Investigating the Benefits, Challenges, and Implications of Integrating Generative AI into Software Development Methodologies for Effective Healthcare Project Management

Abstract

This dissertation examines transforming Project management methodologies into a value-based care paradigm, explicitly focusing on how the rapid evolution of technology has significantly impacted healthcare project management, particularly with the integration of complex digital systems such as telemedicine, Electronic Health Records (EHR), and financial management platforms. As healthcare organizations strive to modernize their operations, they face unique challenges in managing large-scale software development projects. These challenges are exacerbated by the healthcare sector's strict regulatory requirements and need for continuous innovation, making it difficult for traditional project management methodologies such as Agile, Waterfall, and Hybrid models to meet the demands of healthcare environments. These methodologies commonly encounter such problems as cost overruns, delays, and resource misallocation.

This research explores the transformative potential of Generative AI, a subset of Artificial Intelligence (AI), in healthcare project management. Generative AI, powered by advanced models such as GPT and Generative Adversarial Networks (GANs), offers significant potential in automating tasks, enhancing decision-making, and streamlining resource allocation. In healthcare project management, AI can generate project timelines, simulate outcomes, and predict risks, allowing project managers to focus more on strategic initiatives rather than manual processes. Furthermore, AI-driven solutions can facilitate collaboration among cross-functional teams, improve stakeholder communication, and enhance the overall adaptability of project management processes.
The study adopts a quantitative research methodology, analyzing 10-15 healthcare software development projects that use Agile, Waterfall, and Hybrid approaches. It compares AI-integrated projects to those employing traditional methods, evaluating key factors such as project efficiency, risk management, cost control, and adherence to deadlines. The research also aims to assess the influence of Generative AI on innovation, automation, and the overall effectiveness of project management in healthcare settings.
Through a structured analysis, this study will provide insights into the organizational and strategic challenges of integrating Generative AI into healthcare project management. It will offer practical recommendations for enhancing project success rates by improving resource utilization, reducing project delays, and fostering better collaboration. The findings will contribute to the growing body of knowledge on AI's transformative potential in healthcare, particularly in improving the success and efficiency of complex software development projects.
Keywords: Generative AI, Project Management, Healthcare, Software Development, Agile, Waterfall, Hybrid, Risk Management, Innovation, Automation, Collaboration