Navigating publicness in digital innovation: big data and AI adoption in European public sector organisations

Purpose This study investigates how publicness, defined through dimensions of ownership, funding, goal setting and control structure, shapes the collection and use of big data (BD) as well as the development and application of artificial intelligence (AI) in public service delivery across Europe. Design/methodology/approach Drawing on publicness theory, the study employs a multiple case study design, using 17 expert interviews from diverse public organisations across the Netherlands, Germany, Belgium and the UK. Data were analysed through thematic coding and cross-case comparison to explore sectoral differences and integration levels. Findings BD is widely used in statistical, law enforcement and infrastructure sectors, supported by established legal frameworks and inter-organisational sharing. In contrast, AI remains in early development stages due to demands for transparency, ethical concerns and risk aversion. The level of publicness significantly influences data collection, management, sharing and AI application. High control structures foster explainable, human-centric AI, while fragmented infrastructure and limited funding remain barriers. Research limitations/implications The findings are context-specific and not statistically generalisable. However, they provide conceptual and empirical insights for theory-building and future comparative or longitudinal studies. Practical implications Recommendations include investing in data governance, fostering responsible AI culture and strengthening cross-agency coordination and standardisation. Social implications By aligning digital innovation with democratic values, the study promotes citizen trust and equitable service delivery in public AI and BD applications. Originality/value This study offers a novel application of publicness theory to examine technological innovation in the public sector, highlighting how institutional characteristics constrain or enable digital transformation.

Institutions

Publication Details

Journal
European Journal of Innovation Management
Published
2025-12-12
DOI
https://doi.org/10.1108/ejim-07-2025-0964
Primary Topic
E-Government and Public Services
Type
article
Field-Weighted Citation Impact
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article

Navigating publicness in digital innovation: big data and AI adoption in European public sector organisations

European Journal of Innovation Management
E-Government and Public Services
article

Navigating publicness in digital innovation: big data and AI adoption in European public sector organisations

article en

Abstract

Purpose This study investigates how publicness, defined through dimensions of ownership, funding, goal setting and control structure, shapes the collection and use of big data (BD) as well as the development and application of artificial intelligence (AI) in public service delivery across Europe. Design/methodology/approach Drawing on publicness theory, the study employs a multiple case study design, using 17 expert interviews from diverse public organisations across the Netherlands, Germany, Belgium and the UK. Data were analysed through thematic coding and cross-case comparison to explore sectoral differences and integration levels. Findings BD is widely used in statistical, law enforcement and infrastructure sectors, supported by established legal frameworks and inter-organisational sharing. In contrast, AI remains in early development stages due to demands for transparency, ethical concerns and risk aversion. The level of publicness significantly influences data collection, management, sharing and AI application. High control structures foster explainable, human-centric AI, while fragmented infrastructure and limited funding remain barriers. Research limitations/implications The findings are context-specific and not statistically generalisable. However, they provide conceptual and empirical insights for theory-building and future comparative or longitudinal studies. Practical implications Recommendations include investing in data governance, fostering responsible AI culture and strengthening cross-agency coordination and standardisation. Social implications By aligning digital innovation with democratic values, the study promotes citizen trust and equitable service delivery in public AI and BD applications. Originality/value This study offers a novel application of publicness theory to examine technological innovation in the public sector, highlighting how institutional characteristics constrain or enable digital transformation.

European Journal of Innovation Management
Queensland University of Technology (AU), University of Groningen (NL)
Industry, innovation and infrastructure
Openalex Percentile: Top 25%
E-Government and Public Services
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Navigating publicness in digital innovation: big data and AI adoption in European public sector organisations · European Journal of Innovation Management (2025) | TGRS Research Map | TGRS