Amidst the wave of artificial intelligence (AI)-driven industrial transformation, the publishing sector is undergoing profound ecological restructuring encompassing production models, service formats, and value logic. Generative artificial intelligence (GenAI) has deeply permeated the publishing industry, exhibiting a marked duality: on the one hand, it has catalyzed innovative product forms such as AI-enhanced e-books, intelligent adaptive textbooks, conversational knowledge bases, and interactive academic papers, propelling the intelligent upgrading of the entire publishing production and service process; on the other hand, it has exposed structural challenges such as lagging data governance mechanisms, prohibitively high technological application costs, and inadequate compatibility between traditional publishing workflows and intelligent technologies. Grounded in the practical demands of the publishing industry's digital transformation, this paper systematically explores effective pathways for reshaping the sector's competitiveness through generative AI empowerment. To address the three intrinsic predicaments confronting generative AI in publishing—the "universality" of technical tools erasing application specificity within publishing scenarios, the "explicit knowledge" within algorithmic cores constraining the innovative transformation of publishing knowledge, and the inherent "knowledge myopia" of models weakening deep content comprehension—this paper posits that "contextualization" represents the pivotal trend and core breakthrough strategy for the publishing industry to overcome developmental bottlenecks and achieve high-quality growth in the AI era. Drawing upon situational cognition theory, this paper contends that knowledge is not an abstract symbol detached from context, but rather a dynamic process embedded within specific practices, social interactions, and physical environments. The generation, application, and comprehension of knowledge must rely upon particular contexts (such as socio-cultural backgrounds and practical tasks); knowledge divorced from its context becomes hollow. Consequently, as publishing enterprises evolve from content providers to knowledge service providers, contextualization becomes a core element of this transformation. Publishing enterprises must establish a closed-loop ecosystem under GenAI that encompasses "perceiving context—understanding users—dynamically adapting content." By precisely capturing content demands, deeply analyzing user preferences, and intelligently matching dynamic content, they can systematically enhance AI's operational efficiency and applied value throughout the publishing workflow, thereby achieving profound optimization and sustainable development of knowledge services. Publishing enterprises urgently require guidance from contextual cognition theory to deeply embed GenAI technology within their production value chains. This enables a strategic shift from product-centricity to value co-creation, involving the cultivation of consumption contexts, the refinement of production contexts, and the forging of knowledge contexts. Therefore, sustainable competitive advantages can be established within the digital knowledge service ecosystem. The competitive essence of publishing in the AI era lies not in the pursuit of technology itself, but in the ability to define and operate within "contexts". By deeply integrating general-purpose technologies into unique contextual frameworks, the publishing industry can transform challenges into opportunities, thereby achieving a strategic leap from traditional content production to modern knowledge services and ecosystem-level innovation.