Artificial Intelligence (AI) in dentistry is developing quickly, offering both possibilities and difficulties for clinical treatment and teaching [28]. As digital technologies become more prevalent, understanding how future professionals perceive and adapt to these tools is crucial. Our study aimed to capture these insights from a diverse group of postgraduate dental students in Egypt.
Regarding the demographic data, the majority of participants in the sample were 420 females (56.5%) while males were 324 (43.5%), likewise, Yüzbaşıoğlu [23] observed higher female participation (59% females and 41% males), followed by Murali et al., [17] (73% females and 27% males), and another study [29], reported (71.4% females and 28.9% males). Nonetheless, an identical proportion of participants from both genders (49.2% females and 50.8% males) were reported by Khanagar et al., [18]. One possible explanation for the higher proportion of female respondents in our study is that female students may be more likely to respond to survey-based research on ethical, educational or new technology topics like AI, perhaps as a result of higher conscientiousness or engagement [30].
In the present study, 58.6% of respondents believe that AI will bring in a new era of dental innovation, while 26.5% disagree and 14.9% remain uncertain. Although 42.9% of respondents consider AI essential to healthcare services, only 39.5% agree that AI has the potential to enhance dentists’ effectiveness.
These findings align with the key results reported in a recent systematic review by Dashti et al., 2024 [31], which synthesized data from 13 cross-sectional studies across multiple countries, including India, Saudi Arabia, Turkey, and Pakistan. Their review reported that approximately 72% of dental students believed that artificial intelligence will play a significant role in dentistry in the near future. This perception may be attributed to the fact that AI encompasses a wide range of advanced technologies that are increasingly impacting everyday life. The development of AI enables big data analysis, which supports improved decision-making and yields trustworthy information [28].
About half (50.3%) of the participants in the current study indicated that they would like to learn more about the concepts of artificial intelligence. Likely, a similar study observed a significant increase, with 63.3 and 58.3% of dental students and dentists, respectively [19]. While the percentage of medical and dental students in 63 countries who stated they were interested in the application of AI in daily life was just 15.3% in a prior survey [32].
Despite positive attitudes, significant concerns persist. Many respondents were skeptical about AI’s reliability, with particular apprehension regarding its role in clinical judgment and research originality. These concerns have been noted in multiple international surveys [12, 29, 32] and reflect broader unease about AI’s opacity and the potential for misuse or error.
Dealing with these issues requires a multi-faceted approach; comprehensive AI education in dental curriculum including ethics exposure and ensuring transparency in the application of AI. These actions can bridge the gap between interest and confidence so that future dentists will trust AI systems.
Interestingly, most participants rejected the notion that AI could replace dentists entirely. This skepticism is supported by the recognition that human elements such as empathy, nuanced communication, and ethical reasoning remain irreplaceable in healthcare interactions [33].
The current study found that younger participants and BDS holders are more likely to use AI-based software, as well as showing more optimism about AI’s potential to advance dentistry, whereas PhD holders are more skeptical about its integral role in healthcare. These findings align with previous studies [18, 19], which also report greater interest in AI among younger or less experienced dental professionals. However, differences in educational systems, clinical exposure, and cultural attitudes toward emerging technologies may account for some variation across studies.
These findings may be attributed to the fact that younger participants are exposed to digital technologies and evolving curricula that increasingly incorporate AI-related content. In contrast, the skepticism among PhD holders may reflect their greater clinical experience, familiarity with research standards, and awareness of AI’s current limitations, such as reliability, ethical considerations, and lack of clinical validation.
Furthermore, our results support the recommendations for structured AI training and clinical verification suggested in the recent literature [1, 2]. The high interest among younger and less experienced dental professionals is consistent with calls to incorporate AI into dental education and training. Additionally, concerns about clinical reliability and ethical aspects align with the need for strict validation processes before widespread use.
Periodontics (34%) and endodontics (29.6%) stand out as the specialities most aligned with AI developments and the use of AI software, while other fields continue to be marked by uncertainty. These findings align with a previous survey conducted in India, where Endodontics (38%) and Oral Radiology (41%) showed the highest levels of AI adoption, largely due to their reliance on image analysis [17]. Similarly, a study from Saudi Arabia reported that Periodontics (31%) was the leading speciality utilizing AI, driven by digital workflows in implant planning [18]. In contrast, specialities such as Oral Surgery demonstrated lower levels of AI adoption, likely due to the tactile complexity of procedures and limited compatibility with AI-based automation [6]. These results suggest that AI integration is more prevalent in specialities that emphasize diagnostic precision, digital workflows, and data-driven care.
A higher rate of AI usage in Endodontics and Periodontics may indicate the emphasis these disciplines place on diagnostic imaging and quantitative data, areas where AI’s pattern-recognition capabilities provide a significant advantage [34, 35]. The integration of AI with digital dentistry platforms, such as guided implant surgery and dynamic navigation systems, further supports its growing adoption [1, 36, 37]. Moreover, the research-intensive nature of these specialities and AI’s potential to improve the efficiency of time-critical tasks may also contribute to its increased use in these fields [34, 38, 39].
In the present study, the majority (68.1%) doubt that AI might replace dentists, while only 4.4% think it could. It was in accordance with a previous study [20]. Likewise, according to a previous survey [17], 37.78% of dental interns did not agree that this new technology would replace them. While, on the other hand, another study [23], reported that 28.6% of the participants believed that dentists would be replaced by AI.
These results suggest a general consensus that AI will be considered as a supporting role, rather than a replacement for Dentists. The skepticism regarding AI’s ability to completely replace dentists might come from realizing that dental work actually incorporates another level of skill, including clinical decision-making, patient management, and manual dexterity, which are difficult to imitate in AI platforms available today. Additionally, the limited integration of AI into dental education may enhance clinical uncertainty regarding the clinician’s role toward AI.
The accuracy of information generated by AI is a major concern for 83.2% of participants. Two other significant concerns are an over-reliance on technology (78.1%) and a potential loss of originality in research (59.3%). The absence of clinical evidence for AI applications in dentistry was brought up by 77.4% of respondents.
According to Khanagar’s study [18], AI is revolutionary in terms of delivering reliable facts for analytical scientific decision-making. In addition to saving time and lowering the possibility of human error, AI models can be helpful tools for identifying survivors of large-scale disasters and as an extra aid in medico-legal scenarios.
More than half of the responders to the present survey (49.3%) support incorporating AI into graduate or undergraduate education to address knowledge gaps. The majority of participants (73.1%) believe that more clinical studies are necessary to demonstrate the feasibility of AI applications, this was in line with previous studies.
Similarly, according to a prior survey [19], as many as 49.0% of respondents thought that AI education should be taught in dental schools, while the proportion of participants was somewhat higher than that in previous studies [23, 40] as 79.80% and 85.6%, respectively.
Participants advocated for greater integration of AI education into dental curricula and emphasized the need for robust clinical trials to validate AI tools. These findings are aligned with previous studies to include AI literacy in dental education to better prepare students for future practice environments [20, 24, 41].
Ethical considerations play a central place in the responsible integration of AI in dentistry. Globally, there is growing attention to key concerns such as algorithmic bias, data privacy, patient consent, and the transparency of AI decision-making issues that are widely debated in digital health policies. For instance, global digital health strategies emphasize the need for AI systems to be explainable, fair and human-centered, particularly in healthcare settings where flaws systems can directly impact patient outcomes [42]. In the context of dentistry, clear patient communication is essential both when AI tools guide clinical decisions and when such tools have been independently tested for fairness and accuracy. Ethical implementation is not only a technical issue, but also requires regulatory alignment, continuous professional education, and organizational policies with a focus on fairness and accountability.
The multivariate logistic regression analyses provided clear evidence that demographic and professional factors independently impacted dental professionals’ usage and attitude toward AI. In different models, age, speciality, gender, graduation year, and educational level were all significant predictors. Younger participants and those with lower academic qualifications (BD and MSc) showed higher interest in learning about AI and greater optimism regarding its potential to improve dental practice. On the other hand, recent graduates (2010–2024) and PhD holders were considerably more skeptical, especially about AI’s potential to significantly alter healthcare service or replace dentists. While specialities like periodontics and endodontics showed stronger adoption of AI, probably as a result of their reliance on imaging and computerized workflows, male participants were more likely to view AI as a transformative trend.
These findings highlight the critical gap between awareness of AI’s potential and its practical adoption in dentistry. While many practitioners recognize the value of AI, its integration into clinical practice remains limited due to educational, ethical, and practical barriers. Addressing this gap will require structured clinical validation, targeted training, and tailored AI education to build confidence and competence across different practitioner groups. Institutional support and ongoing professional dialogue will also be essential to facilitate the responsible and effective incorporation of AI into dental practice.
This study offers several notable strengths. First, the large and diverse sample of postgraduate dental students from multiple institutions enhances the generalizability of the findings. By addressing a timely and emerging topic AI in dental practice and education the study provides relevant insights into the readiness of future professionals to adopt AI technologies. The structured questionnaire, grounded in existing literature and validated tools, allowed for a comprehensive exploration of participants’ perceptions, usage patterns, and ethical concerns. Additionally, the use of appropriate statistical methods ensured a robust analysis of demographic influences. The ethical conduct of the study, including informed consent and data confidentiality, further strengthens its reliability. Collectively, these elements contribute to a well-rounded understanding of AI’s perceived role and challenges in the context of postgraduate dental education.
Limitations
This study utilized a cross-sectional survey design that measures self-reported perceptions and attitudes, which restricts causal inferences and may introduce response bias. The findings may not be generalizable to other populations or clinical settings due to contextual differences and potential sampling bias. Furthermore, the study focuses on trends in AI awareness and acceptance rather than evaluating the clinical effectiveness or outcomes of AI applications.
While English is the standard language of instruction in all participating dental programs, administrating the survey exclusively in English may be considered a limitation for non-native speakers with varying levels of proficiency, which could have affected their understanding or interpretation of certain survey items.
Additionally, a 3-point forced-choice Likert scale may restrict response nuance compared to 5 or 7-point scales, it was selected to minimize cognitive burden and ensure consistency across participants with varying familiarity with AI and different levels of language proficiency. Finally, some participants may have experienced survey fatigue by the number of questions, which could have compromised response quality and validity.
Implications for practice and education
To responsibly integrate AI into dentistry, a pragmatic and evidence-based approach must guide both clinical implementation and education. This can be achieved through interdisciplinary courses for both undergraduate and postgraduate levels that cover fundamental AI principles, ethical concerns such as bias and privacy, as well as practical experience with AI-based diagnostic systems.
Practical experience with AI-based diagnostic systems should be included in training to prepare future dentists for real-world applications. In clinical practice, AI should be implemented gradually. All AI-assisted decisions must be verified by a dentist via “human-in-the-loop” (HITL) systems to minimize errors and manage legal accountability.
Policymakers should aim to align international regulations, such as those in the U.S. FDA and AI Act within the European Union (EU), and mandate continuous training for skills related to AI for dental professionals. Research should focus on long-term clinical outcomes, cost-effectiveness in low-resource settings, and regular use of reporting guidance such as CONSORT-AI. Funding should also support efforts to reduce disparities in AI access and performance.
Future directions
To bridge the identified gaps in AI knowledge and readiness, dental education systems must incorporate comprehensive training on artificial intelligence [43]. Prospective clinical trials and real-world studies are essential to validate the long-term clinical utility and reliability of AI technologies in dentistry. These efforts should involve collaboration with qualified specialists to ensure that AI is integrated in a manner that upholds the highest standards of privacy, patient safety, and ethical practice. By aligning education with responsible implementation, the dental profession can leverage AI to enhance rather than replace clinical judgment, thereby ensuring patient safety and promoting equitable care.
