PulseExploreJournal ClubDebatesTrendingResearchersJournals
Instagram
HomeExploreJournal ClubTrending
Synapse
⌘+K
Synapse
April 14, 2026Journal of Engineering and Technology Management1 citationsOpen Access

From optimization to disruption: The role of AI-driven innovation in shaping firms’ market competitiveness

View Full Paper
JXJiawei XuBZBing ZhangHLHaohui Li

Key Points

  • This study aims to investigate how AI-driven innovation influences market competitiveness, focusing on its disruptive potential.
  • Used regression analysis to assess the impact of AI-driven radical versus incremental innovations.
  • Analyzed the effects in various industry contexts, particularly in concentrated and non-technology-intensive sectors.
  • Evaluated mechanisms such as media attention and financial constraints influencing innovation outcomes.
  • AI-driven radical innovation leads to greater market competitiveness than incremental innovation.
  • Effects are more prominent in industries with low technology intensity.
  • Positive media attention, reduced financial constraints, and lower cost stickiness enhance the benefits of AI-driven innovation.

Abstract

Firms increasingly invest in artificial intelligence(AI) to enhance market adaptability. Although prior research reveals AI’s optimization potential, whether AI-driven innovation generates disruption remains unclear. This study examines the mechanisms linking AI-driven innovation to market competitiveness. The regression results indicate that AI-driven radical innovation exerts a stronger effect than incremental innovation, highlighting a shift in the role of AI from optimization toward disruption. AI-driven innovation demonstrates stronger effects in concentrated, non–technology-intensive industries and operates through positive media attention, alleviated financial constraints, and reduced cost stickiness. Our findings imply that managers should balance AI-driven radical and incremental innovation portfolios with industry context.

Ask AI
Helpful
Bookmark
Share
View Full Paper

Cite This Study

Xu et al. (2026) studied this question.

synapsesocial.com/papers/69ddd8eee195c95cdefd6782https://doi.org/10.1016/j.jengtecman.2026.101962
Ask AI
Helpful
Bookmark
Share
View Full Paper