AI-driven learning culture enhances innovation performance: a serial mediator of knowledge orchestration and organisational intelligence

Purpose This paper aims to investigate how an artificial intelligence (AI)-driven learning culture (AIDLC) enhances innovation performance (IP) through the complementary roles of knowledge orchestration (KO) and organisational intelligence (OI). It addresses how organisations in an emerging economy context transform AI-enabled learning into intelligent action and innovation outcomes. Design/methodology/approach A quantitative, survey-based study was conducted with 348 professionals working in information technology firms in Karachi, Pakistan. Established scales were adapted to measure AIDLC, KO, OI and IP. Partial least squares structural equation modelling was used to test the hypothesised direct and indirect relationships and to assess the measurement and structural models. Findings The results show that AIDLC has a significant positive effect on KO, OI and IP. KO positively influences OI and IP, while OI positively affects IP. Furthermore, KO and OI each individually mediate the relationship between AIDLC and IP, and they also form a serial mediation path from AIDLC to IP. These findings indicate that AIDLC foster stronger KO capabilities and higher OI, which together explain improved IP. Practical implications Managers should invest in AI-enabled learning practices and systems that not only capture and analyse knowledge but also orchestrate it across teams and functions. Building OI capabilities is critical for converting AI-driven learning into sustained IP, especially in resource-constrained, emerging economy settings. Originality/value This study introduces and operationalises the construct of AIDLC and empirically demonstrates its impact on IP through KO and OI. By integrating dynamic capabilities, knowledge-based and organisational learning perspectives, it offers a novel serial mediation framework that explains how AI-enabled learning is transformed into OI and innovation in the IT industry of an emerging economy.

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Publication Details

Journal
VINE Journal of Information and Knowledge Management Systems
Published
2026-02-23
DOI
https://doi.org/10.1108/vjikms-12-2025-0527
Primary Topic
Organizational and Employee Performance
Type
article
Field-Weighted Citation Impact
0.00
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article

AI-driven learning culture enhances innovation performance: a serial mediator of knowledge orchestration and organisational intelligence

Rohit Bansal, Arman Khan, Zahid Hussain, Abdelrehim Awad
VINE Journal of Information and Knowledge Management Systems
Organizational and Employee Performance
article

AI-driven learning culture enhances innovation performance: a serial mediator of knowledge orchestration and organisational intelligence

Rohit Bansal, Arman Khan, Zahid Hussain, Abdelrehim Awad
article en

Abstract

Purpose This paper aims to investigate how an artificial intelligence (AI)-driven learning culture (AIDLC) enhances innovation performance (IP) through the complementary roles of knowledge orchestration (KO) and organisational intelligence (OI). It addresses how organisations in an emerging economy context transform AI-enabled learning into intelligent action and innovation outcomes. Design/methodology/approach A quantitative, survey-based study was conducted with 348 professionals working in information technology firms in Karachi, Pakistan. Established scales were adapted to measure AIDLC, KO, OI and IP. Partial least squares structural equation modelling was used to test the hypothesised direct and indirect relationships and to assess the measurement and structural models. Findings The results show that AIDLC has a significant positive effect on KO, OI and IP. KO positively influences OI and IP, while OI positively affects IP. Furthermore, KO and OI each individually mediate the relationship between AIDLC and IP, and they also form a serial mediation path from AIDLC to IP. These findings indicate that AIDLC foster stronger KO capabilities and higher OI, which together explain improved IP. Practical implications Managers should invest in AI-enabled learning practices and systems that not only capture and analyse knowledge but also orchestrate it across teams and functions. Building OI capabilities is critical for converting AI-driven learning into sustained IP, especially in resource-constrained, emerging economy settings. Originality/value This study introduces and operationalises the construct of AIDLC and empirically demonstrates its impact on IP through KO and OI. By integrating dynamic capabilities, knowledge-based and organisational learning perspectives, it offers a novel serial mediation framework that explains how AI-enabled learning is transformed into OI and innovation in the IT industry of an emerging economy.

VINE Journal of Information and Knowledge Management Systems
Shaheed Benazir Bhutto University (PK), Khadim Ali Shah Bukhari Institute of Technology (PK), Rockford University (US), University of Bisha (SA)
Industry, innovation and infrastructure
Openalex Percentile: Top 49%
Organizational and Employee Performance
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