GENERATIVE ARTIFICIAL INTELLIGENCE IN ECONOMIC SECTORS: ASSESSING IMPLEMENTATION EFFICIENCY AND ENSURING TECHNOLOGICAL SECURITY

Abstract

This article examines the role of generative artificial intelligence in the digital transformation of economic sectors, with a particular focus on assessing implementation efficiency and ensuring technological security. The study argues that generative AI is becoming a strategic tool for improving productivity, operational speed, decision-making quality, and innovation capacity across manufacturing, finance, logistics, public administration, and other sectors. At the same time, the article emphasizes that the benefits of generative AI are accompanied by serious technological risks, including data leakage, model misuse, privacy violations, unreliable outputs, and cybersecurity vulnerabilities. The research is based on a qualitative comparative analysis of recent open-access academic and institutional sources, including OECD, World Bank, NIST, and sector-specific studies. The findings show that the effectiveness of generative AI should be evaluated through a dual framework that combines economic performance indicators with technological security criteria. The article concludes that sustainable implementation requires not only digital infrastructure and organizational adaptation, but also strong governance mechanisms, human oversight, and continuous risk monitoring.