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As AI becomes a core driver of enterprise transformation, traditional organizations face challenges such as rigid structures, data fragmentation, and outdated evaluation models. Existing digital transformation maturity models focus primarily on IT infrastructure and industrial-era processes, lacking a comprehensive framework for evaluating AI effectiveness. To address this gap, this paper proposes the IMPRESSIVE Enterprise Framework, which defines ten critical capabilities for AI-powered organizations: Innovation, Machine Learning, Personalization, Reliability, Enhanced Experience, Scalability, Security, Integrated Ecosystem, Value-Driven Culture, and Efficiency. Derived from this framework, the IMPRESSIVE Maturity Assessment Model (IMAM) is developed as a quantitative tool to measure AI maturity across these dimensions. Validation through case studies demonstrates IMAM’s applicability in identifying strengths, gaps, and strategic pathways for enterprises transitioning to AI-native operations. This research contributes a holistic framework to guide organizations in systematically navigating AI transformation, bridging the gap between theoretical insights and actionable practice.

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IMPRESSIVE: An AI Enterprise Model and Maturity Assessment Framework for Intelligent Transformation

  • 会议论文

  • 发表日期：

    2026年

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  • Jiawei Dang,
  • Huan Chen,
  • Sheng He,
  • Hongbo Huang,
  • Liang-Jie Zhang

摘要

As AI becomes a core driver of enterprise transformation, traditional organizations face challenges such as rigid structures, data fragmentation, and outdated evaluation models. Existing digital transformation maturity models focus primarily on IT infrastructure and industrial-era processes, lacking a comprehensive framework for evaluating AI effectiveness. To address this gap, this paper proposes the IMPRESSIVE Enterprise Framework, which defines ten critical capabilities for AI-powered organizations: Innovation, Machine Learning, Personalization, Reliability, Enhanced Experience, Scalability, Security, Integrated Ecosystem, Value-Driven Culture, and Efficiency. Derived from this framework, the IMPRESSIVE Maturity Assessment Model (IMAM) is developed as a quantitative tool to measure AI maturity across these dimensions. Validation through case studies demonstrates IMAM’s applicability in identifying strengths, gaps, and strategic pathways for enterprises transitioning to AI-native operations. This research contributes a holistic framework to guide organizations in systematically navigating AI transformation, bridging the gap between theoretical insights and actionable practice.