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Digital Innovation in Generative AI Ecosystems: An Actor-Network Perspective
Mohammad Qorbani Hesari, Arman Sadreddin
Digital innovation through artificial intelligence (AI) has traditionally been considered a costly endeavor. The development, training, and deployment of AI models typically require advanced technical resources and a high level of expertise. However, with the advent of generative AI, these barriers are being broken down, enabling individuals to innovate with AI through simple conversations. This transformation has the potential to reshape the digital innovation landscape. Thus, it is crucial to understand how the future may be impacted. By adopting actor-network theory and situational analysis, this study aims to explain how humans and machines can collaboratively create situations that contribute to the emergence of digital innovation. In particular, this study looks at AI as a counterpart in digital innovation and investigates the OpenAI ecosystem with a special focus on ChatGPT. Our findings suggest that human actors and ChatGPT collaboratively create two reinforcing processes of inscription and translation nourishing digital innovation.

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