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The Role of Artificial Intelligence Technology in Predictive Risk Assessment for Business Continuity: A Case Study of Greece

Author

Listed:
  • Stavros Kalogiannidis

    (Department of Business Administration, University of Western Macedonia, 51100 Grevena, Greece)

  • Dimitrios Kalfas

    (Department of Agriculture, Faculty of Agricultural Sciences, University of Western Macedonia, 53100 Florina, Greece)

  • Olympia Papaevangelou

    (Department of Business Administration, University of Western Macedonia, 51100 Grevena, Greece)

  • Grigoris Giannarakis

    (Department of Business Administration, University of Western Macedonia, 51100 Grevena, Greece)

  • Fotios Chatzitheodoridis

    (Department of Management Science and Technology, University of Western Macedonia, 50100 Kozani, Greece)

Abstract

This study examined the efficacy of artificial intelligence (AI) technologies in predictive risk assessment and their contribution to ensuring business continuity. This research aimed to understand how different AI components, such as natural language processing (NLP), AI-powered data analytics, AI-driven predictive maintenance, and AI integration in incident response planning, enhance risk assessment and support business continuity in an environment where businesses face a myriad of risks, including natural disasters, cyberattacks, and economic fluctuations. A cross-sectional design and quantitative method were used to collect data for this study from a sample of 360 technology specialists. The results of this study show that AI technologies have a major impact on business continuity and predictive risk assessment. Notably, it was discovered that NLP improved the accuracy and speed of risk assessment procedures. The integration of AI into incident response plans was particularly effective, greatly decreasing company interruptions and improving recovery from unforeseen events. It is advised that businesses invest in AI skills, particularly in fields such as NLP for automated risk assessment, data analytics for prompt risk detection, predictive maintenance for operational effectiveness, and AI-enhanced incident response planning for crisis management.

Suggested Citation

  • Stavros Kalogiannidis & Dimitrios Kalfas & Olympia Papaevangelou & Grigoris Giannarakis & Fotios Chatzitheodoridis, 2024. "The Role of Artificial Intelligence Technology in Predictive Risk Assessment for Business Continuity: A Case Study of Greece," Risks, MDPI, vol. 12(2), pages 1-23, January.
    • Handle: RePEc:gam:jrisks:v:12:y:2024:i:2:p:19-:d:1324892
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