The impact of artificial intelligence on organizational decision-making processes

Using a mixed-methods approach, data was collected through quantitative surveys (N=258) and qualitative interviews with AI practitioners and decision-makers across multiple industries. Findings indicate that AI significantly improves decision efficiency by automating analytical tasks, reducing human cognitive biases, and enabling real-time insights. However, challenges persist, particularly in algorithmic transparency, ethical governance, and compliance with regulatory standards. Key findings reveal that AI integration positively influences decision effectiveness (β=0.156, p=0.031), but human oversight (β=0.381, p<0.001) and regulatory compliance (β=0.314, p<0.001) play crucial mediating roles. Ethical and security challenges necessitate stronger AI governance frameworks, as organizations struggle with bias mitigation, legal accountability, and AI explainability. Industry experts emphasize the need for a hybrid Human-AI collaboration model, ensuring AI remains an augmentation rather than a replacement for human decision-makers. This study contributes to AI governance literature by highlighting the importance of ethical AI deployment, transparent decision systems, and regulatory adherence. Future research should explore AI’s impact in high-risk sectors, develop proactive AI compliance strategies, and examine cross-national AI regulatory frameworks to enhance responsible AI adoption globally.

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Publication Details

Journal
Edelweiss Applied Science and Technology
Published
2025-04-09
DOI
https://doi.org/10.55214/25768484.v9i4.6081
Citations
2
Primary Topic
Ethics and Social Impacts of AI
Type
article
Field-Weighted Citation Impact
4.73
Controls
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article

The impact of artificial intelligence on organizational decision-making processes

Eksiri Niyomsilp, Baoyu Huang
2 citations
Edelweiss Applied Science and Technology
Ethics and Social Impacts of AI
4.73
article

The impact of artificial intelligence on organizational decision-making processes

Eksiri Niyomsilp, Baoyu Huang
article en
2 citations

Abstract

Using a mixed-methods approach, data was collected through quantitative surveys (N=258) and qualitative interviews with AI practitioners and decision-makers across multiple industries. Findings indicate that AI significantly improves decision efficiency by automating analytical tasks, reducing human cognitive biases, and enabling real-time insights. However, challenges persist, particularly in algorithmic transparency, ethical governance, and compliance with regulatory standards. Key findings reveal that AI integration positively influences decision effectiveness (β=0.156, p=0.031), but human oversight (β=0.381, p<0.001) and regulatory compliance (β=0.314, p<0.001) play crucial mediating roles. Ethical and security challenges necessitate stronger AI governance frameworks, as organizations struggle with bias mitigation, legal accountability, and AI explainability. Industry experts emphasize the need for a hybrid Human-AI collaboration model, ensuring AI remains an augmentation rather than a replacement for human decision-makers. This study contributes to AI governance literature by highlighting the importance of ethical AI deployment, transparent decision systems, and regulatory adherence. Future research should explore AI’s impact in high-risk sectors, develop proactive AI compliance strategies, and examine cross-national AI regulatory frameworks to enhance responsible AI adoption globally.

Edelweiss Applied Science and TechnologyVol. 9(4)
Shinawatra University (TH)
Openalex Percentile: Top 6%
Ethics and Social Impacts of AI
4.73
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