AI capabilities and entrepreneurial outcomes in high-tech ventures: exploring the (in)congruent role of innovation ambidexterity

Purpose This study examines how artificial intelligence (AI) capabilities influence innovation ambidexterity, comprising exploratory and exploitative innovation, and how these innovation strategies contribute to business model transformation and key entrepreneurial outcomes, including new venture performance and entrepreneurial resilience. Design/methodology/approach A three-wave longitudinal survey of 218 high-tech entrepreneurial ventures in Vietnam was conducted. Polynomial regression and response surface analysis were used to test a temporally ordered process model grounded in the dynamic capabilities framework. Findings The results indicate that AI capabilities significantly enhance both exploratory and exploitative innovation. These innovation types independently and jointly foster business model transformation. Bootstrapping results are consistent with indirect relationships from AI capabilities to entrepreneurial outcomes through exploratory innovation, exploitative innovation, and business model transformation. The response surface results further show that when exploratory and exploitative innovation increase together, business model transformation improves in a positive and largely additive manner. By contrast, incongruence between the two innovation modes does not exhibit a strong detrimental effect, although a small directional effect is observed. Practical implications The findings provide practical guidance for entrepreneurs and managers on integrating AI into organizational routines and reinforcing both exploratory and exploitative innovation, and remaining agile in adapting business models to seize new opportunities and withstand external shocks. Originality/value This study contributes to research on AI and entrepreneurship by showing how AI capabilities activate dual innovation pathways and by clarifying that the configurational effect of innovation ambidexterity on business model transformation is mainly additive, while the effect of incongruence is weak and directional rather than strongly penalizing.

Authors

Institutions

Publication Details

Journal
Industrial Management & Data Systems
Published
2026-08-26
DOI
https://doi.org/10.1108/imds-07-2025-1051
Primary Topic
Innovation and Knowledge Management
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

AI capabilities and entrepreneurial outcomes in high-tech ventures: exploring the (in)congruent role of innovation ambidexterity

Cong Doanh Duong
Industrial Management & Data Systems
Innovation and Knowledge Management
article

AI capabilities and entrepreneurial outcomes in high-tech ventures: exploring the (in)congruent role of innovation ambidexterity

Cong Doanh Duong
article en

Abstract

Purpose This study examines how artificial intelligence (AI) capabilities influence innovation ambidexterity, comprising exploratory and exploitative innovation, and how these innovation strategies contribute to business model transformation and key entrepreneurial outcomes, including new venture performance and entrepreneurial resilience. Design/methodology/approach A three-wave longitudinal survey of 218 high-tech entrepreneurial ventures in Vietnam was conducted. Polynomial regression and response surface analysis were used to test a temporally ordered process model grounded in the dynamic capabilities framework. Findings The results indicate that AI capabilities significantly enhance both exploratory and exploitative innovation. These innovation types independently and jointly foster business model transformation. Bootstrapping results are consistent with indirect relationships from AI capabilities to entrepreneurial outcomes through exploratory innovation, exploitative innovation, and business model transformation. The response surface results further show that when exploratory and exploitative innovation increase together, business model transformation improves in a positive and largely additive manner. By contrast, incongruence between the two innovation modes does not exhibit a strong detrimental effect, although a small directional effect is observed. Practical implications The findings provide practical guidance for entrepreneurs and managers on integrating AI into organizational routines and reinforcing both exploratory and exploitative innovation, and remaining agile in adapting business models to seize new opportunities and withstand external shocks. Originality/value This study contributes to research on AI and entrepreneurship by showing how AI capabilities activate dual innovation pathways and by clarifying that the configurational effect of innovation ambidexterity on business model transformation is mainly additive, while the effect of incongruence is weak and directional rather than strongly penalizing.

Industrial Management & Data Systems
National Economics University (VN)
Decent work and economic growth
Openalex Percentile: Top 7%
Innovation and Knowledge Management
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

AI capabilities and entrepreneurial outcomes in high-tech ventures: exploring the (in)congruent role of innovation ambidexterity — Cong Doanh Duong · Industrial Management & Data Systems (2026) | TGRS Research Map | TGRS