Artificial intelligence in wellbeing services counties: management and experts’ perspectives on opportunities, challenges and AI readiness

Artificial intelligence (AI) can be used to enhance healthcare efficiency and quality. New generative AI (GenAI) and large language models (LLM) offer novel opportunities for AI applications. This study examines management and expert perceptions of AI implementation opportunities and challenges in wellbeing services counties (WSCs), which are the responsible providers of healthcare and social welfare services in their region in Finland.A qualitative interview study was conducted in two phases from Nov 2023 to Feb 2024. First, 28 participants were interviewed semi-structurally. Thematic analysis was used to identify potential AI use cases, main use contexts, and related benefits and challenges. Second, 16 participants (14 new persons and two already interviewed) validated the results in four group interviews and prioritised the use contexts by their potential for WSCs. The framework of Roppelt and colleagues was used to analyse the AI readiness of WSCs. Six AI use contexts were identified and prioritised: 1. Clinical healthcare, 2. Patient interaction and self-care, 3. Support services, 4. Management, 5. Preventive healthcare, 6. Social welfare services. AI readiness should be increased by the government by supporting organisational collaboration, experience sharing and regulatory interpretation. Healthcare organisations need to improve AI competence and skills at all levels. Regulation and WSC culture not supporting experimentation were identified as main challenges for broader AI implementation.AI particularly GenAI, is seen as a promising technology to address workload, financial, and service demand challenges in WSCs. Challenges can be mitigated through focused collaboration and actions within and between stakeholder organisations. AI implementation research in healthcare should consider the rapid development of AI, including increasingly human-like behaviour and integration into physical robots.

Authors

Institutions

Publication Details

Journal
Finnish Journal of eHealth and eWelfare
Published
2025-04-08
DOI
https://doi.org/10.23996/fjhw.155471
Citations
1
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
0.65
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Artificial intelligence in wellbeing services counties: management and experts’ perspectives on opportunities, challenges and AI readiness

Marketta Niemelä, Tommi Kemppainen, Jenny Vuollet
1 citations
Finnish Journal of eHealth and eWelfare
Artificial Intelligence in Healthcare and Education
0.65
article

Artificial intelligence in wellbeing services counties: management and experts’ perspectives on opportunities, challenges and AI readiness

Marketta Niemelä, Tommi Kemppainen, Jenny Vuollet
article en
1 citations

Abstract

Artificial intelligence (AI) can be used to enhance healthcare efficiency and quality. New generative AI (GenAI) and large language models (LLM) offer novel opportunities for AI applications. This study examines management and expert perceptions of AI implementation opportunities and challenges in wellbeing services counties (WSCs), which are the responsible providers of healthcare and social welfare services in their region in Finland.A qualitative interview study was conducted in two phases from Nov 2023 to Feb 2024. First, 28 participants were interviewed semi-structurally. Thematic analysis was used to identify potential AI use cases, main use contexts, and related benefits and challenges. Second, 16 participants (14 new persons and two already interviewed) validated the results in four group interviews and prioritised the use contexts by their potential for WSCs. The framework of Roppelt and colleagues was used to analyse the AI readiness of WSCs. Six AI use contexts were identified and prioritised: 1. Clinical healthcare, 2. Patient interaction and self-care, 3. Support services, 4. Management, 5. Preventive healthcare, 6. Social welfare services. AI readiness should be increased by the government by supporting organisational collaboration, experience sharing and regulatory interpretation. Healthcare organisations need to improve AI competence and skills at all levels. Regulation and WSC culture not supporting experimentation were identified as main challenges for broader AI implementation.AI particularly GenAI, is seen as a promising technology to address workload, financial, and service demand challenges in WSCs. Challenges can be mitigated through focused collaboration and actions within and between stakeholder organisations. AI implementation research in healthcare should consider the rapid development of AI, including increasingly human-like behaviour and integration into physical robots.

Finnish Journal of eHealth and eWelfareVol. 17(1)
University of Helsinki (FI), Tampere University of Applied Sciences (FI), Tampere University (FI), Ferring Pharmaceuticals (Finland) (FI)
Openalex Percentile: Top 26%
Artificial Intelligence in Healthcare and Education
0.65
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.