La Inteligencia Artificial aplicada en la Innovación para la Experiencia del Cliente
| dc.contributor.advisor | Alba, Miguel Antonio | |
| dc.contributor.author | Grisales, Laura Vanessa | |
| dc.contributor.author | Ortiz, Laura Camila | |
| dc.coverage.spatial | Bogotá | spa |
| dc.creator.email | lauraortizarte2023@gmail.com | spa |
| dc.date.accessioned | 2025-04-21T13:18:52Z | |
| dc.date.available | 2025-04-21T13:18:52Z | |
| dc.date.created | 2025-04-12 | |
| dc.description.abstract | El objetivo de este artículo fue analizar cómo la inteligencia artificial (IA) se puede aplicar en la innovación para mejorar la experiencia del cliente en diversos sectores. Este trabajo parte del problema del creciente desafío que enfrentan las empresas para satisfacer las expectativas de los clientes en un entorno competitivo y digitalizado. Se buscó identificar herramientas y enfoques de IA que permitan personalizar la experiencia del cliente, optimizar los procesos de interacción y generar lealtad. Metodológicamente, se realizó una revisión bibliográfica de teorías relacionadas con la innovación tecnológica y el comportamiento del consumidor, además de normas internacionales como ISO 9001:2015 sobre gestión de calidad. Se recopilaron estudios de casos y se empleó un enfoque cualitativo para analizar el impacto de herramientas de IA, como chatbots, análisis predictivo y motores de recomendación, en la experiencia del cliente. Los resultados muestran que la implementación de la IA permite una interacción más eficiente y personalizada, mejorando los tiempos de respuesta y aumentando la satisfacción del cliente. Por ejemplo, empresas como Amazon han utilizado algoritmos de recomendación que han incrementado significativamente sus ventas. Se concluyó que, aunque la IA ofrece múltiples beneficios, su implementación debe ir acompañada de una estrategia ética y centrada en el cliente para maximizar resultados y minimizar riesgos como la invasión de privacidad. | spa |
| dc.description.abstractenglish | The objective of this article was to analyze how artificial intelligence (AI) can be applied in innovation to improve customer experience across various sectors. This work addresses the growing challenge companies face in meeting customer expectations in a competitive and digitalized environment. The aim was to identify AI tools and approaches that allow for personalizing the customer experience, optimizing interaction processes, and building loyalty. Methodologically, a literature review was conducted of theories related to technological innovation and consumer behavior, as well as international standards such as ISO 9001:2015 on quality management. Case studies were compiled, and a qualitative approach was used to analyze the impact of AI tools, such as chatbots, predictive analytics, and recommendation engines, on customer experience. The results show that implementing AI enables more efficient and personalized interactions, improving response times and increasing customer satisfaction. For example, companies like Amazon have used recommendation algorithms that have significantly increased their sales. It was concluded that, although AI offers multiple benefits, its implementation must be accompanied by an ethical and customer-centric strategy to maximize results and minimize risks such as privacy invasion. | spa |
| dc.description.sponsorship | Universidad Libre -- Economía, Administración, Contaduría y Afines -- Negocios Internacionales | spa |
| dc.format | spa | |
| dc.identifier.uri | https://hdl.handle.net/10901/30983 | |
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| dc.relation.references | Chui, M., Manyika, J., & Miremadi, M. (2018). Where machines could replace humans—and where they can’t (yet). McKinsey Quarterly. https://www.mckinsey.com/featured-insights/artificial-intelligence/where-machines-could-replace-humans-and-where-they-cant-yet | spa |
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| dc.relation.references | Huang, M.-H., & Rust, R. T. (2020). A strategic framework for artificial intelligence in marketing. Journal of the Academy of Marketing Science, 48(1), 30-50. https://doi.org/10.1007/s11747-019-00696-0 | spa |
| dc.relation.references | Lemon, K. N., & Verhoef, P. C. (2016). Understanding customer experience throughout the customer journey. Journal of Marketing, 80(6), 69-96. https://doi.org/10.1509/jm.15.0420 | spa |
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| dc.relation.references | Salesforce. (2021). State of the connected customer: Fourth edition. Salesforce Research. https://www.salesforce.com | spa |
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| dc.relation.references | Tuzovic, S., & Paluch, S. (2018). Chatbots—A next generation of virtual personal assistants in customer service. In Proceedings of the International Conference on Information Systems (pp. 6-9). | spa |
| dc.relation.references | West, S. M., & Allen, J. R. (2018). Ethically aligned design: A vision for prioritizing human well-being with autonomous and intelligent systems. IEEE. https://mktefa.ditrendia.es/blog/estadisticas-ia | spa |
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| dc.rights.accessrights | info:eu-repo/semantics/openAccess | spa |
| dc.rights.coar | http://purl.org/coar/access_right/c_abf2 | spa |
| dc.rights.license | Atribución-NoComercial-SinDerivadas 2.5 Colombia | spa |
| dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/2.5/co/ | spa |
| dc.subject | Inteligencia artificial | spa |
| dc.subject | Innovación | spa |
| dc.subject | Experiencia del cliente | spa |
| dc.subject.lemb | Servicio al cliente - Control de calidad | spa |
| dc.subject.lemb | Inteligencia artificial - Aspectos sociales | spa |
| dc.subject.subjectenglish | Artificial intelligence | spa |
| dc.subject.subjectenglish | Customer experience | spa |
| dc.title | La Inteligencia Artificial aplicada en la Innovación para la Experiencia del Cliente | spa |
| dc.type.coar | http://purl.org/coar/resource_type/c_7a1f | spa |
| dc.type.driver | info:eu-repo/semantics/bachelorThesis | spa |
| dc.type.hasversion | info:eu-repo/semantics/acceptedVersion | spa |
| dc.type.local | Tesis de Pregrado | spa |
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