Jacob R. Holm, Daniel S. Hain, Roman Jurowetzki, Edward Lorenz
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We also discuss the merits of AI as a general purpose technology and argue that conclusions about AI in relation to innovation dynamics are likely to change when generative AI is widely adopted.KEYWORDS: Artificial intelligenceinnovation dynamicsinnovation processinnovation collaborationorganisational changeJEL CLASSIFICATION: O31O33O36 Disclosure statementNo potential conflict of interest was reported by the author(s).Notes1 The acronym ‘GPT’ is commonly used to represent both ‘general-purpose technology’ and ‘generative pretrained transformer’. The latter refers to the neural network architecture developed by OpenAI in 2018 that powers the ChatGPT system. Variants of the third generation and GPT-4 are used in this system, which was released in late 2022 and has sparked widespread discussion about AI among both mainstream audiences and academia. 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First, innovation using AI has unique dynamics that are characterised by data playing a central role and the increasing importance of external collaboration; however, data security and privacy issues also present new risks to external collaboration. When innovating in AI, collaboration with customers and competitors is critical, yet there are considerable risks associated with data sharing. Second, unique organisational challenges emerge during the diffusion of AI innovations, because adopting AI in an organisation not only results in the need for additional employee competencies but also challenges organisational power structures. 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Innovation dynamics in the age of artificial intelligence: introduction to the special issue
ABSTRACTIn this paper, we discuss the impact of artificial intelligence (AI) on innovation dynamics and argue that AI has affected innovation dynamics in at least two distinct ways. First, innovation using AI has unique dynamics that are characterised by data playing a central role and the increasing importance of external collaboration; however, data security and privacy issues also present new risks to external collaboration. When innovating in AI, collaboration with customers and competitors is critical, yet there are considerable risks associated with data sharing. Second, unique organisational challenges emerge during the diffusion of AI innovations, because adopting AI in an organisation not only results in the need for additional employee competencies but also challenges organisational power structures. We also discuss the merits of AI as a general purpose technology and argue that conclusions about AI in relation to innovation dynamics are likely to change when generative AI is widely adopted.KEYWORDS: Artificial intelligenceinnovation dynamicsinnovation processinnovation collaborationorganisational changeJEL CLASSIFICATION: O31O33O36 Disclosure statementNo potential conflict of interest was reported by the author(s).Notes1 The acronym ‘GPT’ is commonly used to represent both ‘general-purpose technology’ and ‘generative pretrained transformer’. The latter refers to the neural network architecture developed by OpenAI in 2018 that powers the ChatGPT system. Variants of the third generation and GPT-4 are used in this system, which was released in late 2022 and has sparked widespread discussion about AI among both mainstream audiences and academia. In this paper, ‘GPT’ represents ‘general-purpose technology’.
期刊介绍:
Industry and Innovation is an international refereed journal presenting high-quality original scholarship of the dynamics of industries and innovation. Interdisciplinary in nature, Industry and Innovation is informed by, and contributes in turn to, advancing the theoretical frontier within economics, organization theory, and economic geography. Theoretical issues encompass: •What are the institutional underpinnings for different organizational forms? •How are different industrial structures and institutions related to innovation patterns and economic performance?