The objective is to identify the impact of artificial intelligence in business marketing, the main clusters, the AI tools that have been applied for the benefit of marketing, their implementation process, the strategies employed in the application and the main challenges of AI in marketing application. To this end, a systematic review was conducted following the PRISMA guidelines and the PICO question of the empirical studies found in the Scopus and Web of Science (WoS) databases. Subsequently, a bibliometric analysis was developed and a total of 35 scientific articles were identified in journals indexed between the years 2019 and 2024 that met the inclusion criteria and were ready to extract the information. It was identified that the application of AI in companies improved the quality of predictions about customer behavior, which helps to perform better segmentation and personalization of offers to the target audience, and to increase customer retention. It was concluded that there is a close connection between artificial intelligence, marketing and commerce, and emphasis was placed on emerging areas such as data mining, machine learning, ChatGPT-4, neural networks, BiLSTM, chatbots algorithms and virtual assistants, which are revolutionizing the field.

Artificial intelligence (AI) has advanced significantly in medicine, impacting the detection and treatment of diseases by storing data and analyzing repetitive patterns. Currently, medical diagnoses often involve long waiting times and, in some cases, can generate false results, further prolonging the wait and negatively impacting treatments. The study systematically reviews the literature on the impact of AI on the diagnosis and treatment of diseases and health conditions. Initially, 1211 articles were obtained by searching the Scopus database, then, applying the inclusion and exclusion criteria, 14 articles most relevant to the study were identified. At the methodological level, the guidelines established by the PRISMA method were applied. The results show that AI can provide diagnoses with an accuracy of 84.7% to 98% and specificities of 50% to 100%. In addition, AI has significantly improved the accuracy of medical diagnoses, reducing the need for unnecessary procedures and enabling continuous monitoring of patients through IoT devices. This facilitates the work of healthcare professionals and contributes to more efficient and effective management of diseases and health conditions.