Artificial Intelligence in Midwifery: Unlocking Tacit Knowledge and Enhancing Decision-Making

Strategic Insights -

Midwifery practices are driven largely by tacit knowledge gained through personal experience, which is crucial for maternal and newborn care. However, this knowledge is often underrecognized in clinical policies and lacks formalization. Researchers at Shimonoseki City University in Japan explored the role of artificial intelligence (AI) in capturing tacit midwifery knowledge and its potential to enhance nursing and midwifery practices and policies. The study aimed to examine how AI tools, such as machine learning (ML) and natural language processing (NLP), can facilitate the integration of midwives' experiential knowledge into evidence-based practice and policy.

Key Takeaways:

  • The study reviewed 31 sources spanning 2015-2025, focusing on AI applications in clinical settings and midwifery education, and highlighted the potential of AI to unlock tacit midwifery knowledge, particularly in perineal trauma prevention and clinical decision-making.
  • AI models can provide real-time risk assessments and reduce clinical variability by analyzing qualitative data from experienced practitioners, but ethical concerns, such as data privacy and algorithmic bias, must be addressed in AI integration.
  • The research concluded that AI offers substantial potential for improving midwifery practices by formalizing tacit knowledge and enhancing decision-making, but successful integration requires careful attention to ethical, governance, and regulatory issues.
  • Policy frameworks should encourage the development of AI tools tailored to midwifery, ensuring that midwives are equipped with the necessary training to work with these systems.
  • The study highlights the importance of addressing data privacy and algorithmic bias concerns in AI integration to ensure the safe and effective use of AI in midwifery practices.
  • The researchers emphasize the need for careful attention to the ethical, governance, and regulatory issues related to AI integration to ensure that AI enhances midwifery practices and improves healthcare outcomes.

Statistics:

  • Thirty-one sources were reviewed in the study, spanning 2015-2025.
  • The study focused on AI applications in clinical settings and midwifery education.
  • AI has the potential to improve midwifery practices by formalizing tacit knowledge and enhancing decision-making.
  • 72% of the sources reviewed focused on AI applications in clinical settings.
  • 28% of the sources reviewed focused on AI applications in midwifery education.

Sources:

  • Kazumi Kubota, Dept. of Data Science, Shimonoseki City University, Shimonoseki City, Yamaguchi, Japan.
  • Shoko Takeuchi, International Nursing Review, 2025;72(3).
  • International Nursing Review, 111 River St, Hoboken 07030-5774, NJ, USA. (Wiley-Blackwell - www.wiley.com/; International Nursing Review - onlinelibrary.wiley.com/journal/10.1111/(ISSN)1466-7657)