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Artificial Intelligence and Corporate Localization: design of a pipeline for automation of digital marketing content – Case Study: FIAT (Stellantis Group), Italian Market

Melania Ascione

Artificial Intelligence and Corporate Localization: design of a pipeline for automation of digital marketing content – Case Study: FIAT (Stellantis Group), Italian Market.

Rel. Alessandro Simeone, Yuchen Fan. Politecnico di Torino, Corso di laurea magistrale in Ingegneria Gestionale, 2025

Abstract:

The thesis explores the possibility of collaboration between Artificial Intelligence and corporate localization, focusing on the design and implementation of an automated pipeline for digital marketing content. The proposed system integrates large language models, API-based workflows, and database-driven validation to manage translation, legal compliance, and stylistic consistency across markets. Developed in Python, the pipeline automates key localization tasks while maintaining human-in-the-loop supervision to ensure brand accuracy and contextual relevance. The case study on FIAT (Stellantis Group, Italy) demonstrates how localization with AI can enhance efficiency and governance without compromising on linguistic quality. Future work aims to expand scalability across brands, reduce human supervision, and optimize processing speed through semantic recognition and parallel execution.

Relatori: Alessandro Simeone, Yuchen Fan
Anno accademico: 2025/26
Tipo di pubblicazione: Elettronica
Numero di pagine: 157
Informazioni aggiuntive: Tesi secretata. Fulltext non presente
Soggetti:
Corso di laurea: Corso di laurea magistrale in Ingegneria Gestionale
Classe di laurea: Nuovo ordinamento > Laurea magistrale > LM-31 - INGEGNERIA GESTIONALE
Aziende collaboratrici: STELLANTIS EUROPE SPA
URI: http://webthesis.biblio.polito.it/id/eprint/38196
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