Leveraging artificial intelligence for workload balancing in information technology departments: A qualitative...

Area of Science:

• Information Technology
• Artificial Intelligence
• Operations Management

Background:

• Inefficient workload distribution and resource utilization in IT departments hinder operational performance.
• Traditional methods struggle with dynamic workload changes, necessitating advanced solutions.

Purpose of the Study:

• To examine artificial intelligence's role in IT workload balancing and its impact on operational efficiency and resource utilization.
• To analyze AI's influence on both technical optimization and human/organizational aspects.

Main Methods:

• Qualitative approach utilizing systematic literature review and document analysis.
• Thematic analysis of academic, technical, and corporate documents to identify AI roles in workload balancing.

Main Results:

• AI algorithms reduce workload imbalance, processing times, and errors through task prioritization and dynamic resource allocation.
• Operational efficiency is boosted via performance monitoring and cost optimization, but human-machine interaction and organizational adaptation are crucial for effectiveness.

Conclusions:

• AI is a potent tool for IT workload balancing, efficiency, and resource optimization.
• Holistic implementation requires integrating technological performance with human factors, organizational adaptation, and strategic management.
• The study frames AI-based workload management from a socio-technical perspective for academic and practical guidance.