The impact of machine learning and artificial intelligence on business process reengineering in the digital era

The fast growth of Machine Learning (ML) and Artificial Intelligence (AI) has greatly changed the way companies plan, control, and improve their work steps in the digital age. Firms are under growing demand to boost their efficiency, flexibility, and decision-making. ML and AI tools have become important parts of Business Process Reengineering (BPR). This paper looks at the role of ML and AI in business process reengineering by studying how data-driven plans help automation, forecast analysis, and smart decision-making in the main areas of a company. The paper discusses applied machine learning techniques that are increasingly implemented in current business landscapes. This involves supervised learning, predictive modelling, and pattern recognition. The said techniques allow firms to restructure their standard practices by reducing human input as well as eliminating operational lags, hence raising the total efficiency of the process. Moreover, these systems heighten business activities through instant observation of anomalies in addition to flexible process improvement grounded on perpetually changing data. This study takes an application view and merges recent advances in the application of ML and AI towards business process improvement and reengineering. These include operational efficiency, cost reduction, enhanced customer experience, and strategic decision support. The paper outlines how ML-based predictive modelling assists organizations in such areas as demand forecasting and resource allocation optimization as well as process bottlenecks identification that can be addressed through AI-based automation of faster and more accurate execution of both routine as well as complex tasks. They found that firms using ML and AI technologies in business process reengineering get greater process agility, enhanced consistency of performance, and strength in resilience when going digital.