ASSESSMENT OF THE EFFECTIVENESS OF INTERNAL CONTROL SYSTEMS IN THE CONTEXT OF ARTIFICIAL INTELLIGENCE AND PROCESS AUTOMATION
Keywords:
artificial intelligence; internal control; process automation; risk management; intelligent automated controls; human oversight; European Regulation on Artificial Intelligence (AI Act); COSO; COBIT; internal audit; regulatory compliance; corporate governance.Abstract
This study is dedicated to assessing the effectiveness of internal control systems in the context of the increasing use of artificial intelligence and automation of business processes. The transformation of traditional control mechanisms in a digital environment is analyzed, emphasizing the role of intelligent automated controls, algorithmic risk and the need for human oversight in decision-making.Particular attention is paid to the new European regulatory framework for the use of artificial intelligence - Regulation (EU) 2024/1689, which introduces a risk-based approach, mandatory requirements for transparency, traceability and human control, as well as significant sanctions for non-compliance. The study considers artificial intelligence not only as a tool for increasing efficiency, but also as an object of internal control, subject to systematic management, monitoring and audit.Based on the principles of COSO and COBIT, an integrated approach is proposed for assessing the effectiveness of internal control in an AI environment, which combines organizational, technological and regulatory elements. Practical examples illustrate how the lack of adequate internal controls over AI can lead to significant regulatory and financial risks, including the imposition of significant sanctions.The study highlights the importance of an adaptive and proactive approach to internal control and audit in the context of digitalization, as a factor for resilience, compliance and good corporate governance in modern organizations.
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