Integration of AI Supported Risk Management in ERP Implementation

  •  Petya Biolcheva    
  •  Miglena Molhova    


The objective of this paper is to show the possibilities for the implementation of artificial intelligence (AI) in risk assessment methodology for ERP projects. Both AI and ERP being solutions built around data, it is of great importance how this data is organized and processed, and how it can be used on the one hand to manage the business process in a more efficient way and on the other to address risk factors that might compromise the ERP system in a way, which standard risk assessment methodologies might miss. AI can add value to such risk assessment methodology as it can process large amounts of data and even automize repetitive and heavy load risk management steps. AI can allow risk managers to respond faster to new and emerging threats in an ERP project. By acting in real time and with some predictive capabilities, AI supported risk management could reach a new level in improving the managers’ decision-making for building the ERP system of the company. The literature review is given of the main AI and machine learning techniques of benefit to risk management and ERP projects. Then an analysis, using current practice and empirical evidence, is carried out of the application of these techniques to the risk management fields in implementing an ERP system. The paper also presents a showcase of how Bulgarian companies address the issues of risk assessment and AI implementation in it to build ERP systems.

This work is licensed under a Creative Commons Attribution 4.0 License.
  • ISSN(Print): 1913-8989
  • ISSN(Online): 1913-8997
  • Started: 2008
  • Frequency: quarterly

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