AI Reshaping Knowledge Management: Structural Transformation of Information Science and the Invisible Frontier of Urban Knowledge Ecosystems

In the flood of digitalization, Artificial Intelligence (AI) is no longer a distant science fiction concept; it has deeply permeated the fabric of digital media, information science, and even academic research. From natural language processing to computer vision, the rapid iteration of AI technologies is reshaping the underlying logic of information organization, knowledge retrieval, and dissemination at an unprecedented speed. However, when we examine the specific applications of AI in academic libraries, digital repositories, and publication management, a structural research gap is becoming increasingly apparent: despite AI demonstrating significant efficiency gains in metadata indexing, citation analysis, and recommendation systems, there is a lack of macro, mixed-method research into the impact of this technological integration on the entire knowledge ecosystem, especially in the critical fields of academic institutions and digital libraries.

Existing academic research often relies on bibliometric analysis to reveal research trends and knowledge hotspots, providing necessary tools for quantitatively defining research structures. However, this method focuses on "what" and "where," neglecting user experience, the dynamic evolution of knowledge dissemination processes, and the qualitative perceptions brought about by AI. Therefore, the current academic community urgently needs a more forward-looking research paradigm—combining dynamic text analysis with qualitative user sentiment analysis—to comprehensively grasp the impact of AI on digital knowledge management.

From the macro perspective of urban strategy and knowledge production, this technological transformation is far from an isolated academic phenomenon. As knowledge hubs and incubators for innovation, the efficiency of a city's knowledge infrastructure directly determines its position in global competition. When AI begins to drive the automated organization of knowledge, intelligent retrieval, and personalized recommendations, the functions of city libraries and digital archives will undergo a fundamental shift. They will no longer be mere warehouses for information but "smart hubs" for knowledge flow. Cities need to consider how to ensure equitable access to knowledge, maintain academic integrity, and mitigate potential biases and privacy risks brought by emerging technologies—issues directly related to the future form of urban knowledge governance.

Future research directions must move beyond the level of mere technical application to a deeper understanding of "human-AI collaboration." This not only requires building more transparent AI systems but also establishing interdisciplinary collaborative mechanisms, involving information science, humanities, and AI ethics in the design of knowledge systems. Only through this multidimensional research can we truly understand how AI evolves from a technical tool into a core governance element influencing civilization and spatial relationships.In short, the transformation brought about by AI in digital knowledge management is a profound structural reconstruction of the paradigm of knowledge production. For global cities, grasping the rhythm of this transition and formulating a forward-looking knowledge infrastructure strategy will determine their competitiveness in the global digital space and the pace of their civilization's evolution. This is not just a technological competition, but a long-term strategic game involving space, power, and wisdom.