A retrospective chart review of 102,059 virtual primary care clinical encounters from October 1, 2022, to January 31, 2023 A Mayo Clinic study shows that physicians and AI models agree on over 80% of diagnoses, indicating AI's strong potential as a second opinion in medical diagnosis. Bladder Infections diagnosis had the highest agreement rate of 98.9% indicating a well-specialized model developed. AI can help reduce the medical error rate and the time taken for a diagnosis, the third-leading cause of death in the US, by offering consistent and unbiased evaluations. The time taken for an AI-enabled diagnosis is approximately 44.4 seconds on average while a conventional doctor's diagnosis takes an average time of 3.6 minutes.  However, conditions that have high misdiagnosis rates, such as dental infections, will record lower agreement rates due to a combination of human and algorithm errors. Apart from training more radiologists, AI implementation could help mitigate a shortage of radiologists in practices and academic departments. As such, the model's effectiveness depends on the quality and variety of data it is exposed to. While AI could assist in correcting human errors, it also requires continuous improvement through exposure to diverse cases.