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

Year: 2026

Type: article

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.

Source: Journal of Engineering and Technology Management

DOI: 10.1016/j.jengtecman.2026.101962

Authors: Jiawei Xu, Baofeng Zhang, Haohui Li, Jianjun Lu, Yubing Yu

Institutions: China Agricultural University, Ningbo University, Zhejiang Wanli University

Language: English

Topic: Firm Innovation and Growth

Subfield: Economics and Econometrics

Field: Economics, Econometrics and Finance

Domain: Social Sciences

SDGs: Industry, innovation and infrastructure, Decent work and economic growth

Open Access status: hybrid

Estimated APC paid: $2,630