This research-in-progress paper investigates the impact of Large Language Models (LLMs) on Digital Transformation (DT) across various industries, highlighting a paradigm shift in software customization and integration. Utilizing a mixed-methods approach, the study combines qualitative case studies and Qualitative Comparative Analysis (QCA) to explore the transformative effects of LLMs in business environments. Key findings reveal that LLMs significantly enhance customization capabilities, streamline data integration, and promote agile decision-making processes. This transition marks a critical evolution in DT strategies, offering new opportunities for operational efficiency and competitive advantage. The paper contributes vital insights to both academic discourse in technology management and practical business strategy, emphasizing the increasingly central role of LLMs in the digital-first business landscape.

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Is Software Customization an Impediment or Enabler for Digital Transformation in the Era of Large Language Models

  • Govindarajan Narayanan,
  • Rahul Kharat,
  • Abhishek Kathuria

摘要

This research-in-progress paper investigates the impact of Large Language Models (LLMs) on Digital Transformation (DT) across various industries, highlighting a paradigm shift in software customization and integration. Utilizing a mixed-methods approach, the study combines qualitative case studies and Qualitative Comparative Analysis (QCA) to explore the transformative effects of LLMs in business environments. Key findings reveal that LLMs significantly enhance customization capabilities, streamline data integration, and promote agile decision-making processes. This transition marks a critical evolution in DT strategies, offering new opportunities for operational efficiency and competitive advantage. The paper contributes vital insights to both academic discourse in technology management and practical business strategy, emphasizing the increasingly central role of LLMs in the digital-first business landscape.