AI in academia and business

Authors

Daniela Paola Ávalos Espinoza
Universidad Estatal de Bolívar. Guaranda 020150, Ecuador. ROR: https://ror.org/005cgg117
https://orcid.org/0000-0002-7184-3318
Carlos Napoleón Ribadeneira Zapata
Universidad Estatal de Bolívar. Guaranda 020150, Ecuador. ROR: https://ror.org/005cgg117
https://orcid.org/0000-0001-7337-3850
Wilter Rodolfo Camacho Arellano Wilter Rodolfo Camacho Arellano
Universidad Estatal de Bolívar. Guaranda 020150, Ecuador. ROR: https://ror.org/005cgg117
https://orcid.org/0000-0002-4259-0032
Charles Paul Vizcarra Armijos Charles Paul Vizcarra Armijos
Universidad Estatal de Bolívar. Guaranda 020150, Ecuador. ROR: https://ror.org/005cgg117
https://orcid.org/0000-0002-0247-4731

Keywords:

education, ethics, artificial intelligence, scientific research, digital marketing

Synopsis

The volume AI in academia and business presents an interdisciplinary analysis of the integration of artificial intelligence across key domains such as scientific research, education, and digital marketing; this work brings together four chapters that examine the impact of these technologies from technical, pedagogical, ethical, and social perspectives. In this context, the purpose of the volume is to analyze how artificial intelligence reshapes knowledge production processes, teaching-learning dynamics, and the understanding of consumer behavior in contemporary digital environments. The overall methodology is based on systematic reviews of scientific literature following PRISMA 2020 guidelines, enabling the identification, selection, and analysis of empirical evidence published between 2020 and 2025 in indexed databases; this approach ensures methodological rigor, transparency, and validity in the synthesis of findings. Through thematic analysis, categories are structured around the automation of research processes, personalized learning, consumer behavior analytics, and the ethical challenges associated with the use of intelligent technologies. The findings demonstrate that artificial intelligence enhances efficiency in scientific production, improves educational outcomes through adaptive systems, and transforms marketing strategies through personalization and predictive decision-making; however, risks related to ethics, privacy, information quality, and the digital divide are also identified. Consequently, the volume concludes that artificial intelligence constitutes a strategic axis of social transformation, whose implementation requires a critical, regulated, and human-centered approach.

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References

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Published

April 29, 2026

Online ISSN

3103-117X

Details about the available publication format: MTC V2i2 2026

MTC V2i2 2026

ISBN-13 (15)

978-9942-7391-8-6

Details about the available publication format: MTC V2i2e1 2026

MTC V2i2e1 2026

ISBN-13 (15)

978-9942-7391-8-6

Details about the available publication format: MTC V2i2e2 2026

MTC V2i2e2 2026

ISBN-13 (15)

978-9942-7391-8-6

Details about the available publication format: MTC V2i2e3 2026

MTC V2i2e3 2026

ISBN-13 (15)

978-9942-7391-8-6

Details about the available publication format: MTC V2i2e4 2026

MTC V2i2e4 2026

ISBN-13 (15)

978-9942-7391-8-6

How to Cite

AI in academia and business: Vol. V2i2. (2026). Editorial Unión Científica. https://doi.org/10.63804/mtc.v2i2