Independent Researcher, USA.
World Journal of Advanced Engineering Technology and Sciences, 2025, 15(03), 2209–2219
Article DOI: 10.30574/wjaets.2025.15.3.1145
Received on 12 May 2025; revised on 21 June 2025; accepted on 24 June 2025
This article examines the integration of Artificial Intelligence and Enterprise Resource Planning systems to transform workforce planning in healthcare environments. Traditional workforce planning in healthcare relies on historical averages and reactive approaches, creating inefficiencies in resource allocation and staff utilization. The article presents a framework for enhancing ERP systems with AI-driven predictive capabilities that leverage consolidated data from human resources, clinical operations, and scheduling modules. Through a detailed case study at an academic medical center, the implementation demonstrates significant improvements in forecasting accuracy, resource distribution, cost management, and staff satisfaction. The framework balances algorithmic capabilities with human oversight, establishing appropriate governance structures and change management protocols. Critical success factors include data readiness, leadership commitment, stakeholder engagement, and phased implementation approaches. The article discusses limitations in current implementations and future research directions while exploring broader implications for AI-human collaboration in complex decision environments beyond healthcare.
Healthcare workforce planning; Artificial intelligence; Enterprise resource planning; Predictive analytics; Buman-AI collaboration
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Kumar Amodh Yadav. Transforming healthcare workforce planning through AI-augmented ERP Systems: A predictive analytics framework. World Journal of Advanced Engineering Technology and Sciences, 2025, 15(03), 2209-2219. Article DOI: https://doi.org/10.30574/wjaets.2025.15.3.1145.