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<p>This paper examines how artificial intelligence (AI) capability contributes to real-time financial reporting capability (RTFRC) within organizations, emphasizing the digital mechanisms that enable this transformation. Drawing on survey data from 320 accounting and finance professionals across diverse industries, the study employs structural equation modeling SEM to test the hypothesized relationships and assess the mediating roles of process automation, data quality, and system integration. The findings reveal that AI capability enhances real-time financial reporting both directly and indirectly through these mediating pathways, with system integration emerging as the most influential factor in translating AI investments into timely and reliable financial disclosures. By extending the resource-based view and information processing theory, the study demonstrates that the benefits of AI materialize only when digital resources are embedded into organizational routines, data infrastructures, and reporting workflows. Beyond its theoretical contributions, the research offers practical insights, showing that AI initiatives must be supported by robust data governance, automation of core accounting processes, and integrated financial systems to achieve meaningful improvements in reporting performance. For policymakers, the results underscore the importance of promoting data quality standards and encouraging unified, interoperable reporting ecosystems that enhance transparency and strengthen market confidence in AI-enabled financial reporting.</p>

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Artificial intelligence capability and real-time financial reporting: the mediating roles of automation, integration, and data quality

  • 期刊论文

  • 发表日期：

    2026年4月3日

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  • Khodor Shatila

摘要

This paper examines how artificial intelligence (AI) capability contributes to real-time financial reporting capability (RTFRC) within organizations, emphasizing the digital mechanisms that enable this transformation. Drawing on survey data from 320 accounting and finance professionals across diverse industries, the study employs structural equation modeling SEM to test the hypothesized relationships and assess the mediating roles of process automation, data quality, and system integration. The findings reveal that AI capability enhances real-time financial reporting both directly and indirectly through these mediating pathways, with system integration emerging as the most influential factor in translating AI investments into timely and reliable financial disclosures. By extending the resource-based view and information processing theory, the study demonstrates that the benefits of AI materialize only when digital resources are embedded into organizational routines, data infrastructures, and reporting workflows. Beyond its theoretical contributions, the research offers practical insights, showing that AI initiatives must be supported by robust data governance, automation of core accounting processes, and integrated financial systems to achieve meaningful improvements in reporting performance. For policymakers, the results underscore the importance of promoting data quality standards and encouraging unified, interoperable reporting ecosystems that enhance transparency and strengthen market confidence in AI-enabled financial reporting.