Strategizing AI-powered middleware system design for Human Resources Data Management

The growing adoption of iPaaS (Integration Platform as a Service) solutions in organisations has led to an increased need for efficient and tailored middleware systems to manage the various data types, including various use cases of artificial intelligence and automation. While many iPaaS solutions offer similar core utilities, the differences in configuration options, the availability of connectors, range of features and the ease-of-use can greatly impact their efficacy while handling specific types of data. Most iPaaS solutions try to fit the one-size-fits-all model so that all kinds of data can be manipulated through a single iPaaS medium. Differences in data types poses a limitation to such a model. This paper aims to explore the challenges faced during best practices of the current middleware systems focussing on HR (Human Resources) data, as well as potential AI applications in the design of the iPaaS. The study also highlights the importance of considering factors such as data security, data governance, and user friendliness when selecting an iPaaS solution for HR data management and possible AI-driven strategies.