20.500.12556/DKUM-99535 Dynamic sustainability risk an artificial intelligence framework for explaining forward-looking industry betas Systematic risk plays a central role in company valuation, enterprise risk management, and sustainable investment. However, conventional approaches primarily rely on historical beta estimates and provide limited insight into the factors associated with future changes in systematic risk. This study develops an AI-supported framework for identifying the determinants of one-year-ahead industry beta coefficients for the US economy by combining macroeconomic variables with risk indicators derived from global news analytics. Annual industry betas published by Damodaran are transformed into monthly observations to align with lagged explanatory variables. The analysis combines macroeconomic indicators with twenty-two artificial intelligence-supported risk categories extracted from the GDELT database, collectively representing Dynamic Sustainability Risk. The empirical results show that historical beta persistence alone does not fully explain future industry beta coefficients. Sustainability-related factors—including ESG, supply-chain, technological, strategic, and labor-market risks—consistently appear among the significant determinants across industries, complementing traditional macroeconomic variables. Furthermore, forward-looking systematic risk is associated with interactions between macroeconomic conditions and dynamic sustainability-related risks rather than with historical financial information alone. Rather than developing a forecasting model, the proposed framework provides an interpretable approach for identifying the macroeconomic and sustainability-related determinants associated with future industry beta coefficients, thereby supporting company valuation, enterprise risk management, and sustainable financial decision-making. dynamic sustainability risk sustainable finance artificial intelligence industry beta systematic risk ESG corporate resilience enterprise risk management cost of capital news analytics true false true Angleški jezik Angleški jezik Znanstveno delo 2026-08-19 12:54:09 2026-08-19 12:54:09 2026-08-20 03:07:21 0000-00-00 00:00:00 2026 0 0 str. 1-26 no. 16, spec. iss., [art. no.] 8290 Vol. 18 2026 0000-00-00 Zaloznikova Objavljeno NiDoloceno 2026-07-01 2026-08-11 2026-08-12 336.76:004.8 288193283 10.3390/su18168290 2071-1050 https://www.mdpi.com/2071-1050/18/16/8290 1 4ec4b4b9-9bbc-11f1-a6d4-00155d0001be https://dk.um.si/Dokument.php?lang=slv&id=209885 RAZ_Jagric_Timotej_2026.pdf RAZ_Jagric_Timotej_2026.pdf 1 2BCEBD35602ADDEC55D998D52B57FCD9 84ffb59ade0217cdbeee5dd7b243498ccdb4b4633405cf0f4b381f90c22cca7b 6b57be68-9bbc-11f1-a6d4-00155d0001be https://dk.um.si/Dokument.php?lang=slv&id=209886 Ekonomsko-poslovna fakulteta 0 0 0