This paper uses both bibliometric analysis and a systematic literature review to investigate the effects of generative AI on marketing strategies with respect to Adoption, Impact, and Ethical Considerations. The study also covers several objectives linked to content production, consumer interactions, and targeted marketing that are supported by complex artificial intelligence (AI) strategies and big data. The authors have demonstrated that using generative AI in marketing increases efficiency by facilitating and personalizing consumer interactions. However, there are certain ethical challenges associated with this use of generative AI in marketing, including abuses of consumer privacy, the need to explain algorithms, and biased decision-making. It emphasizes the need for an appropriate ethical framework and clear policies regarding the use of data to protect consumer interests and boost user confidence in AI-enabled marketing solutions. Moreover, this study develops an extensive approach for incorporating generative AI into marketing initiatives. To prevent misuse of the applications, this framework emphasizes how crucial it is to make sure AI systems adhere to ethical standards and the law. Additionally, practical examples of this integration's applications are provided to show how AI can transform marketing by giving real-time access to consumer data, improving the customer journey, and applying targeted marketing strategies based on consumer needs. Also, suggestions for future research are provided to look into the potential impacts of AI marketing applications on consumer behavior, brand values, and future markets. To uncover the patterns of consumers' perceptions of ongoing AI interactions and the effects of advertising over time, more research is necessary. Without ignoring the ethical concerns of the application, this study aims to add a theoretical and innovative perspective to the topic of literature on the application of generative artificial intelligence in marketing.
This paper uses both bibliometric analysis and a systematic literature review to investigate the effects of generative AI on marketing strategies with respect to Adoption, Impact, and Ethical Considerations. The study also covers several objectives linked to content production, consumer interactions, and targeted marketing that are supported by complex artificial intelligence (AI) strategies and big data. The authors have demonstrated that using generative AI in marketing increases efficiency by facilitating and personalizing consumer interactions. However, there are certain ethical challenges associated with this use of generative AI in marketing, including abuses of consumer privacy, the need to explain algorithms, and biased decision-making. It emphasizes the need for an appropriate ethical framework and clear policies regarding the use of data to protect consumer interests and boost user confidence in AI-enabled marketing solutions. Moreover, this study develops an extensive approach for incorporating generative AI into marketing initiatives. To prevent misuse of the applications, this framework emphasizes how crucial it is to make sure AI systems adhere to ethical standards and the law. Additionally, practical examples of this integration's applications are provided to show how AI can transform marketing by giving real-time access to consumer data, improving the customer journey, and applying targeted marketing strategies based on consumer needs. Also, suggestions for future research are provided to look into the potential impacts of AI marketing applications on consumer behavior, brand values, and future markets. To uncover the patterns of consumers' perceptions of ongoing AI interactions and the effects of advertising over time, more research is necessary. Without ignoring the ethical concerns of the application, this study aims to add a theoretical and innovative perspective to the topic of literature on the application of generative artificial intelligence in marketing.
Bibliographic Research: Generative AI in Marketing
DADKHAH TEHRANI, ZAHRA
2023/2024
Abstract
This paper uses both bibliometric analysis and a systematic literature review to investigate the effects of generative AI on marketing strategies with respect to Adoption, Impact, and Ethical Considerations. The study also covers several objectives linked to content production, consumer interactions, and targeted marketing that are supported by complex artificial intelligence (AI) strategies and big data. The authors have demonstrated that using generative AI in marketing increases efficiency by facilitating and personalizing consumer interactions. However, there are certain ethical challenges associated with this use of generative AI in marketing, including abuses of consumer privacy, the need to explain algorithms, and biased decision-making. It emphasizes the need for an appropriate ethical framework and clear policies regarding the use of data to protect consumer interests and boost user confidence in AI-enabled marketing solutions. Moreover, this study develops an extensive approach for incorporating generative AI into marketing initiatives. To prevent misuse of the applications, this framework emphasizes how crucial it is to make sure AI systems adhere to ethical standards and the law. Additionally, practical examples of this integration's applications are provided to show how AI can transform marketing by giving real-time access to consumer data, improving the customer journey, and applying targeted marketing strategies based on consumer needs. Also, suggestions for future research are provided to look into the potential impacts of AI marketing applications on consumer behavior, brand values, and future markets. To uncover the patterns of consumers' perceptions of ongoing AI interactions and the effects of advertising over time, more research is necessary. Without ignoring the ethical concerns of the application, this study aims to add a theoretical and innovative perspective to the topic of literature on the application of generative artificial intelligence in marketing.File | Dimensione | Formato | |
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Zahra Dadkhah Tehrani - Generative AI in Marketing.pdf
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https://hdl.handle.net/20.500.12608/68693