Systemic challenges in AI adoption in public social and health organizations in Finland: a technology-organisation-environment perspective

Purpose The aim is to identify the key technological, organizational, and environmental challenges affecting the adoption of artificial intelligence (AI) in public social and health organizations. The Technology-Organization-Environment (TOE) theory was used as a framework for the study. As AI is increasingly utilized, research is needed to support organizational management and development work. Design/methodology/approach We employed a mixed-methods research design, utilizing a web-based survey that included both quantitative, structured questions and qualitative, open-ended questions. The data included answers from experts within the Finnish social and healthcare AI innovation ecosystem (n = 82), representing public, private, and third-sector organizations. A theory-driven content analysis was conducted for the qualitative data, and descriptive statistical analysis was performed for the quantitative data. Findings The challenges of AI adoption form a systemic whole where factors are strongly interdependent. All 46 challenges were rated at least somewhat significant (mean ≥ 1.6, scale 0–3), with an overall mean score of 2.05. Organizational challenges emerged as the most critical, notably limited financial resources, insufficient AI competence, and inadequate change management. Among the environmental challenges, ambiguity in legislative interpretation and national funding shortfalls were particularly notable. Experts with prior involvement in AI projects rated challenges statistically less substantial than those with less experience. Originality/value This study provides the first national-level analysis examining AI adoption challenges across all three TOE theory dimensions in public social and healthcare organizations, empirically demonstrating their systemic interdependencies through multi-stakeholder perspectives. Previous research has primarily focused on specific AI applications or individual organizational factors.

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Publication Details

Journal
Journal of Health Organization and Management
Published
2025-09-30
DOI
https://doi.org/10.1108/jhom-06-2025-0309
Citations
1
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
0.65
Controls
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article

Systemic challenges in AI adoption in public social and health organizations in Finland: a technology-organisation-environment perspective

Marjo Suhonen, Jarmo Pulkkinen, Kimmo Huttu
1 citations
Journal of Health Organization and Management
Artificial Intelligence in Healthcare and Education
0.65
article

Systemic challenges in AI adoption in public social and health organizations in Finland: a technology-organisation-environment perspective

Marjo Suhonen, Jarmo Pulkkinen, Kimmo Huttu
article en
1 citations

Abstract

Purpose The aim is to identify the key technological, organizational, and environmental challenges affecting the adoption of artificial intelligence (AI) in public social and health organizations. The Technology-Organization-Environment (TOE) theory was used as a framework for the study. As AI is increasingly utilized, research is needed to support organizational management and development work. Design/methodology/approach We employed a mixed-methods research design, utilizing a web-based survey that included both quantitative, structured questions and qualitative, open-ended questions. The data included answers from experts within the Finnish social and healthcare AI innovation ecosystem (n = 82), representing public, private, and third-sector organizations. A theory-driven content analysis was conducted for the qualitative data, and descriptive statistical analysis was performed for the quantitative data. Findings The challenges of AI adoption form a systemic whole where factors are strongly interdependent. All 46 challenges were rated at least somewhat significant (mean ≥ 1.6, scale 0–3), with an overall mean score of 2.05. Organizational challenges emerged as the most critical, notably limited financial resources, insufficient AI competence, and inadequate change management. Among the environmental challenges, ambiguity in legislative interpretation and national funding shortfalls were particularly notable. Experts with prior involvement in AI projects rated challenges statistically less substantial than those with less experience. Originality/value This study provides the first national-level analysis examining AI adoption challenges across all three TOE theory dimensions in public social and healthcare organizations, empirically demonstrating their systemic interdependencies through multi-stakeholder perspectives. Previous research has primarily focused on specific AI applications or individual organizational factors.

Journal of Health Organization and ManagementVol. 39(9)
University of Lapland (FI)
Openalex Percentile: Top 21%
Artificial Intelligence in Healthcare and Education
0.65
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