Artificial intelligence adoption and financial management outcomes: A multi-dimensional analysis of banking and insurance sectors in Indonesia
DOI:
https://doi.org/10.53088/jmdb.v6i1.3048Keywords:
Artificial Intelligence, Financial Performance, Indonesia Stock Exchange, Signalling Theory, Operational EfficiencyAbstract
This study investigates the impact of Artificial Intelligence (AI) adoption on the financial performance of banking and insurance firms listed on the Indonesia Stock Exchange from 2020 to 2024. Using a quantitative explanatory framework, the research analyzes a sample of 230 observations. AI adoption was measured through disclosure intensity in annual reports, while financial performance was evaluated across three dimensions: operational efficiency (BOPO), financial stability (Z-Score), and firm value (Tobin’s Q). A Fixed Effect Model was employed for statistical analysis, as dictated by the Hausman Test results. The results indicate that AI adoption has a significant positive impact on operational expenses (BOPO), suggesting that high infrastructure costs and initial implementation expenditures currently outweigh efficiency gains. However, AI adoption also shows a significant positive impact on firm value, supporting Signaling Theory, where investors reward digital transformation despite short-term costs. No significant impact was found on financial stability. These findings confirm an AI Productivity Paradox in the Indonesian emerging market, where the high cost of implementation creates a temporary financial burden but yields a market innovation premium.
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