Digital Readiness for Artificial Intelligence Adoption in Islamic Cooperatives Financial Reporting

Abstract

This study examines the extent to which Artificial Intelligence (AI) has actually been adopted in the financial reporting process of Islamic savings, loan and financing cooperatives (KSPPS) in Pati Regency, assesses the implications of the systems currently in use for reporting transparency and accuracy, and identifies the barriers to and opportunities for future adoption. A descriptive qualitative field study was conducted at four KSPPS registered with PBMT Pati, namely KSPPS Yaumi MAS, KSPPS Harapan Umat (Harum), KSPPS Artha Bahana Syariah (ABS) and KSPPS BMT Berkah Al-Fath Mulia, selected purposively and extended through snowball sampling. Ten key informants (four managers, four finance staff and two IT staff, each with more than five years of service) were interviewed using a semi-structured protocol developed and validated through a focus group discussion. Interviews were complemented by direct observation of the reporting applications in use (Imf@, Artos System and Baraty) and by documentation of monthly reports, daily closing records and internal supervision documents. Data validity was tested through source, technique and time triangulation, and the data were analysed using the interactive model of Miles and Huberman. To avoid conflating digitalisation with AI, the study distinguishes AI implementation, defined as systems with learning, predictive or autonomous decision-making capability, from digital readiness for AI adoption, assessed through three enabling conditions: real-time data availability, algorithmic capability and computing power. The findings show that none of the four cooperatives has implemented AI in the strict sense; their systems perform rule-based recording, validation and reporting without learning or predictive functions. Three cooperatives display a high level of digital readiness because their systems are online, real time and integrated across branches, while one cooperative is at a moderate level because part of its operations remains manual and data are synchronised in batches. Real-time digitalisation is associated with more timely and more accessible reports and with fewer recording errors, yet typographical and duplicate input and manual cash reconciliation persist and these are precisely the areas in which AI could add value. Adoption is constrained by unstable connectivity, weak input validation, cybersecurity incidents, limited human resources and the absence of specific regulatory guidance. KSPPS in Pati Regency are therefore at a pre-adoption stage: the digital foundation is adequate, but realising the benefits of AI for transparent, accurate and sharia-accountable reporting requires deliberate investment, capacity building and regulatory support.