What is Natural Language Generation (NLG)

Generative AI, such as generative pre-trained transformer (GPT), has seen rapid advancements in recent years, offering a wide range of applications, but it also presents several challenges and opportunities. GPT can automate content generation for various industries, including journalism, marketing, and entertainment, reducing the need for manual content creation. Generative AI can personalize content and recommendations in e-commerce, streaming services, and more, enhancing user experiences. Generative AI, such as GPT, offers immense potential across various sectors but requires careful management to address bias, ethics, and quality control challenges. As technology evolves, finding the right balance between control and creativity will be crucial for maximizing its benefits while minimizing risks. Based on the above, the authors systematically review the bibliometric literature on how Generative AI and generative pre-trained transformer applications challenge opportunities using the Scopus database by analysing 49 academic and/or scientific documents.