Construction of a High-Quality Development Model for Regional Digital Economy Driven by Artificial Intelligence: An Analysis From the Perspective of Information Resources Management

Effectively managing data as a core information resource is critical as the digital economy shifts from demographic to data dividends. While existing literature emphasizes artificial intelligence's (AI's) substitution effect, it overlooks how AI activates data factors. Positioning AI as a key tool for information resource management, this paper constructs an integrated framework of micro-level factor activation, meso-level friction reduction, and macro-level spatial reconstruction. Using panel data from 285 Chinese cities (2013–2023) and spatial Durbin model with dynamic effects, the following was found: (1) AI nonlinearly enhances data factors' output elasticity, confirming its activation effect on information resources; (2) a real economy threshold (S∗ = 0.342) exists—below it, AI cannot reduce industrial information friction; and (3) virtual agglomeration substitutes for geographic distance, revealing digital gravity's role in reshaping regional economies. Three differentiated models—factor activation, friction reduction, and cloud collaboration—are proposed to help regions maximize value from their information resources.