Artificial Intelligence: The Prevalent Coauthor Among Early-Career Surgeons

<h3>Study Design</h3> Cross-sectional survey study <h3>Background</h3> Artificial intelligence (AI) tools are increasingly integrated into various aspects of medicine, including medical research. However, the scope and manner in which early-career surgeons utilize AI tools in their research remain inadequately understood. <h3>Objective</h3> This study aimed to investigate the frequency and specific applications of AI tools in medical research among early-career surgeons, including their perceptions, concerns, and outlook regarding AI in research. <h3>Methods</h3> A survey comprising 25 questions was distributed among members of an international club of early-career spine surgeons (&lt;10 years of experience). The survey assessed demographics, AI tool utilization, access to AI training resources, and perceptions of AI benefits and concerns in research. <h3>Results</h3> Sixty early-career surgeons participated, with 86.7% reporting AI tool use in their research. ChatGPT was the most frequently utilized tool, with a usage rate of 93.1%. AI tools were primarily used for grammatical proofreading (69.6%) and rephrasing (64.3%), while 26.8% of participants used AI for statistical analysis. While 80.4% perceived improved efficiency as a key benefit, 70.0% expressed concerns about reliability. None of the participants had received formal AI training, and only 15.0% had access to AI mentors. Despite these challenges, 91.6% anticipated a positive long-term impact of AI on research. <h3>Conclusion</h3> AI tools are widely adopted among early-career surgeons for various research tasks, extending from text generation to data analysis. However, the absence of formal training and concerns regarding the reliability of AI tools underscore the necessity of training for AI integration in medical research. <h3>Clinical Relevance</h3> This study provides timely insights into AI adoption patterns among early-career surgeons, highlighting the urgent need for formal AI training programs to ensure responsible research practices. <h3>Level of Evidence</h3> 4.