Exploring the Impact of Machine Learning on Predictive Safety Analytics: A Qualitative Study of Implementation Challenges and Benefits Across Key Industries
This study explores the impact of machine learning (ML) on predictive safety analytics, focusing onimplementation challenges and benefits across key industries. Utilizing a qualitative research methodology,including interviews and case studies, the research identifies critical themes such as integration challengeswith legacy systems, data quality and management, regulatory compliance, and privacy concerns. The studyalso highlights significant benefits including enhanced predictive accuracy, operational efficiency, andimproved safety outcomes. The findings provide valuable insights into the successful adoption of MLtechnologies for safety analytics, emphasizing the importance of cross-functional collaboration and effectivechange management.
Publication Details
- Journal
- Zenodo (CERN European Organization for Nuclear Research)
- Published
- 2025-08-07
- DOI
- https://doi.org/10.5281/zenodo.16761027
- Primary Topic
- Artificial Intelligence in Healthcare and Education
- Type
- article
- Field-Weighted Citation Impact
- 0.00