ANALYZING THE AREAS OF APPLICATION OF INNOVATIONS IN ASSESSING BUSINESS ENTITIES: A SYSTEMATIC LITERATURE REVIEW

The rapid digital transformation of the global economy has necessitated innovative approaches to assessing business entities. Traditional valuation and performance evaluation methods are increasingly supplemented or replaced by advanced technologies such as artificial intelligence (AI), machine learning (ML), blockchain, big data analytics, and the Internet of Things (IoT). This study systematically reviews the literature to identify and analyze the primary areas of application of these innovations in business assessment. Following PRISMA guidelines, 142 peer-reviewed articles published between 2015 and 2025 were analyzed from Scopus, Web of Science, and Google Scholar. Key findings reveal that AI and ML dominate applications in financial forecasting, risk management, and fraud detection, while blockchain enhances transparency in auditing and ESG reporting. Big data analytics and IoT enable real-time operational and strategic assessments. Quantitative data indicate that organizations adopting these innovations report up to 66% gains in productivity and efficiency, with AI investment in the financial sector projected to reach USD 60 billion by 2025. The study categorizes applications into five core areas, highlights empirical benefits and challenges, and proposes a conceptual framework for integrated innovation-driven business assessment. Implications for practitioners, policymakers, and future research are discussed, emphasizing the need for ethical governance and hybrid human-AI models.