Toward the sixth generation of digital transformation: from generative intelligence to inferential intelligence

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• Semantic Scholar2026-07-28 07:16:04
  Toward the sixth generation of digital transformation: from generative intelligence to inferential intelligence

  Digital transformation has evolved through successive stages over the past decades, progressing from digitization and digitalization toward intelligent, AI-enabled organizational ecosystems. Recent advances in Generative Artificial Intelligence (GenAI) have significantly expanded the capabilities of digital systems in content generation, decision support, and organizational productivity. Nevertheless, existing digital transformation frameworks continue to emphasize automation, operational efficiency, predictive analytics, and optimization, while comparatively limited attention has been devoted to the role of artificial intelligence in scientific reasoning, hypothesis generation, theory development, and the systematic creation of new knowledge (Vial, 2019; Verhoef et al., 2021; Hanelt et al., 2021). This paper proposes the concept of the Sixth Generation of Digital Transformation (6GDT) as a new conceptual paradigm centered on the emergence of Inferential Intelligence. Unlike Generative AI, which primarily produces new content by learning statistical patterns from existing data, Inferential Intelligence is defined as the capability to generate scientific hypotheses, identify hidden relationships, support causal reasoning, facilitate theory formation, and promote collaborative human–AI knowledge discovery. Building upon the theoretical principles of Neo-Inference Science (NIS), the proposed framework reconceptualizes artificial intelligence as an inferential collaborator that augments scientific inquiry rather than functioning solely as a computational or generative assistant (Pearl & Mackenzie, 2018; Gil et al., 2014; Dellermann et al., 2019).To operationalize this paradigm, the paper develops a six-layer conceptual architecture integrating Data and Reality, Cognitive AI, Inferential Intelligence, Human–AI Co-Discovery, Knowledge and Theory Formation, and Recursive Knowledge Evolution. The applicability of the framework is illustrated through three representative domains: Sixth-Generation Universities (6GU), Sixth-Generation Economy (6GE), and Sixth-Generation Transportation (6GT). These examples demonstrate how inferential intelligence may reshape higher education, economic systems, and intelligent mobility by extending digital transformation beyond automation toward scientific discovery and continuous knowledge creation.Rather than viewing digital transformation solely as the optimization of organizational processes, this study conceptualizes its next evolutionary stage as the digital transformation of scientific reasoning, collaborative discovery, and knowledge generation. The proposed framework establishes a theoretical foundation for future conceptual and empirical research on inferential artificial intelligence, human–AI collaboration, and the evolution of next-generation knowledge ecosystems.