Artificial intelligence as a catalyst for sustainable business innovation: Perspectives from finance and marketing

Bartelt, Cedric és Röser, Alexander Maximilian (2024) Artificial intelligence as a catalyst for sustainable business innovation: Perspectives from finance and marketing. GAZDASÁG ÉS TÁRSADALOM, 35 (2). pp. 37-65. ISSN 0865-7823

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Artificial Intelligence (AI) has emerged as a transformative force driving sustainable business innovation across various sectors, particularly in finance and marketing. This study conducted a comprehensive meta-analysis of existing research to explore the role of AI as a catalyst for sustainable practices and digital transformation. This methodology entails a comprehensive literature search across multiple databases with a focus on the nexus of AI, sustainability, and business model innovation. The study underscores the significance of digital transformation in the context of sustainable business models, underscoring the necessity for strategic integration of technology, business model reengineering, and organizational structure optimization. The potential of AI technologies, including Machine Learning (ML), neural networks, and generative AI, to enhance sustainability efforts and drive innovation is also discussed. Furthermore, this study examines the challenges and opportunities associated with the adoption of AI in the fields of finance and marketing, considering factors such as data quality, ethical considerations, and organizational readiness. By providing in-sights into the sustainable utilization of AI technologies, this study contributes to the understanding of how AI can facilitate digital transformation and promote long-term value crea-tion in finance and marketing.

Tudományterület / tudományág

társadalomtudományok > gazdálkodás- és szervezéstudományok
társadalomtudományok > közgazdaságtudományok

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Mű tipusa:	Cikk
SWORD Depositor:	Teszt Sword
Felhasználó:	Csaba Horváth
A mű MTMT azonosítója:	MTMT:35643371
Dátum:	05 Feb 2025 08:25
Utolsó módosítás:	05 Feb 2025 08:25
URI:	http://publicatio.uni-sopron.hu/id/eprint/3452

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