AUDITS AT ALTERNATIVE ENERGY ENTERPRISES USING ARTIFICIAL INTELLIGENCE TECHNOLOGIES

The article explores the theoretical and practical aspects of the application of artificial intelligence in the audit of alternative energy enterprises in the context of the digitalization of the economy, the growth of technical and financial information, and the strengthening of requirements for transparency, accuracy, and efficiency of audit procedures. The relevance of the topic is due to the rapid development of alternative energy, the increase in the share of energy from renewable sources in the structure of energy consumption, the high capital intensity of such enterprises, the dependence of their functioning on natural and climatic factors, as well as the complexity of integrating technical, financial, environmental, and regulatory data in the audit process. The study proposes to use artificial intelligence at the preparatory stage of the audit to process documents, analyze the regulatory framework, and identify risk areas; at the audit planning stage, to predict risks, model audit scenarios, and optimize the audit plan; at the stage of collecting and verifying audit evidence – for analyzing large amounts of technical and financial data; at the stage of summarizing audit results – for grouping violations, ranking risks and visualizing results; at the stage of preparing the audit conclusion and recommendations – for automating the preparation of the audit report, summarizing results and forming recommendations; at the stage of monitoring the implementation of recommendations – for continuous monitoring of indicators, identifying secondary deviations and reporting new risks. The SWOT analysis made it possible to systematize the strengths and weaknesses, opportunities, and threats of applying artificial intelligence in the audit of alternative energy enterprises. The practical significance of the results obtained lies in the possibility of using them to improve audit methodology, develop digital tools for controlling and improving the quality of management decisions, and assess the technical, financial, and environmental sustainability of alternative energy enterprises.