Health Care Professional Perspectives on Artificial Intelligence DiagnosticTools for Oral Cancer: A Systematic Review

Background: Radiological detection and diagnosis of oral cancer has been revolutionized by artificialintelligence through improved accuracy together with faster exam times and standardized results. Healthcareprofessionals determine how successfully AI can integrate into clinical practice through their acceptance andpreparedness for such systems.Objective: A systematic review analyzes prevailing data about healthcare professional perspectives togetherwith their attitudes toward their knowledge level and obstacles they perceive in relation to AI-based oral cancerdiagnostic tools.Methods: The research team carried out a broad database search through PubMed and Scopus and Web ofScience along with Google Scholar for their search period (January 2010 – March 2025). The research includedstudies which examined dentists' and oral pathologists' and oncologists' perspectives about AI diagnostic toolsalong with other healthcare personnel views on AI diagnostic technologies in oral oncology. Two independentreviewers executed data extraction together with quality assessment of the selected studies. A narrative approachwas used for the synthesis of results.Results: Twenty-three published studies revealed data from 3,152 medical personnel including dentists togetherwith oral pathologists and maxillofacial surgeons and oncologists and general practitioners. Professionalhealthcare providers showed positive sentiments toward using AI for oral cancer diagnosis since theyrecognized its capability to enhance both early detection and diagnostic precision (78%). A total of 36% ofparticipants showed they had appropriate understanding or training regarding AI whereas 58% declared theirlack of familiarity with AI tools. The respondents who participated in the study mainly identified threeadvantages of AI technology which were improved diagnostic precision alongside accelerated decision-makingcombined with standardized diagnostic practices. Numerous professionals expressed concern about theirdiminished clinical freedom (45%), worrying data privacy problems (51%) and difficulties proving legalcompliance (39%). Most professionals expressed openness to AI adoption when they receive training combinedwith regulatory backing. The participants demanded medical schools to include AI education in their coursesand demanded better interaction between healthcare practitioners and AI engineers to produce successful AIintegration results.Conclusion: For AI integration in oral cancer diagnostics to succeed healthcare professionals need specifictraining together with defined regulations and systematic collaborative development that receives end-userinput. Further work should concentrate on developing staff capabilities and resolving legal and practicalconcerns alongside morality issues to advance AI acceptance in oral health care.