Bridging the Gap Economic Accessibility of AI-Enabled Dental Care in Low- and Middle-Income Setting

European Journal of Prosthodontics and Restorative Dentistry (2026) 34(3s), 30–38

Guided implant surgery, Conventional implant placement, Computer-assisted implant surgery, Dynamic navigation, Static guided surgery

Dr. Pooja Singh1*, Prof Manisha A Mehrotra2,
Ritishaa Singh3, Dr Sadananda Hota4, Dr.
Anita Awasthi5, Prof. Sandeep Kumar Singh6

Bridging the Gap Economic
Accessibility of AI-Enabled
Dental Care in Low- and
Middle-Income Setting

1*

Assistant Professor, Department of
Economics, Specialization in Economics,
Chhatrapati Shahu Ji Maharaj Kanpur, Uttar
Pradesh-208024, India, Email Id:
poojasingh@csjmu.ac.in, Orcid Id:
https://orcid.org/0009-0000-8946-890X
2

Professor, Department of Economics,
Specialization in Economics, Banaras Hindu
University, Varanasi, Uttar Pradesh-221005,
India, Email Id: manueco@bhu.ac.in, Orcid
Id: 0000000158146772
3

Student, Department of IPM (BBA-MBA),
Specialization in Management, Indian
Institute of Management- Rohtak, Sunarian,
Haryana-124010, India, Email Id:
ritsa.singh08@gmail.com, Orcid Id:
https://orcid.org/0009-0000-6630-1883
4

Professor, Department of Prosthodontics,
Specialization in Prosthodontics, Kalinga
Institute of Dental Sciences, Kalinga Institute
of Industrial technology, Bhubaneswar,
Odisha-751024, India, Email Id:
sadananda.hota@kids.ac.in, Orcid Id: 00000002-3750-1752

AI's influence on healthcare systems is reshaping the health industry in many ways, including providing accurate diagnostics, creating treatment plans, and improving access to healthcare. The economic viability of AIbased oral health intervention in low and middle-income communities, however, hasn't been thoroughly studied. The purpose of this study is to investigate the accessibility, affordability, acceptance and barriers of using AI in dental care services in resource-poor environments. This research is quantitative research design with cross sectional method and sampling is done by conveniant sampling with number of sample respondents 50 respondents. The data were analyzed using descriptive statistics, reliability analysis, correlation analysis and the regression interpretation method of Microsoft Excel. The findings revealed that the respondents overall positively perceived the economic advantages of AI-assisted dental care since this could contribute to decreasing the cost of care, the amount of time spent in the waiting area, and the distance to dental services as well as provide remote consultations. The results suggest that AI-powered dental services can contribute to more inclusive and sustainable dental care systems, given that there are effective policy frameworks, government investments, and fair digital healthcare approaches. The study underscores the need to embed AI technologies into oral health delivery systems to enhance access to oral health care and mitigate oral health care inequalities in low-resource areas. Keywords: Dental Care, Economic Accessibility, Oral Healthcare, Lowand Middle-Income Countries, Healthcare Equity

5

Assistant Professor, Department of Social Work, Specialization in Sociology of Development, Chhatrapati Shahu Ji Maharaj University, Kanpur, Uttar Pradesh-208024, India, Email Id: anitaawasthis@gmail.com, Orcid Id: 0009-0007-2310-264X 6

Professor, Faculty of Advanced Studies of Social Science, Specialization in Social Work Chhatrapati Shahu Ji Maharaj University, Kanpur, Uttar Pradesh-208024, India, Email Id: drsandeepmsw@gmail.com, Orcid Id: 0009-0009-5073-7450

Received: 17.04.2026 Revised: 23.04.2026 Accepted: 20.05.2026

1. Introduction The field of artificial intelligence (AI) has become one of the most disruptive technologies in the contemporary healthcare system, impacting the diagnostic accuracy, treatment planning, and access to healthcare significantly. Over the past few years, AI has become more widely spread in dental healthcare, with machine learning, deep learning, and predictive algorithms starting to be applied to enhance oral disease diagnostics, radiographic interpretation, and clinical decision-making (Schwendicke et al., 2020). The development of AI in the healthcare industry has increased the digital transformation of dentistry through quicker, more precise and data-driven oral healthcare services (Meskó et al., 2018). Modern dentistry is now equipped with AI-driven diagnostic imaging, predictive analytics, teledentistry, robotics, and automated treatment planning systems that enhance clinical outcomes and operational efficiencies (Dua et al., 2025). The use of AI in the field of dentistry has proved to be quite useful in identifying dental caries, periodontal diseases, and oral abnormalities via sophisticated imaging technologies. Dental radiograph and diagnostic prediction have demonstrated outstanding performance by deep learning algorithms (Lee et al., 2018). Likewise, machine learning models have been used effectively in predicting root caries and progression of oral disease (Hung et al., 2019). Cone beam •••••••••••••••••••••••••••••••• ejprd.org- Published by Riset Publishing Services LLC.

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