The digital-intelligent transformation of educational publishing constitutes a systemic reconstruction across legal, ethical, organizational, and technological dimensions. This study addresses the core dilemma confronting K–12 educational publishing institutions: leveraging data-driven approaches to deliver precise and personalized educational services while rigorously safeguarding the privacy of minors—a legally protected category of "sensitive personal information." Employing a "Problem-Attribution-Solution" analytical framework, the research conducts a systematic investigation. By integrating textual analysis of key legal provisions (such as China' s Personal Information Protection Law and Minors Protection Law), scrutiny of industry practices, and feasibility assessments of emerging privacy-enhancing technologies and service models, this paper moves beyond superficial descriptions to provide an in-depth, multi-faceted analysis. The study first delineates the concrete manifestations of this dilemma, revealing inherent conflicts between the scope of data collection and the minimum necessity principle, between deep data utilization and the purpose limitation principle, between rising technical compliance costs and unsustainable profit models, and between agile business development and rigorous compliance procedures. It then diagnoses three critical capability gaps within publishing institutions that underlie these conflicts: (1) an "easier said than done" gap in legal cognition, wherein abstract principles fail to translate into operational rules; (2) a significant technical capability deficit, where legacy systems and the absence of robust data governance frameworks impede secure data handling and the adoption of Privacy-Enhancing Technologies (PETs); and (3) a management system void, characterized by the absence of dedicated roles, comprehensive internal policies, and inadequate oversight of third-party partners. As the core outcome, this paper constructs and elaborates a novel, integrated "Management-Technology-Content" trinity governance framework as a strategic pathway forward—one that embeds the "Privacy by Design (PbD)" principle, a core tenet emphasized in the research, into the entire digital-intelligent transformation process. This framework advocates for proactive, systemic change: Management-wise, it proposes establishing a privacy-first governance architecture with dedicated leadership (e.g., a Data Protection Officer), clear internal ethical guidelines, full-lifecycle data policies, and user-friendly transparency mechanisms. Technology-wise, it evaluates the deployment and application of key PETs—including data masking, strict anonymization, federated learning, and differential privacy—analyzing their operational mechanics, suitability for educational scenarios, and inherent trade-offs. Content-wise, it pioneers a paradigm shift toward service models with low dependency on sensitive personal data, such as modular "knowledge components" libraries for user-led navigation, explicit interactive feedback replacing implicit behavioral monitoring, context-aware marketing based on group trends, and exploration of "data trusteeship" collaborations with authorized third-party platforms. This research concludes that sustainable transformation requires a fundamental rethinking of data value—shifting from exploiting data for predictive control to utilizing it to support learner autonomy and educational equity. The proposed holistic framework aims to provide a theoretically grounded and practically actionable guide for educational publishers to navigate the dual imperatives of innovation and compliance, thereby fostering a responsible, trustworthy, and ethically sound ecosystem for digital-intelligent development in education. The findings underscore that the future lies not in deeper data mining but in building respectful, low-dependency, and trustworthy service paradigms.