Human-AI Collaboration and Innovation in Corporate Communication Models: A Study of Intelligent Transformation Based on University-Industry-Research Collaboration

This study investigates how human-AI collaboration reshapes corporate communication models within intelligent transformation, focusing on university–industry–research collaboration as an enabling mechanism. Drawing on qualitative case evidence and framework development, the paper identifies three collaborative modes-co-design, adaptive integration, and evaluative feedback-that mediate between AI capabilities and organizational communication innovation. The findings suggest that successful intelligent transformation depends less on technology adoption than on the institutional alignment of academic knowledge, industrial practice, and research-driven experimentation. Corporate communication evolves from linear information dissemination to dynamic stakeholder engagement, with human oversight and ethical judgment embedded in AI-supported workflows. The paper contributes a framework linking university–industry–research inputs, human-AI collaboration modes, and communication performance, and concludes with implications for policy and managerial practice.

Authors

Publication Details

Journal
Insights in computer, signals and systems.
Published
2026-10-26
DOI
https://doi.org/10.70088/t3f40r96
Primary Topic
University-Industry-Government Innovation Models
Type
article
Field-Weighted Citation Impact
0.00
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article

Human-AI Collaboration and Innovation in Corporate Communication Models: A Study of Intelligent Transformation Based on University-Industry-Research Collaboration

Danqing Wang
Insights in computer, signals and systems.
University-Industry-Government Innovation Models
article

Human-AI Collaboration and Innovation in Corporate Communication Models: A Study of Intelligent Transformation Based on University-Industry-Research Collaboration

Danqing Wang
article en

Abstract

This study investigates how human-AI collaboration reshapes corporate communication models within intelligent transformation, focusing on university–industry–research collaboration as an enabling mechanism. Drawing on qualitative case evidence and framework development, the paper identifies three collaborative modes-co-design, adaptive integration, and evaluative feedback-that mediate between AI capabilities and organizational communication innovation. The findings suggest that successful intelligent transformation depends less on technology adoption than on the institutional alignment of academic knowledge, industrial practice, and research-driven experimentation. Corporate communication evolves from linear information dissemination to dynamic stakeholder engagement, with human oversight and ethical judgment embedded in AI-supported workflows. The paper contributes a framework linking university–industry–research inputs, human-AI collaboration modes, and communication performance, and concludes with implications for policy and managerial practice.

Insights in computer, signals and systems.Vol. 3(5)
Openalex Percentile: Top 8%
University-Industry-Government Innovation Models
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