From a Data-Driven to Information-Driven Management Paradigm: Reflections on Generative AI and Intellectual Capital Management

Henri Hussinki () and Josh Morton ()
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Henri Hussinki: Lappeenranta-Lahti University of Technology LUT
Josh Morton: University of Leeds

A chapter in Futurizing Intellectual Capital, 2025, pp 201-217 from Springer

Abstract: Abstract This chapter explores the emergence and transformative impact of generative artificial intelligence (Gen AI) on organizational intellectual capital (IC) management and the shift from a data-driven to an information-driven management paradigm. It contributes to future IC research and practice by outlining several implications that Gen AI will have on an organization’s IC management. First, regarding human capital, it challenges organizations to develop and retain a specific breed of information engineering experts, sets demand for personnel reskilling including prompt engineering, and emphasizes the central role of collaboration between technical Gen AI experts and domain experts. Second, the chapter argues that organizations must pay attention to certain facets of their structural capital, including the controlled generation of new information through established business processes and the design and maintenance of adaptable information systems. Further, there is a need for an information-driven culture, which drives the utilization of Gen AI outputs in practice. Third, it emphasizes an increasing need to augment an organization’s proprietary information with extra-organizational information, as higher volumes of complementary information improve Gen AI performance. This development will lead to a market of commercialized information products, where organizations may operate as clients and providers or participate through different networks and ecosystems.

Keywords: Generative AI; Intellectual capital; IC management; Data-driven paradigm; Information-driven paradigm (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:spr:kmochp:978-3-031-80197-6_11

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DOI: 10.1007/978-3-031-80197-6_11

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