THEORETICAL AND METHODOLOGICAL FOUNDATIONS FOR DEVELOPING AUDIT IN THE DIGITAL ECONOMY
DOI:
https://doi.org/10.5281/Keywords:
Artificial intelligence, machine learning, big data analytics, cybersecurity, audit profession, fraud detection, real-time monitoring, RFID, unstructured data, financial reporting, risk assessment, digital transformationAbstract
Artificial intelligence (AI), big data analytics, and cybersecurity are rapidly transforming the modern audit profession. This paper examines how AI-driven machine learning models enhance fraud detection, automate transaction recording, and enable the analysis of unstructured data such as emails, social media, and audio recordings. Furthermore, big data technologies — including RFID, GPS, and sensor-based data streams — provide auditors with real-time monitoring capabilities and richer audit evidence beyond traditional financial records. At the same time, cybersecurity emerges as a critical concern, as organizations face growing threats to their digital assets, financial systems, intellectual property, and operational continuity. The study concludes that the integration of these three pillars fundamentally redefines the role of auditors, shifting their focus from routine data processing toward higher-level analytical judgment, risk assessment, and strategic decision-making in an increasingly digitalized environment.
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