Original Research Open access

Knowledge, attitude and perception toward robotics and artificial intelligence in dentistry among dentists and dental students of Assam: A cross-sectional study

Enakshi Mitra , Navpreet Kaur , Manish Bhalla , Vivek Kumar Sharma , Sonal Subhangi , Ramen Haloi

Pages 41-47 Published 16 July 2026 DOI 10.65929/JSAD.2026.1.2.003 Rights held by the authors

Abstract

Introduction: Artificial Intelligence (AI) and Robotics are the emerging technologies that are revolutionizing modern dentistry by improving diagnosis, treatment planning and clinical efficiency. Awareness and acceptance of these technologies by dental professionals is important for the successful integration of these technologies into clinical practice and education.

Objective: The objective of this online cross-sectional study was to evaluate the Knowledge, Attitude and Perception toward Artificial Intelligence and Robotics in dentistry among dentists and dental students in Assam.

Materials and Method: A cross-sectional online questionnaire study was conducted among 200 dentists and dental students of Assam. A structured self-administered questionnaire was distributed through Google Forms to assess the Knowledge, Attitude and Perception towards AI and Robotics in Dentistry. Descriptive statistics and chi-square test were done using SPSS version 27. p≤0.05 was considered statistically significant.

Results: This study revealed that 97% of participants had good Knowledge and positive Perception toward AI and Robotics in dentistry. All participants demonstrated a positive Attitude towards learning and adoption of these technologies. Most participants were aware of AI applications in radiographic interpretation (92%), prediction of implant placement (92%) and oral cancer detection (77%). Statistically significant association was found between knowledge and age and gender (p≤0.05) but not with qualification.

Conclusion: Dentists and dental students demonstrated favorable knowledge, positive attitude, and good perception regarding AI and Robotics in dentistry. Integration of AI-based learning into dental curriculum and clinical practice is recommended.

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How to cite this article

Mitra E, Kaur N, Bhalla M, Sharma VK, Subhangi S, Haloi R. Knowledge, attitude and perception toward robotics and artificial intelligence in dentistry among dentists and dental students of Assam: A cross-sectional study. J. Sci. Adv. Dent. 2026;1(2):41-47. doi:10.65929/JSAD.2026.1.2.003

Mitra, E., Kaur, N., Bhalla, M., Sharma, V. K., Subhangi, S., & Haloi, R. (2026). Knowledge, attitude and perception toward robotics and artificial intelligence in dentistry among dentists and dental students of Assam: A cross-sectional study. Journal of Scientific Advances in Dentistry, 1(2), 41-47. https://doi.org/10.65929/JSAD.2026.1.2.003

Enakshi Mitra, Navpreet Kaur, Manish Bhalla, Vivek Kumar Sharma, Sonal Subhangi, and Ramen Haloi. "Knowledge, attitude and perception toward robotics and artificial intelligence in dentistry among dentists and dental students of Assam: A cross-sectional study." Journal of Scientific Advances in Dentistry, vol. 1, no. 2, 2026, pp. 41-47. https://doi.org/10.65929/JSAD.2026.1.2.003

Enakshi Mitra, Navpreet Kaur, Manish Bhalla, Vivek Kumar Sharma, Sonal Subhangi, and Ramen Haloi. "Knowledge, attitude and perception toward robotics and artificial intelligence in dentistry among dentists and dental students of Assam: A cross-sectional study." Journal of Scientific Advances in Dentistry 1, no. 2 (2026): 41-47. https://doi.org/10.65929/JSAD.2026.1.2.003

Mitra, E., Kaur, N., Bhalla, M., Sharma, V. K., Subhangi, S., and Haloi, R. (2026) 'Knowledge, attitude and perception toward robotics and artificial intelligence in dentistry among dentists and dental students of Assam: A cross-sectional study', Journal of Scientific Advances in Dentistry, 1(2), pp. 41-47. https://doi.org/10.65929/JSAD.2026.1.2.003

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© 2026 the authors. Published by REVO Publication. This article is distributed under CC BY 4.0, which permits use and redistribution provided the original work is properly cited.