Human-in-the-Loop Automation: Redesigning Global Business Processes to Optimize Collaboration between AI and Employees
Abstract
The implementation of Artificial Intelligence (AI) in the business process worldwide is fast, with potential efficiency improvements never seen before. However, the complete automation oftentimes lacks nuance and the situational sense of judgment, which only a human employee can provide. With the world of business looking to expand its operations both in scale and domain, the resolve to mingle the precision of AI and the intuition and ethical thinking of human beings has never been more important. This essay discusses Human-in-the-Loop (HITL) paradigm, a kind of hybrid approach that preserves human supervision during the automatized processes, as one of the key approaches to designing and governing. Through assessing empirical evidence, theoretical frameworks, and the case studies around the world, the study will be able to determine the best practices on implementing HITL practices to guarantee operational excellence and excellent quality of decisions made, as well as maintaining a workforce through engagement. Using a mixed-methods design, the paper answers practical questions related to task design, regulatory compliance, and cross-cultural adaptability with an eventual recommendation to redesign business processes and human-AI work relationship according to global scalability and resilience.
How to Cite This Article
Abdullateef Okuboye (2022). Human-in-the-Loop Automation: Redesigning Global Business Processes to Optimize Collaboration between AI and Employees . International Journal of Multidisciplinary Research and Growth Evaluation (IJMRGE), 3(1), 1169-1178. DOI: https://doi.org/10.54660/IJMRGE.2022.3.1.1169-1178
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