{"title":"The impact of integrating artificial intelligence into regulatory affairs functions in the Medtech industry.","authors":"Renee Cotta, Mary Garvey, Olivia McDermott","doi":"10.1080/17434440.2026.2648001","DOIUrl":null,"url":null,"abstract":"<p><strong>Introduction: </strong>Artificial intelligence is becoming an important tool in the medical technology industry where its implementation has the potential to streamline processes and provide rapid and efficient data analysis and interpretation in the regulatory affairs function.</p><p><strong>Areas covered: </strong>The adoption of Artificial Intelligence is emerging as a tool in the MedTech Regulatory Affairs function and the success factors and barriers to successful implementation are outlined. Empirical case applications and hands-on experiences of artificial intelligence are limiting factors in the adoption of AI. The factors for successful adoption include rigorous validation processes aligned with trustworthiness, transparency, and reproducibility. In addition, effective regulatory guidance and internal governance are required. Literature from the last two decades from 2016 to 2026 in relation to the above was reviewed from the Web of Science, SCOPUS, and MEDLINE academic databases.</p><p><strong>Expert opinion: </strong>Currently, persistent barriers to artificial intelligence adoption are global acceptance by regulatory bodies for artificial intelligence-generated outputs, assuring compliance with the quality and interoperability of data across jurisdictions, data hallucinations, cost, training, and integration hinder the application of artificial intelligence. Cross-regional policy harmonization is an opportunity for the regulators as adoption broadens.</p>","PeriodicalId":94006,"journal":{"name":"Expert review of medical devices","volume":" ","pages":"509-518"},"PeriodicalIF":2.7000,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Expert review of medical devices","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1080/17434440.2026.2648001","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2026/4/16 0:00:00","PubModel":"Epub","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Introduction: Artificial intelligence is becoming an important tool in the medical technology industry where its implementation has the potential to streamline processes and provide rapid and efficient data analysis and interpretation in the regulatory affairs function.
Areas covered: The adoption of Artificial Intelligence is emerging as a tool in the MedTech Regulatory Affairs function and the success factors and barriers to successful implementation are outlined. Empirical case applications and hands-on experiences of artificial intelligence are limiting factors in the adoption of AI. The factors for successful adoption include rigorous validation processes aligned with trustworthiness, transparency, and reproducibility. In addition, effective regulatory guidance and internal governance are required. Literature from the last two decades from 2016 to 2026 in relation to the above was reviewed from the Web of Science, SCOPUS, and MEDLINE academic databases.
Expert opinion: Currently, persistent barriers to artificial intelligence adoption are global acceptance by regulatory bodies for artificial intelligence-generated outputs, assuring compliance with the quality and interoperability of data across jurisdictions, data hallucinations, cost, training, and integration hinder the application of artificial intelligence. Cross-regional policy harmonization is an opportunity for the regulators as adoption broadens.
导读:人工智能正在成为医疗技术行业的重要工具,其实施有可能简化流程,并在监管事务功能中提供快速高效的数据分析和解释。涵盖领域:人工智能的采用正在成为医疗技术监管事务功能中的一种工具,并概述了成功实施的成功因素和障碍。人工智能的实证案例应用和实践经验是采用人工智能的限制因素。成功采用的因素包括与可信度、透明度和可再现性相一致的严格验证过程。此外,还需要有效的监管指导和内部治理。从Web Of Science、SCOPUS和MEDLINE学术数据库中检索了2016年至2026年间与上述内容相关的近20年文献。专家意见:目前,人工智能采用的持续障碍是监管机构对人工智能生成的输出的全球接受,确保跨司法管辖区数据的质量和互操作性,数据幻觉,成本,培训和集成阻碍了人工智能的应用。随着采用范围的扩大,跨区域政策协调对监管机构来说是一个机会。