(untitled) (Revista Docentes 2.0, 2025)
In the last decade, artificial intelligence (AI) has emerged as a transformative agent in producing scientific knowledge, impacting multiple disciplines in a transversal way. The research’s purpose is to analyze the impact of AI-based prompts in optimizing data processing and structuring. A qualitative approach was adopted, based on the interpretive paradigm and hermeneutic method, with a descriptive cross-sectional design. The sample representative consisted of 25 academic researchers. For information collection, semi-structured interviews were used, whose analysis was carried out through open coding and NVivo software, allowing the identification of emerging patterns and significant trends. The results show that AI increases efficiency in data management and favors the identification of new lines of scientific inquiry. In addition, a notable reduction in processing times and increased precision in analyzing large volumes of information were observed. Consequently, the tools are consolidated as notable resources for contemporary research, particularly in contexts where the management of massive data and the optimization of comparative methodologies are decisive. It is recommended that they be incorporated into all phases of the knowledge-generation process and that ethical and regulatory frameworks be established to regulate the use of AI in research, promoting its integration as a complementary tool and not as a substitute for human reasoning in the construction of scientific knowledge.