AI-Augmented Intelligent System Integration and Business Automation

Abstract

The increasing number and complexity of systems required for business process automation have resulted in system integration issues, leading to IT project failures or delays, necessitating a need for a better approach to streamline system integration and
business automation with efficient use of resources. Existing research have identified the need for using AI techniques in business process automation, however there is a scarcity of research of applying AI techniques in the context of system integration and business automation. This research provides a comprehensive review of system integration and business automation and discusses the AI techniques in this context. This research focuses on the use of established AI techniques and emerging AI Augmented Software Engineering (AIASE) for intelligent system integration and business automation. The study employs deductive reasoning, descriptive analysis, and inductive reasoning to examine existing literature, collect primary and secondary data from the industry using quantitative methods, and propose a framework and approach for AIASE implementation. The study emphasizes the contemporary challenges of system integration, skillset, infrastructure, and environment for applying AIASE and highlights the benefits and challenges resulting from AIASE. The proposed framework and approach have the potential to significantly improve the system integration market and shape the future of system integration software. The research findings are valuable to system integration consultancy businesses and integration software providers in developing better consultancy practice, products, and tools for applying AI augmented system integration and business automation.