital Support

 The role of AI in higher education goes beyond facilitating access to information, turning into a structural paradigm shift (Bozkurt, 2023). Today, when routine assignments and research can be performed by generative AI models, it becomes important for university education to focus on fundamental skills such as critical thinking and problem-solving (Asad & Ajaz, 2024). The relevant literature indicates that education models unable to bridge the gap between theory and practice carry the risk of losing their function, and that students utilize AI tools as educational coaches to close this gap (Elçiçek, 2024).

METHOD

This research is built on a qualitative research design aiming to make sense of individuals’ beliefs about AI and their criticisms of the education system through their own ways of perceiving the world. The qualitative approach allows for the in-depth examination of complex social situations through the subjective expressions of the participants (Creswell  & Poth, 2023; Merriam & Tisdell, 2015).

Sample and Study Group

 The study group of the research was formed using the convenience sampling method. Research questions were delivered to participants via e-mail, and 64 university students who volunteered and provided detailed responses were included in the research. The fact that students come from diverse faculties such as Education, Engineering, Economics and Administrative Sciences, Islamic Sciences, and Communication reflects interdisciplinary diversity as an observed characteristic of the dataset. The group includes 33 female and 31 male participants, and the data collection process was concluded at the point of data saturation, where additional responses yielded no new codes or themes (Merriam & Tisdell, 2015).

Data Collection and Analysis

Data were collected in the form of written texts so that participants could freely express their thoughts. Participants were asked to indicate their gender and department of study, and to answer the following questions:

·        How do you evaluate your digital skill level (1. very low - 5. very high)?

·        What are your thoughts on artificial intelligence in terms of your future employment opportunities?

·        What are your thoughts, expectations, and criticisms regarding the current education system in the context of artificial intelligence?

An inductive thematic content analysis method was applied to the collected data (Braun & Clarke, 2006; Elo & Kyngäs, 2008). Data were coded by reading line by line; related codes formed categories, and categories formed main themes (Miles et al., 2014). Additionally, within the context of digital skills, participants were divided into two sub-categories: those with levels 1, 2, and 3 were grouped as “Low/Moderate Digital Skill,” and those with 4 and 5 as “High Digital Skill,” and the opinions were comparatively examined along this axis.

Validity, Reliability, and Ethics

To protect participant confidentiality in the analysis reporting, pseudonyms such as P1, P2... P64 (for Participant) were used. To ensure reliability in qualitative research, inter-coder agreement was evaluated, and the obtained themes were presented to field experts for confirmation. Accordingly, two researchers independently coded the same dataset, and the resulting agreement rate was calculated as 82%. Subsequently, the codes were compared, and units with disagreements were discussed and re-evaluated until consensus was reached (Miles et al., 2014). The research adopted a thick description approach, including direct quotes from the participants’ statements (Patton, 2014).

FINDINGS

As a result of the content analysis, it was observed that the opinions of the 64 participants were shaped around three mutually supportive main themes. The analysis framework and participant distributions are summarized in Table 1.

 Table 1. Themes, Categories, and Codes Regarding AI Perception and University Education

* A participant can be coded in more than one category. P27 is coded in both the “Opportunity Perception in High Digital Skills” category in Theme 1 and the “Criticisms of Existing Education” category in Theme 2.

Theme 1: Comparison of AI Perceptions by Digital Skill Levels

A distinct differentiation was observed between the participating students’ perspectives on AI technologies and their self-reported digital skill levels.

Category 1: Opportunity and Assistant Perception among Participants with High Digital Skills: A large portion of the participants who reported their digital skill levels as “4 and 5” (P10, P25, P38, P39, P45, P48) characterized AI as a working tool that supports professional productivity. For instance, P48, who has high digital skills, defined AI as “an assistant in professional life,” while P39 and P45 stated that the technology accelerates business processes. Some participants in this group approached the subject from a more philosophical perspective. P1 stated that AI could form the “most important foundation” for humanity, and P51 expressed that this process is a “huge step” taken without leaving it to chance in the evolution of humanity. These participants reflect a strong sense of self-efficacy that they can control the technology.

Category 2: Economic Anxiety and Threat Perception among Participants with Low/Moderate Digital Skills: A notable portion of the students who reported their digital skill levels between “1 and 3” (P4, P6, P21, P28, P41, P44, P47, P53, P56, P64) perceive this technology as an uncontrollable process that could contract employment. Expressing unemployment anxiety, P28 argued that AI would be an accelerating factor in this regard, while P21 stated their concern that it would increase the existing unemployment level. P6, aware of the deficiency in their skills and fearing that the technology would narrow their field, materialized the feeling of individual inadequacy by saying, “If I stagnate a bit more, artificial intelligence will soon destroy me too.” P58, who maintains a distant stance towards technological developments, reflected a defensive attitude against technology by stating that they completely rely on human labor.

Theme 2: Criticisms and Expectations Regarding the Education System

Participants presented various criticisms and improvement demands regarding the current state of university education, which is an important step in their career journeys.

Category 1: Criticisms of Existing Education and Digital Seeking: Some of the students (P13, P15, P24) criticize the current education system for being rote-based and disconnected from practice. While P24 stated that nothing can be achieved merely through memorization, P27 thinks that basic logical processes are not sufficiently transferred at the university. At this point, it is seen that students resort to AI tools to develop themselves. P27’s statement, “I continue to get information from artificial intelligence as if it were an educational coach, a university professor,” shows that students try to compensate for their search for academic support with technology. In addition, the fact that some educators remain distant from technology (P15) and that universities’ employment/internship connections are weak (P59) are among the problems voiced.

Category 2: Expectations from the Education System: Updating the curriculum according to the conditions of the day is demanded by many students (P9, P12, P22, P24, P25, P28, P29, P36, P45, P46, P60, P62). While P62 suggested establishing new faculties or departments in the field of AI, P60 argued that courses should be taught directly in an applied manner at the computer instead of traditional presentations. Regarding the competence of academic staff on this issue, P12 stated that frequent training should be given to personnel. P24 and P29, who believe that the bond between education and the sector should be strengthened, emphasized that the education model should be structured in accordance with the market’s need for professional personnel.

Theme 3: The Need for Social Awareness and Ethical Regulation

It was also expressed by the participants that the need for legal, social, and ethical regulations has increased as the use of AI technologies expands.

Category 1: Societal Regulation and Ethics: Some students (P8, P16, P34) think that society does not have sufficient knowledge about these new technologies. Regarding the control of generated content, P5 argued that labeling AI-generated materials must be mandatory to prevent misleading visuals. Concerning ethical boundaries in the educational process, P26 and P49 carry the concern that students’ use of these tools while preparing assignments may harm academic development and lead to unfairness.

Category 2: Individual Self-Regulation: The importance of individual responsibility in the use of technology was also emphasized. While P14 stated that uncontrolled technology cannot be beneficial, P15 and P33 expressed that they do not accept the information produced by AI directly as true, but always pass it through a verification filter. P51, on the other hand, approached the issue differently and placed the responsibility on human will rather than technology with the statement, “Before fearing losing control of artificial intelligence, we should fear not being able to control ourselves.”

DISCUSSION

One of the most striking findings of this research is the results of the comparative analysis regarding the relationship between participants’ digital skill levels and their technology acceptance and anxiety levels. The theoretical assertions in the relevant literature (Wang et al., 2024; Yaşar & Karagucuk, 2025) that the technology acceptance levels of individuals with high digital competence increase (Chen et al., 2025), have materialized in this research as the “highly skilled” participants (P39, P48, P51) view AI as a supportive assistant. This situation suggests that an individual’s technical equipment serves as a buffer against uncertainty.

However, automation risk and fear of technological unemployment (Akçakanat, 2024; Uçar et al., 2024) manifested themselves much more dominantly in the discourses of participants who evaluated their digital skills at low/moderate levels. In particular, the fear of labor displacement explicitly stated by P6, P21, and P28 in the findings can be evaluated as reflections of the sociotechnical blindness state (Wang & Wang, 2022) in individuals with low technology adaptation. This deep feeling of insecurity arising from a lack of mastery over digital tools, combined with the perception of uncertainty regarding the future of sectors (Raina, 2024) damages students’ career decidedness.

The system criticisms reflected in student opinions indicate that universities should review their educational approaches (Bozkurt, 2023). Applied studies gaining weight instead of mere theoretical knowledge transfer are frequently demanded by students (P60). The fact that students turn to technology as an educational coach shows that digital alternatives have begun to take the place of inadequate traditional academic guidance. This situation gives rise to the need for educators to stop being merely individuals who transfer information and become mentors who guide students (P12, P36) (Asad & Ajaz, 2024; Tuomi, 2018).

In light of these evaluations, it is thought that it would be beneficial for higher education institutions to focus on the four strategic transformation areas outlined below to adapt to changing dynamics and alleviate the anxieties of students with low digital skills:

·        Strengthening Practice-Based Education: Transitioning to practice-based models and designing new departments in needed areas.

·        Supporting Academic Development: Ensuring the adaptation of university professors and staff to technological developments through in-service training.

·        Enhancing Sectoral Communication: Updating the education curriculum in line with market needs and employment analyses.

·        Developing Ethical Standards: Ensuring transparency in the use of technology and providing students with digital verification skills.

CONCLUSION AND RECOMMENDATIONS

Artificial intelligence technologies are an important development that goes beyond being a technical advancement and reshapes production and education processes. These qualitative findings obtained from the statements of 64 university students show that prospective employees experience dilemmas between optimism and anxiety about the future in the face of new technologies, and this situation is directly related to the individual’s digital competence. Possessed technological skill transforms AI from a threat into a tool that supports professional development.

In light of these findings, the four strategic transformation areas detailed in the Discussion section (strengthening practice-based education, developing academic staff, enhancing sectoral communication, and establishing ethical standards) provide a concrete roadmap for restructuring the higher education ecosystem. It is evaluated that this adaptation process in education can only be possible within the framework of a comprehensive public-university-industry collaboration ecosystem to be established among the Ministry of National Education, academic institutions, and the industrial sector, rather than through the efforts of universities alone.

In conclusion, AI development should be approached not as a threat, but as a new starting point where the education system can reinvent itself and support students’ creativity. Supporting future research in this area with focus group interviews and longitudinal studies will provide valuable contributions to the knowledge base in this field.

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