Introduction

It is unbelievable that 80 years ago no one even had heard of artificial intelligence (AI) [1], while now, it is hard to imagine life without it. In such a short time, AI has gone from being a futuristic idea to something that has completely transformed our way of living. At its core, AI is about creating technology that can think and learn like humans, using smart algorithms and powerful computers [2]. Today, AI can be seen everywhere; it powers self-driving cars, translates languages in real time, and even keeps our homes running smoothly by controlling smart devices, such as thermostats and lights [3-5]. It has become so seamlessly integrated that we barely think about it; it is just there, making things easier and more connected.

We are living in the age of AI, and it is not just about convenience, it is about innovation. Even fields, such as dentistry, are being transformed by AI. From analyzing dental images and detecting issues that might be missed by the human eye to designing perfectly fitted braces or crowns, AI is changing the way dental care is provided [6-8]. It is exciting to think where this technology might be taking us next because, at this point, it feels like the possibilities are endless [9-11].

For dental students entering this rapidly evolving field, it is crucial to understand how AI can enhance cli­nical outcomes and streamline their workflow. The way they approach and adapt to this technology while still learning will have a big impact on how rapidly AI becomes a regular part of dental care. This underscores the need for dental schools to empower students, building both their confidence and competence in leveraging AI technologies [12].

Given the rapid advancement of AI, capturing the perspective of dental students is critical, as they represent the profession’s future. How do they feel about AI shaping their careers? Are they excited or concerned about AI taking over certain tasks, or not being accurate enough? Their perspectives are important because they are the next generation of dentists that will implicate AI into clinical practice.

By developing students’ technical skills and critical understanding of AI, dental schools can prepare them to deliver high quality care in an increasingly technology-driven environment [12-14].

Although research on dental students’ views about AI have been done at international institutions as well as in countries, such as Turkey [15], Brazil [16], and Saudi Arabia [17], there are no such studies done in Kosovo. Therefore, this investigation addresses that gap by exploring how dental students in Kosovo perceive the use of AI in their future professional careers.

Objectives

The aim of this study was to evaluate dental students’ knowledge, attitudes, and perceptions regarding the incorporation of AI in dental practice, and to examine differences in these perspectives based on gender, type of institution, and year of study.

Material and methods

This cross-sectional descriptive study received approval from the Institutional Ethics Committee at Fa­culty of Dentistry, AAB College in Pristina, and included undergraduate dental students, both male and female, from the first to final year of their academic programs. Exclusion criteria applied to postgraduates as well as to practicing dentists or dental specialists. To assess knowledge, attitudes, and perceptions of dental students about AI, an online survey in the form of a questionnaire was developed and distributed via Google Forms. The questionnaire was adapted from a previously published study of Karan-Romero et al. [17] on a similar topic, with modifications made to suit the specific context of this research. Prior to distribution, the questionnaire was piloted among 10 students, who were asked to identify any confusing or misleading questions. Adjustments were then made based on their feedback to enhance clarity and relevance. The final survey was conducted in Kosovo and shared through social media platforms, accompanied by a brief overview of the study’s objectives. Convenience sampling method was used. Sample size of 285 was calculated based on a number of undergraduates dental students (n = 1,100), with 5% margin of error and 95% level of confidence.

The questionnaire consisted of two sections: an initial demographic section, collecting data on age, gender, academic level, and study sector (public or private), and a main section divided into three subsections, i.e., knowledge (4 questions), perception (12 questions), and attitude (3 questions). Most of the questions in the knowledge and attitude sections were direct, asking participants to choose between “Yes,” “No,” or “I don’t know.” However, there were a couple of exceptions; in the attitude subsection, question No. 4 asked participants who they would trust more in case of a disagreement (“Me” or “AI”). In the perception subsection, responses were divided between two formats: six questions used a 3-point Likert’s scale, with options ranging from “Agree” and “Neutral” (neither agree nor disagree) to “Disagree.” The remaining six questions required participants to select from “Yes,” “No,” or “I don’t know.” Question number 7 was presented as a multiple answer, with one option to select only.

Statistical analysis was performed using IBM SPSS version 23.0. Frequency analysis was done for all questions, and the results were presented as percentages relative to the total number of participants. Chi-square test of independence was employed for questions with categorical responses to assess differences across gender, institution type (private/public), and year of study. Kruskal-Wallis test was applied in questions with ordinal responses (Likert’s scale), to compare ranked data across the same variables. Significance level was set at p ≤ 0.05.

Results

Out of the 290 participants, a slight female’s predo­minance was observed (53%). Majority of participants were in their 6^th year (24%) and 5^th year (20%), followed by 3^rd year (19%). The second-year students composed the smallest group, with just 10% of participants. On the other hand, 79% were from private institutions, which might be due to a larger pool of private institution students (Table 1).

In terms of AI knowledge, nearly all participants (99%) were familiar with AI, with 88% having a basic understanding of how it works and 70% recognizing its potential applications in dentistry. However, only 20% felt confident using a dental AI program. Regarding perception, although majority of participants (78%) believed that AI could lead to significant advancements in dentistry and medicine, only 10% reported that AI’s diagnostic capabilities might surpass those of specialist doctors, and 17% thought that AI could serve as a definitive diagnostic tool, predict disease progression, and recovery chances. Furthermore, more than 80% of participants disagreed with the idea that AI could replace dentists and doctors, but many acknowledged that certain dental specialties, such as orthodontics and prosthodontics, might be significantly affected by AI. AI’s use in radiographic diagnosis was supported by most participants, particularly in identifying dental caries, jaw pathologies, periodontal diseases, and planning three-dimensional implants. However, some students remained neutral or uncertain about these applications. In terms of attitude, majority expressed willingness to learn, and 62% believed AI should be offered as a subject in academic curriculum (Table 2).

There were significant statistical differences among genders in attitude with regards to AI offered as a subject in academic programs. Female participants were significantly more likely to agree compared to male participants (p < 0.05). In addition, public institution students consistently demonstrated higher agreement with AI’s diagnostic (p < 0.05) (Table 3). Moreover, differences were most pronounced in later years, with senior students showing greater trust and agreement with AI’s dia­gnostic and prognostic capabilities (p < 0.05) (Table 4).

Discussion

The study examined differences in knowledge, perception, and attitudes toward AI across gender, institution type, and year of study, offering valuable insights into how these factors shape dental students’ views and the potential for integrating AI into education and clini­cal practice.

In our study, a high proportion of students (70%) were aware of AI application in dentistry, especially among senior students. These findings align with a study by Yüzbasiouglu et al. [15] on dental students in Turkey, showing over 60% of AI’s awareness, and a study by Tahsina et al. [18], who found that 89.63% of dental students in India were familiar with AI. Despite this widespread perception, both the current and the Turkish study revealed a significant gap in participants’ ability to use dental AI programs. Similarly, a South Korean research by Jeong et al. [19] found that only 24% of individuals described themselves as well or very well informed about AI, which might reflect a lack of confidence in effectively using these technologies. Globally, Busch et al. [20] highlighted that students generally have limited AI knowledge, with most reporting low levels of technological lite­racy despite positive attitudes toward AI in healthcare. These findings emphasize the need for targeted education, not only to raise awareness but also to teach students how to apply AI in their professional practice.

Optimism about AI’s potential was consistently high, with more than 70% of participants across stu­dies believing in its transformative role in dentistry [15, 18-20]. However, skepticism about AI replacing dentists remains a strong theme. In our study, over 80% of students rejected this idea – a higher proportion compared to 64% in a South Korean study [19]. The lowest level of uncertainty was observed in an Indian study, with only 38% of participants expressing skepticism [21]. This shared uncertainty highlights the general view that while AI is a powerful tool, it is not a substitute for human expertise.

There was a universal call for incorporating AI into dental curricula, with emphasis on both theoretical understanding and practical applications. This is consistent with findings from Karan-Romero et al. [17], where 67% of students supported AI inclusion in undergraduate studies, and 72% endorsed its integration into postgraduate programs. In all of the studies, most of individuals agreed that AI should be integrated into academic curricula. It is interesting to note that the need for more education and training to integrate AI into dental practice is not just a concern among dental students; it is something that practicing dentists recognize as well [22, 23]. This shared understanding across the profession shows how important it is to provide comprehensive AI education, not only for those starting their professional careers but also for experienced practitioners, so that everyone can confidently and effectively apply AI in their work.

In the current research, gender differences were most apparent in attitudes toward AI in education. Female participants (p < 0.05) were significantly more likely to support incorporating AI into academic programs compared to male participants. In line, an Indian study found that female participants were slightly more optimistic about AI’s application, although this difference was not statistically significant [24]. These conclusions might reflect differences in educational priorities or how technological advancements are valued in academic settings. Notably, no significant gender differences were found in knowledge or perceptions, suggesting that awareness and understanding are consistent across genders.

In our study, students from public institutes (p < 0.05) demonstrated significantly higher agreement with AI’s applications in dentistry compared to those from private institutions. These differences were particularly observed for radiographic diagnosis of jaw pathologies. Nonetheless, no significant variations were noted between participants from public and private institutions in terms of their awareness, basic understanding of AI, or attitude towards AI education.

Senior students showed greater confidence in using AI programs; similar patterns were seen in an Indian study (Seram et al. [21]), where postgraduates were more familiar with AI applications than undergraduates. Also, in a South Korean study [19], junior students demonstrated less AI knowledge. Senior students demonstrated stronger agreement with AI’s potential applications, such as diagnostics and treatment planning. This aligns with findings from an Indian study (Tahsina et al. [18]), where familiarity and positive perceptions of AI were higher among more experienced participants.

To bridge the gaps identified in this study, future efforts should prioritize integrating AI education into dental curricula in a structured way. The integration may start by developing basic knowledge during the early years of study through a curriculum review and the inclusion of dedicated AI modules. As students progress in studying, practical training and applications can be gradually introduced to enhance their understanding and clinical readiness. This can be further supported by interdisciplinary collaboration with computer science or engineering departments, enabling students to gain deeper insights into the technological aspects of AI. Specific tools, such as AI-powered radiographic analysis that helps students understand how AI interprets dental imaging as well as AI applications in orthodontics that support learning in cephalometric diagnostics and digital treatment planning, are just a few examples that can enhance dental education. Future research should focus on understanding how AI education impacts clinical practice over time, and how students’ perceptions of AI evolve as they gain more exposure to these technologies. Also, it is important to consider regional and institutional differences in the efforts to ensure equitable access to AI training. By taking these steps, we can better prepare future dental professionals to confidently embrace the growing role of AI in dental field.

Conclusions

Overall, this study found that students reported having heard about AI in dentistry, indicating widespread awareness. There were some gender and institutional differences, but slightly lower awareness among students of the earlier years.

Disclosures

Author contributions: Conceptualization: D.I.S., A.A., B.K.; Methodology: D.I.S., A.A., B.K.; Questionnaire adaptation: D.I.S., A.A., B.K.; Investigation and data collection: D.I.S., A.A., B.K.; Formal analysis: D.I.S., A.A., B.K.; Data curation: D.I.S., A.A., B.K.; Writing of origi­nal draft: D.I.S., A.A., B.K.; Writing – review and editing: D.I.S., A.A., B.K.; Supervision: D.I.S., A.A., B.K.; Project administration: D.I.S., A.A., B.K. All authors have read and agreed to the published version of the manuscript.

Funding: This research received no external funding.

Institutional Review Board statement: This study was approved by the Institutional Ethics Committee at Faculty of Dentistry, AAB College in Pristina (approval number: 17/09-2024 issued on 24 September 2024).

Informed consent statement: Electronic informed consent was obtained from all participants before they completed anonymous questionnaire.

Data availability statement: The data supporting the findings of this study are available from the corresponding author upon reasonable request.

Acknowledgments: None.

Conflicts of interest: The authors declare no conflicts of interest.

AI use statement: No artificial intelligence tools were used in the preparation of this manuscript.

References