Exploration of AI in Ensuring Sharia Compliance in IF Institutions: Focus on Accounting Practices ()
1. Introduction
Artificial Intelligence (AI) technologies have been evolving at a very fast rate; their application in many fields has boosted their production, and the financial sector has not been exempted. Regarding IFIs, the institutions that abide by the rules and regulations of Sharia law, the use of AI are boons and banes. The need to maintain Sharia compliance, that is, the principle of not utilizing interest (Riba), excessive uncertainty (Gharar), and unethical investment in any of the institution’s activities may highly complicate the use of AI.
Accounting practices within IFIs are highly sensitive to Sharia compliance as they must respond to the ethical, moral, and religious foundations of Islamic finance. Monitoring and verification activities are an expansion direction with the aim of improving the accuracy of the Sharia compliance method using Artificial Intelligence. Nevertheless, the integration of AI and Sharia compliance comes with important ethical questions such as AI biases, algorithmic decisions, transparency, and most importantly, trust.
The importance of this theoretical analysis is to create the prospect of practical application of AI in the Islamic financing sector and improve the stability of these houses to the global audience. This study aims to theoretically explore the role of AI in ensuring compliance with Sharia within Islamic financial institutions’ accounting practices. The research questions guiding this theoretical exploration are as follows. How can AI be effectively integrated into accounting in Shariah-compliant Islamic financial institutions? What are the theoretical implications, benefits, and constraints of such an integration?
This study introduces a novel theoretical exploration of how AI can be effectively harnessed to ensure compliance with Sharia, specifically within Islamic financial institutions’ accounting practices. To the best of our knowledge, there is insufficient literature discussing the place and usage of AI in Islamic finance, although prior studies have covered the broad use of AI in the enhancement of finance. The remarkable aspect of this research is the investigation of Shariah-compliant AI integration, in addition to exploring ethical issues that are normally ignored in mainstream financial systems.
Furthermore, this study advances knowledge by discussing the potential of AI application in Islamic finance in the subsequent stage, highlighting the need for the authors to consider cultural factors, stakeholders’ trust, and the creation of ethical frameworks compliant with Sharia in the professional literature. To bridge the gap between technological advancements and religious compliance requirements, this study provides a framework that may help in the future direction and application of AI in IFIs, ensuring both innovation and adherence to fundamental ethical values.
2. Literature Review and Theoretical Framework
2.1. Conceptualization of AI in Sharia Compliance
AI is a branch of computer science that deals with designing software that exhibits cognitive abilities like humans; for instance, in solving problems, decision-making capability, and the ability to imitate cognitive human or physical actions. This can be considered a significant development over conventional information technology based on human logic (Rahman, & Ali, 2024).
In a financial context, AI covers predictive analysis, machine learning and training, and automation processes conduct and circumstances information, risk, decision analysis, and process optimization in real-time (Foster & Rhoden, 2020). Among these, capabilities of greater value in improving operational effectiveness are, for instance, that AI is useful in the fight against money laundering, focusing on the use of big data to detect unlawful activities, and to protect customer data in decentralized systems, which can exclude threats such as identity theft (Rani et al., 2023).
Simultaneously, Islamic finance can be viewed as a system that boasts certain features and solutions for solving socioeconomic development problems, complying with Sharia standards. This system offers a spectrum of innovative financial products with respect to social involvement and sound moral practices that would help create a sound and sustainable economic environment for different levels of government, corporate, and non-profit organizations (Ashraf, 2023). Technological enhancements, the application of Sharia laws, and the presence of many cultures make it challenging for Islamic finance to exist (Al-Okaily & Alsmadi, 2024).
Thus, the convergence of AI and Islamic finance presents an opportunity to harness technology while remaining aligned with Islamic principles. The use of AI technologies such as Natural Language Processing (NLP) and predictive analytics can enhance Sharia compliance by automating key tasks. NLP can be used to analyze financial documents and contracts to detect non-compliance with Sharia principles, such as the presence of Riba (usury) or Gharar (excessive uncertainty). This automation ensures contracts align with Islamic teachings by flagging potentially prohibited elements in real time.
Predictive analytics, on the other hand, can be used to forecast market trends or financial product outcomes based on historical data, ensuring that investments remain ethically sound and aligned with Sharia law (Malik & Khan, 2023). By predicting future risks or returns in accordance with Islamic principles, AI supports decision-making that prioritizes both financial growth and ethical standards.
Thus, AI technologies like NLP and predictive analytics not only enhance operational efficiency but also play a pivotal role in ensuring that financial practices remain compliant with Sharia requirements. This constructive collaboration between technology and Islamic finance reflects how AI can address socio-economic challenges while adhering to cultural, legal, and ethical considerations.
2.2. Integration of AI in Accounting Practices
The application of AI in accounting systems, as well as the rules and regulations of Sharia in accounting, establish a symbiotic relationship between financial stability and technological advancement. Advancements in technology, especially in the current digital world, where many administrative functions are being automated in financial institutions and the corporate world, accounting has not been left behind; it has become not only the mechanical process of writing down financial transactions, but also a very important tool in the strategic management and decision-making process (Agarwal et al., 2023). The use of present-day technologies, such as Artificial Intelligence, enhances the efficiency and accuracy of such responsibilities. Consequently, the quality of financial analyses and reports increases organizational performance and competitiveness in business circles. Nonetheless, such a swift process of digital transformation is not without problems; these are issues associated with security, privacy, reliability, and shifts in organizational structures and cultures (Suzuki & Dulal Miah, 2022; Altaf et al., 2022).
AI is widely used in many accounting practices including auditing, data analysis, big data, and risks. For instance, integrated and expressed auditing employs electronic audit dimensions and criteria such as relevance, efficiency, sufficiency, and timeliness to improve the accuracy and legitimacy of financial information. Not only does it enhance the quality of data input, but it also decreases auditors’ fees because of the application of electronic auditing tools (Hashem, 2023; Murphy et al., 2024). Another process improvement technique specifically for an audit is the use of robotic process automation (RPA), which involves repetitive work in which the robot searches for irregularities and brings them to the auditor’s attention (Dotel, 2020; Azhar & Hassan, 2024).
Despite AI’s advanced capabilities and adaptation, it still does not boast of being truly independent and free, but rather of being a measure dependent on certain norms set down by human fraternity. Therefore, decision-making must be a joint effort of humans and AI systems; thus, governance, internal and external audits, and governance must be developed to guarantee ethical decision making (Lehner, 2022). It can be described as transformative how contemporary enterprises and incumbents, in particular, have been influenced by AI and big data. Big data implies the availability of a large amount of extensive and diverse data, which AI-aided tools and gizmos allow for quick, competent, and plausible data analyses. Regarding risk management, AI performs an effective function in the banking and finance sectors in terms of risk minimization, operational cost control, customer satisfaction, compliance and regulation, credit assessment, loan granting, and accurate financial forecasting (Mer et al., 2024; Khafaga, 2024).
In Islamic finance, AI helps investors select and evaluate Shariah-compliant investment opportunities to entrust the management of their portfolios to professionals who will invest in accordance with Islamic laws (Al-Shalhoob, 2023). Islamic financial institutions follow the rules set by AAOIFI and IFSB in consultation with scholars and experts in the field. Nonetheless, the integration of AI into compliance with Sharia in these institutions has been controversial.
AI supporters have claimed to improve its efficiency and effectiveness in determining Sharia compliance with increased accuracy, augmented by its ability to manage large volumes of data in the shortest time. In addition, some anticipate that AI will spur innovation in Islamic finance by developing new financial products and services, as required by the market, under Shariah laws to address changing customer demands (Karim & Hassan, 2019; Zain & Habib, 2018; Saad, 2024).
In contrast, the use of AI in Sharia compliance comes with moral issues raised by critics. They believed that there was a risk that AI could make decisions without the knowledge needed to understand the complexity and difficult issues of Sharia standards. They emphasized the importance of proper monitoring using AI technologies and the ethical considerations that should be in place (Foster & Rhoden, 2020). In addition, there are also those who fear that AI adoption could diminish the cultural and religious values inherent to Sharia compliance. Critics also point out that AI has no capacity to comprehend and interpret the nature of Sharia law, which is context specific and complex. This is one of the reasons why some people are still not satisfied with the idea of AI usage in Islamic financial organizations, in cooperation with the fact that only large enterprises have the ability and technology to create complex AI systems. Smaller Islamic organizations that might be less well-financed and have fewer technical resources are likely to have a harder time implementing AI technology in their institutions (Rahman, 2021; Karim & Hassan, 2019).
One way of looking at this is that AI should be used as the first-line tool for human decision-making, the subsequent backup planning for incomplete decisions, and a tool that makes the entire process of Shariah compliance paperless. This instrumental dimension is a blend of AI efficiency, human capabilities, and the ethical dimensions of the full utilization of AI in Islamic finance. Thus, there is a dual improvement in both efficiency and adherence to the Shairia principles (Lehner, 2022; Arora & Sharma, 2023).
2.3. Ethical Considerations
The integration of AI with compliance with Sharia as an Islamic financial institution raises several theoretical ethical considerations. Banking and financial firms must ensure that AI technologies are consistent with Islamic finance values and principles.
The similarity between AI systems and Sharia principles is crucial. The fundamental principles of Islamic finance include justice, transparency, and ethics. As Ahmad and Shabbir (2018) emphasize, the integration of technology, including AI, must be in line with these principles to ensure the integrity of Sharia compliance. It is the moral principles set by Islamic finance that should guide the development of AI-powered solutions and actions, to guarantee that technology does not interfere with the moral mainstay of Islamic finance.AI must act in a transparent and accountable manner to use the technology ethically. For instance, AI systems required to operate in such a way that stakeholders understand the decision-making process are provided to instill trust. Rahman (2021) highlighted that God is a God of clarity; therefore, Sharia-compliant financial practices must be transparent to all parties (Rahman, 2021). This point is made evident by the fact that AI technologies must ensure that the processes and transactions involved in financial affairs are transparent and accessible to all parties, so that trust and accountability can be maintained (Virdhagriswaran & Kumar 2022; Johnsson & Persson, 2021).
Bias and fairness are no less than serious pitfalls of ethics. AI algorithms may mix and introduce surface biases that affect the impartial treatment of some groups. Karim and Hassan (2019) presented a case of an ethical dilemma posed by biases in AI algorithms. If we look at Islamic finance, where fairness and justice are of primary importance, we must perform a thorough test and study of bias; if any is present, it should be eliminated by AI systems to ensure that they produce unbiased outcomes and uphold ethical standards.
AI management considers ethical issues such as privacy and data protection. In addition, Islamic banks should ensure that AI systems follow Sharia principles such as respecting the privacy of individuals and protecting sensitive data. Abdullah and Chee (2020) warned that data downtime and control are sources of data problems and should be the focus of ethical AI use and implementation. These are the bases for autonomous AI development systems and the frameworks of data governance that will ensure that the data offer is managed in a Sharia-compliant manner. as the ethical usage of its capacity, based on the principles of consent and autonomy. Stakeholders must consent to using AI in their financial decisions. Zain and Habib (2018) dedicate their attention to the necessity of informed consent, which is the same as Sharia’s ethical requirements. As part of Sharia improv, these institutions should ensure that customers and stakeholders know what AI systems are used and what their implementation entails in relation to human life. AI systems must have a positive impact on society, as this is one of Sharia’s main points of social responsibility. The introduction of AI must have a positive impact on a society’s well-being and justice; otherwise, the outcome will be negative. Iqbal and Mirakhor (2017) claimed that the Islamic financial system was designed to promote social justice and responsibility. Therefore, AI technologies should be used as instruments to foster the welfare of society and prevent societal challenges (Hashem, 2023).
3. Methodology
3.1. Research Approach
Before this study employs a qualitative content analysis approach, utilizing secondary data sources to explore the integration of AI in Sharia compliance within Islamic finance. The research aims to identify key themes, trends, and challenges related to AI adoption in Islamic financial institutions (IFIs), with a particular focus on accounting practices, compliance monitoring, and ethical considerations. To ensure a structured and replicable analysis, the study applies thematic coding to extract insights from various sources.
3.2. Data Collection
The study relies on peer-reviewed journal articles, industry reports, regulatory guidelines, and case studies that discuss AI’s role in automating compliance, fraud detection, and financial decision-making. The data sources include academic literature, such as journal articles and conference papers published between 2016-2024 that examine AI applications in Islamic finance. Additionally, regulatory reports from institutions like AAOIFI (Accounting and Auditing Organization for Islamic Financial Institutions) and IFSB (Islamic Financial Services Board) provide insights into AI adoption within compliance frameworks. The study also incorporates industry case studies, particularly those from IFIs implementing AI-powered compliance solutions, such as Wahed Invest and Dubai Islamic Bank, to illustrate real-world applications.
To ensure the credibility and relevance of the data, the selection criteria required that sources be directly related to AI in Islamic finance, published in reputable academic or industry outlets, and recent (2016-2024) to reflect evolving trends. This diverse dataset allows for a comprehensive evaluation of AI’s impact on compliance, operational efficiency, and ethical considerations.
3.3. Thematic Coding Framework
To systematically analyze the literature, a thematic coding approach was employed, categorizing key insights into five primary themes:
AI in Sharia Compliance: Examines how AI tools assist in ensuring Islamic financial products adhere to Riba-free and ethical investment principles.
AI for Risk & Fraud Detection: Explores AI’s role in identifying fraud, money laundering, and compliance violations in IFIs.
AI-Based Decision Support: Focuses on the use of predictive analytics and natural language processing (NLP) to enhance Sharia-compliant investment recommendations.
Ethical Considerations: Highlights challenges such as bias, fairness, data privacy, and transparency in AI-driven compliance mechanisms.
Regulatory & Institutional Challenges: Investigates barriers to AI adoption in IFIs, including regulatory constraints, resource limitations, and governance concerns.
To illustrate how thematic coding was applied, a case study from Wahed Invest was categorized under “AI-Based Decision Support”, as it employs machine learning algorithms to optimize Sharia-compliant investment portfolios. Similarly, regulatory discussions from AAOIFI and IFSB reports were coded under “Regulatory & Institutional Challenges”, highlighting key policy constraints on AI integration in IFIs. To enhance reliability, multiple researchers conducted cross-validation of the coding framework, minimizing subjective bias and ensuring consistency in thematic identification.
3.4. Data Analysis Process
The thematic analysis followed a structured four-step process to ensure a systematic and replicable approach:
Data Familiarization: The research team reviewed 30+ scholarly papers, regulatory documents, and case studies to gain a comprehensive understanding of AI in Islamic finance.
Initial Coding: Text segments were assigned to predefined themes (e.g., “AI for Risk & Fraud Detection”) to identify relevant insights.
Theme Refinement: Overlapping patterns were analyzed, and common findings were consolidated into major thematic categories.
Validation & Interpretation: The findings were compared against existing Islamic finance frameworks to ensure they aligned with Sharia compliance principles.
While the primary focus of this study is qualitative analysis, the research also incorporates quantitative elements, particularly in reviewing AI adoption trends. Empirical case studies measuring AI’s impact on fraud detection accuracy and cost reduction in IFIs further strengthen the analysis. For instance, studies show that AI-driven fraud detection systems in IFIs have improved fraud detection rates by over 90% while reducing operational costs. This integration of qualitative and quantitative insights ensures a comprehensive understanding of AI’s potential in Islamic finance.
3.5. Ethical Considerations in AI Implementation
As AI becomes increasingly integrated into Islamic financial systems, ethical considerations remain critical. This study examines key ethical concerns, including data privacy, algorithmic bias, and transparency in decision-making. Literature from Ahmad & Shabbir (2018) highlights the need for AI-driven financial systems to align with Islamic ethical standards, ensuring fairness and justice. Additionally, Abdullah & Chee (2020) emphasize the importance of data governance in protecting privacy within AI-powered IFIs. The study also considers bias mitigation strategies to ensure AI systems do not unintentionally discriminate against certain financial transactions or investors.
4. Result and Discussion
After the integration of artificial intelligence (AI) in Islamic finance has significantly transformed financial monitoring, verification, and compliance, ensuring that financial practices align with ethical and legal standards as prescribed by Sharia law. AI-driven tools enhance credibility and operational efficiency, contributing to the achievement of Sustainable Development Goals (SDGs) (Aysan et al., 2024). In Islamic finance, AI improves accountability by automating compliance checks, reducing manual workload, and enhancing audit accuracy. For instance, Dubai Islamic Bank has implemented AI-powered compliance solutions to screen transactions against Sharia principles, ensuring that financial activities remain free from Riba (interest), Gharar (excessive uncertainty), and haram investments (Walton, 2024).
Moreover, AI’s predictive analytics capabilities significantly enhance risk assessment and decision-making in Islamic finance. Predictive models can assess market trends, allowing Islamic financial institutions (IFIs) to anticipate risks while adhering to profit-and-loss sharing principles. For example, Wahed Invest, an Islamic fintech firm, leverages machine learning algorithms to offer Sharia-compliant robo-advisory services, optimizing investment portfolios while adhering to AAOIFI standards (Mansoori & Sadeghi, 2023). Additionally, natural language processing (NLP) enables AI systems to analyze vast amounts of Sharia fatwas, contracts, and legal texts, structuring them into actionable compliance rules, thereby reducing human errors in financial decision-making (Saad, 2024).
One of AI’s most critical applications in Islamic finance is its ability to detect fraud and financial misconduct while ensuring compliance with Sharia law. Traditional fraud detection methods rely on manual auditing and slow verification processes, which are often prone to human error and inefficiency. AI, on the other hand, employs real-time fraud detection algorithms that analyze transaction patterns and flag suspicious activities (Giacalone, 2022).
For instance, Malaysia’s CIMB Islamic Bank has adopted AI-driven fraud detection systems that monitor real-time transactions, automatically identifying potential Sharia violations such as hidden interest payments or speculative trading. Similarly, AI-powered chatbots and virtual assistants in Islamic banks guide consumers in making Sharia-compliant investment decisions, ensuring that their financial choices align with Islamic ethical values (Osei-Assibey Bonsu et al., 2023).
Furthermore, blockchain-based smart contracts, powered by AI automation, ensure compliance with Sharia principles by minimizing human error and improving contract transparency. For example, the UAE’s Emirates Islamic Bank has integrated AI with blockchain to automate Sharia-compliant sukuk issuance, ensuring that contracts adhere to Islamic law in a fully transparent manner (Zafar & Khalid, 2024).
Despite its benefits, AI adoption in Sharia-compliant finance faces several challenges. A primary concern is the dependence on high-quality data, as AI systems require large, diverse, and well-structured datasets to function accurately. In Islamic finance, Sharia compliance decisions are highly context-specific and require nuanced interpretations from scholars. Inadequate training datasets could lead to misinterpretations and non-compliance issues. For example, AI models trained on Western financial datasets may not fully understand Sharia restrictions on interest-based transactions, leading to potential classification errors (Walton, 2024; Elmarzouky et al., 2021).
Additionally, a technological divide exists between large, resource-rich IFIs and smaller institutions, limiting AI adoption in less-developed Islamic finance markets. Large banks such as Dubai Islamic Bank can afford advanced AI-driven compliance solutions, while smaller Islamic financial institutions struggle with limited funding, technical expertise, and infrastructure (Santos & Luengo, 2024). This disparity risks excluding smaller players from benefiting from AI-powered Sharia compliance tools, creating unequal access to technological advancements in the sector.
Another major limitation is the “black box problem” the opacity of AI algorithms, which conflicts with Sharia principles of transparency and accountability. Stakeholders in Islamic finance may hesitate to trust AI-driven compliance decisions if the reasoning behind those decisions is unclear. For instance, if an AI system flags a transaction as non-compliant, IFIs must be able to trace the decision-making process to verify its alignment with Islamic law. Without explainable AI (XAI) solutions, regulatory oversight becomes challenging, hindering AI adoption in Islamic finance governance frameworks (Zain & Habib, 2018).
AI adoption in Islamic financial systems raises ethical dilemmas concerning bias, fairness, and privacy. AI models may inadvertently incorporate biases that impact Sharia-compliant financial decisions, especially if the training data is skewed or lacks diversity (Abdullah & Chee, 2020). To mitigate these risks, Islamic financial institutions must conduct rigorous AI bias testing and implement fairness algorithms to ensure compliance with Islamic ethical standards.
Privacy concerns are another critical issue in AI-powered Islamic finance. Sharia law emphasizes individual privacy and data protection, requiring that AI-driven systems adhere to strict ethical guidelines regarding customer data handling. For example, Islamic fintech firms in Indonesia and Malaysia have implemented AI-based biometric authentication systems, ensured secure transactions while protected customer privacy (Ahmad & Shabbir, 2018).
Governance frameworks must also be established to provide clear ethical guidelines for AI use in Islamic finance. AI systems should incorporate explainable AI (XAI) models, ensuring that Sharia compliance decisions are transparent and traceable. Additionally, Islamic scholars, regulators, and AI experts must collaborate to develop AI governance models aligned with Islamic financial ethics (Hussain & Al-Awadhi, 2024).
To overcome AI-related challenges in Islamic finance, IFIs must adopt a balanced strategy that integrates technological innovation with robust ethical safeguards. AI models should be specifically tailored for Sharia compliance, incorporating clear rule-based algorithms that reflect Islamic legal principles.
A critical step in achieving this is developing AI training datasets specific to Islamic finance. For example, AAOIFI and IFSB should collaborate with AI researchers to create Sharia-compliant financial datasets, ensuring that AI models accurately reflect Islamic laws. Additionally, IFIs should implement explainable AI techniques, such as decision-tree-based machine learning, to improve algorithm transparency and enhance stakeholder trust.
Efforts must also be made to bridge the AI adoption gap between large and small IFIs. Governments and regulatory bodies could introduce AI adoption incentives, such as subsidized AI compliance tools for smaller Islamic financial institutions. Moreover, open-source AI solutions for Sharia compliance could help democratize AI accessibility across the industry (Sakurai & Urano, 2023).
AI has the potential to revolutionize Sharia-compliant finance, enhancing transparency, risk management, and compliance monitoring. By automating fraud detection, contract verification, and investment screening, AI strengthens Islamic finance governance while reducing operational inefficiencies. However, ethical, regulatory, and data-related challenges must be carefully addressed to ensure that AI aligns with Sharia principles of fairness, transparency, and accountability. The integration of explainable AI models, ethical governance frameworks, and AI-specific Islamic financial datasets will be crucial in ensuring responsible AI adoption in IFIs. As the industry evolves, AI-driven innovations will play a pivotal role in shaping the future of Islamic finance.
5. Conclusion
This study examines the use of artificial intelligence (AI) in accounting practices within Islamic financial institutions with a specific focus on its contribution to shipping compliance. The theoretical findings substantiate the importance of AI in boosting the efficiency and accuracy of compliance monitoring and auditing. Different predictive analytics, NLP, and auditing systems may help follow Sharia rules by automizing and optimizing detailed procedures. The analysis of large volumes of information in real time enhances the identification of noncompliant transactions and involves AI-based risk management. Nevertheless, the incorporation of AI in accounting practices in Sharia-compliant organizations depends on the resolution of other primary issues, such as the quality of data, the ability to interpret large datasets, and the extent of the disclosure of operations of the artificial intelligence system.
The implications of this study add to the theoretical knowledge regarding the engagement of AI in compliance with Sharia in the following ways. First, it shows that AI can revolutionize how compliance issue monitoring and compliance can be performed without the errors and biases of human beings while also being more open to Sharia compliance. The adoption of AI in accounting helps provide a rational solution over conventional accounting techniques, which is still largely a manual effort and erroneous. Other theoretical advancements have also been made in the ability to apply NLP techniques to understand complicated Sharia texts and to enhance compliance validation. In addition, this work provides insights for furthering the understanding of AI’s drawbacks of AI, including data bias, the opulence of Sharia law, and ethical issues that are vital for comprehending the interim results of applying AI in the given setting. This will help establish new paradigms in the industry, including shaping how Islamic financial institutions conduct the adoption and implementation of technology in line with global ethical legal requirements across the world. AI is still developing, but its impact on increasing Sharia compliance can be regarded as the standard for how new regulations and technology should be incorporated when there are religious concerns.
Future research on AI use and the application of Shariah compliance in IFIs should explore several theoretical frameworks, particularly from an accounting perspective. Another unexplored field that may be of interest is training new, complex AI to cope with the complex legal interpretations that are part of Sharia. Some of the ramifications of these systems would include recognizing different culturally related views or various legal system classifications where needed to ensure that AI can respond to the shift in interpretations regarding the law but, in the same manner, stay lawfully sound in its approaches to accounting. It could improve the way IFIs practice the applications of Artificial Intelligence in its financial and accounting aspects, as well as the general framework that would guarantee Sharia compliance. There is also another direction in which considerable attention should be paid in future, namely, the question of the extent and methodologies of explicability of AI-controlled systems. Hence, stakeholders in the Shariah sensitive areas of financial transactions to trust AI need to be able to explain how it came about to the decision. More research should be dedicated to how such transparency can be improved, such as in accounting, and its impact on stakeholder confidence. The practical, technical, and theoretical methodological concepts of transparency regarding AI integration in Islamic finance may depend heavily on understanding and discharging the emerging ethical implications associated with its use. Therefore, the identification of the current state of ethical considerations regarding AI application in Islamic finance is also valuable, as are research recommendations highlighting the ethical frameworks that exist within the use of AI in IF. It might be helpful to examine how managerial decision making and the attitudes of stakeholders, such as customers, regulatory bodies, and sources of Islamic teaching, are affected by AI. This line of inquiry is particularly appropriate given that ethical issues are very sensitive, especially in accounting. By studying the ethics of using AI, experts can determine how to implement these technologies within Islamic finance to ensure the trust of direct stakeholders.