Currently, artificial intelligence (AI) is comprehensively integrated into the entire process of academic journal publishing, spanning the full lifecycle from content production to distribution While AI-generated content enhances the quality and efficiency of publishing, it also raises concerns about the authenticity of knowledge production and the order of dissemination, triggering issues such as "AI hallucinations" and academic ethics conflicts, thereby threatening the construction of a trustworthy academic ecosystem. Based on resilience theory, this paper examines the AI-enhanced academic journal publishing scenario, analyzes the generative mechanisms of technological risks and governance dilemmas, and systematically argues for the logical shift and comprehensive framework of applying resilience governance to resolve the paradox of risk in intelligent transformation. It aims to propose strategies for translating AI governance from universal standards to specifically industry-adapted implementation.

The research process consists of four parts: first, introducing resilience theory to explain the logical transition mechanism in risk governance for academic journal publishing; second, examining AI intervention scenarios to dissecct the generative mechanisms of complex risks; third, analyzing the new characteristics of technological risks generated by AI intervention to reveal the practical dilemmas faced by academic journal publishing risk governance; finally, constructing a resilience governance framework to propose concrete governance strategies covering the three dimensions: subject, path, and goal.

The findings indicate that with the evolution of the resilience theory paradigm, academic journal publishing must actively adjust their risk governance logic across three dimensions: chronological order, structural organization, and goal alignment. AI has introduced complex risk matrix into various scenarios, such as content creation, peer review, editing and proofreading, and distrubution. These risks stem from profound contradictions between technological logic and the core humanistic academic values, presenting new characteristics such as multi-agent interest correlation, dynamic technological iteration, and network diffusion, leading to governance dilemmas characterized by ambiguous responsibilities, outdated methods, and systemic conflicts. Faced with complex environments of disruptive technoloical shocks, the academic journal publishing system must maintain its core functions — such as academic integrity and knowledge dissemination — through internal multi-agent collaboration, continuous learning-feedback mechanisms, and global institutional design. This allows the system to actively achieve optimization and transformation, completing resilience governance under AI intervention.

Based on the analysis, this paper advocates constructing a resilience governance framework centered on "multi-agent co-governance — adaptive learning — systemic adjustment." Specific resilience governance strategies are proposed to address risks associated with academic journal publishing: in terms of governance subjects, implementing the logic of multi-agent co-governance, improving a hierarchical responsibility mechanism, and building a collaborative governance community to address the question of "who governs"; In terms of governance methods, following adaptive learning logic to agilely sense technical risks and establish dynamic governance cycles to overcome the challenge of "how to govern"; In terms of governance goals, implementing systemic adaptation logic to construct a resilience interconnection framework, guiding beneficial technological trajectories, and realizing the functional optimization of the academic journal publishing system to clarify the ultimate foothold of "what governance is for".