ENTERPRISE RISK MANAGEMENT IN ERP IMPLEMENTATION: CHALLENGES, STRATEGIES AND RECENT TRENDS IN AI – A MINI REVIEW

Abstract

Enterprise Risk Management (ERM) has become a critical foundation for guiding the success of Enterprise Resource Planning (ERP) implementations, particularly as organizations face increasingly complex technological, organizational, and financial uncertainties. This mini-review synthesizes research between 2020 and 2025, highlighting how structured ERM methodologies ranging from Risk Assessment Matrices and Monte Carlo Simulation to SWOT Analysis and Delphi-based evaluations support the identification, prioritization, and mitigation of risks throughout the ERP lifecycle. The selected studies show that these approaches contribute to improved project stability, better cost control, and stronger alignment between ERP initiatives and organizational objectives across sectors such as healthcare, manufacturing, education, and retail. Recent developments further indicate a growing shift toward AI-enhanced risk management, where techniques such as predictive analytics, anomaly detection, and automated auditing enable earlier detection of system failures and more responsive oversight. Despite these advancements, challenges persist, including cultural resistance, uneven data quality, skill shortages, and limited adaptability of ERM models across different operational contexts. The review concludes that integrating traditional ERM frameworks with intelligent, data-driven tools and continuous monitoring mechanisms is essential for transforming ERP implementation into a proactive and resilient organizational strategy.