Sustainable Financial Performance in the Age of AI: Opportunities and Challenges - Khan, Aqil Waqar; Kumar, C. T. Sunil; Gohil, Divyaba Pravinsinh (International Journal of Economics and Financial Issues, 2025)
This study investigates the role of artificial intelligence (AI) in shaping sustainable financial performance by exploring both the opportunities and challenges of AI adoption in the financial sector. It highlights AI’s potential to enhance fraud detection, financial reporting, accessibility of financial services, and investor trust while also addressing concerns around ethics, regulatory gaps, algorithmic bias, and data privacy. A quantitative research design was adopted using survey data collected from 200 finance professionals across auditing, financial services, education, banking, investment, and energy sectors. The study applied descriptive statistics, exploratory factor analysis (EFA) to examine the impact of AI opportunities and challenges on sustainable financial performance and reliability tests using Cronbach’s alpha to ensure internal consistency of the scales. The results demonstrate that AI integration significantly strengthens fraud detection, improves financial reporting transparency, and enhances investor confidence through proactive disclosures. These findings validate the signaling effect of AI-related transparency on firm performance. However, empirical evidence also confirms that ethical dilemmas, regulatory fragmentation, data privacy risks, and algorithmic bias remain critical barriers to sustainable AI adoption. While opportunities strongly align with improved financial performance, challenges undermine stakeholder trust and limit equitable integration. The study is limited to survey responses from finance professionals in selected industries, which may restrict generalizability across global contexts. Additionally, the cross-sectional design prevents assessment of long-term causal effects. This research contributes by bridging the gap between AI innovation and sustainable finance literature. It extends signaling, stakeholder, and technology acceptance theories, showing how AI disclosures act as strategic signals of credibility and long-term value creation.