Artificial Intelligence in Accounting and Financial Reporting: A Systematic Literature Review and Research Agenda
DOI:
https://doi.org/10.54518/rh.6.3.2026.1132Keywords:
Artificial intelligence, Auditing, Financial Reporting, Large Language Models, Systematic Literature ReviewAbstract
Artificial intelligence has rapidly transformed accounting practices through advanced digital technologies worldwide. This study aims to systematically review the literature on AI applications in accounting and financial reporting, mapping dominant technologies, documented impacts, and critical research gaps. A Systematic Literature Review following PRISMA 2020 guidelines was conducted using Scopus and Web of Science without year restriction. After a four-stage screening process, 25 peer-reviewed articles published in 2025–2026 were retained for thematic synthesis, guided by Agency Theory, the Resource-Based View, and the Technology Acceptance Model. Large Language Models (LLMs) and generative AI are the most prominent technologies applied across financial reporting, auditing, education, and corporate disclosure. Ensemble methods dominate fraud detection and financial distress prediction, while Graph Neural Networks represent an emerging frontier in relational fraud analysis. AI yields measurable improvements in reporting accuracy, audit efficiency, and sustainability accounting; however, critical challenges persist, including LLM hallucination, explainability gaps, regulatory lag, and limited evidence from developing economies. This review is among the first to synthesize AI applications in accounting within the post-generative AI era (2025–2026), integrating evidence across LLMs, GNNs, and explainable AI, and proposing a theoretically grounded research agenda that extends beyond prior bibliometric and domain-specific reviews.
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References
Adelakun, B. O. (2023). AI-driven financial forecasting: Innovations and implications for accounting practices. International Journal of Advanced Economics, 5(9), 323-336. https://doi.org/10.51594/ijae.v5i9.1231.
Adelakun, B. O., Onwubuariri, E. R., Adeniran, G. A., & Ntiakoh, A. (2024). Enhancing fraud detection in accounting through AI: Techniques and case studies. Finance & Accounting Research Journal, 6(6), 978-992. https://doi.org/10.51594/farj.v6i6.1232.
Adeyelu, O. O., Ugochukwu, C. E., & Shonibare, M. A. (2024). Ethical implications of AI in financial decision-making: A review with real-world applications. International Journal of Applied Research in Social Sciences, 6(4), 608-624.
Ahmad, A. Y. A. B. (2023). Ethical implications of artificial intelligence in accounting: A framework for responsible AI adoption in multinational corporations in Jordan. International Journal of Data and Network Science, 8(1), 401-416. https://doi.org/10.5267/j.ijdns.2023.9.014.
Ahmed, D. B. (2026). The impact of artificial intelligence on accounting information and earnings management: Bibliometric analysis. Journal of Risk and Financial Management, 19(1), 90-104. https://doi.org/10.3390/jrfm19010090.
Alassuli, A., Eltweri, A., Thuneibat, N. S., Al-Hajaya, K., & Ismail, S. M. (2026). Artificial intelligence applications and financial forecasting accuracy in banking platforms: Evidence from Jordan. Administrative Sciences, 16(1), 122-140. https://doi.org/10.3390/admsci16030122.
Almarri, S. O., Alotaibi, E., Khallaf, A., Gleason, K. C., & Abdallah, A. A. (2025). The impact of digital transformation on accounting information systems: Evidence from the aviation industry of the United Arab Emirates. International Journal of Data and Network Science, 9(4), 751-764. https://doi.org/10.5267/j.ijdns.2025.8.009.
Alnesafi, A. (2025). Overview of AI-powered predictive analytics in audits: Perspective evidence from Kuwait auditors. International Journal of Data and Network Science, 9(3), 395–410. https://doi.org/10.5267/j.ijdns.2025.4.001.
Alwanin, R., Ben Ismail, M. M., & Bchir, O. (2025). Customs fraud detection using a gradient boosting approach for joint classification and risk estimation. Scientific Reports, 16(1), 3432-3450.
Antwi, B. O., Adelakun, B. O., & Eziefule, A. O. (2024). Transforming financial reporting with AI: Enhancing accuracy and timeliness. International Journal of Advanced Economics, 6(6), 205-2018.
Arian, A., Timilsina, S., Gamage, P., & Sands, J. (2025). Cultural governance and earnings quality: The role of corporate values and managerial ability. Journal of Business and Socio-economic Development, 6(2), 109–130. https://doi.org/10.1108/JBSED-07-2025-0321.
Aruwaji, M. A., & Swanepoel, M. J. (2025). The impact of AI-Integrated ESG reporting on firm valuation in emerging markets: a multimodal analytical approach. Journal of Risk and Financial Management, 18(12), 675-687. https://doi.org/10.3390/jrfm18120675.
Barney, J. (1991). Firm resources and sustained competitive advantage. Journal of Management, 17(1), 99–120. https://doi.org/10.1177/014920639101700108.
Bednárová, M. (2025). ESG reporting and communication. In Environmental, social, and governance (ESG) investment and reporting (pp. 175-202). Cham: Springer Nature Switzerland.
Boiță, M., Dumiter, F. C., Loučanová, E., Păiușan, L., Pribeanu, G., & Milutin, I. M. (2026). AI-enabled management of transfer pricing documentation: A sustainable governance framework integrating compliance, digitalization, and CSRD requirements. Sustainability, 18(1), 2528-2540. https://doi.org/10.3390/su18052528.
Bonsu, M. O., Wang, Y., & Guo, Y. (2023). Does fintech lead to better accounting practices? Empirical evidence. Accounting Research Journal, 36(1), 129-144. https://doi.org/10.1108/ARJ-07-2022-0178.
Carollo, M., Lauri, L., Bardozzo, F., Cafaro, E. M., D’Alessio, R., & Tagliaferri, R. (2026). Exploring the efficiency of GPT models in automating trial balance mapping: Applications and insights. Soft Computing, 30(1), 1693–1709. https://doi.org/10.1007/s00500-025-10983-4.
Croom, J. (2026). Interactivity and illusions of ability: How using generative AI affects investor judgments. Journal of Accounting Research, 64(1), 681–719. https://doi.org/10.1111/1475-679X.70017Digital.
Darmawati, D., Jaafar, N. I., HS, R., Baja, H. K., Purisamya, A. J., Yolanda, A. M. W., Amir, B., & Juanda, M. R. P. (2025). The role of artificial intelligence in improving the efficiency and accuracy of local government financial reporting: A systematic literature review. Journal of Risk and Financial Management, 18(11), 601-614. https://doi.org/10.3390/jrfm18110601.
Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–340. https://doi.org/10.2307/249008.
El Aziz, O., & Asdiou, A. (2025). AI-powered analysis of ESG disclosure: a clustering approach to determinants and motivations. Future Business Journal, 11(1), 197-210. https://doi.org/10.1186/s43093-025-00623-6.
Elnakeeb, S., & Elawadly, H. S. H. (2025). Automation and artificial intelligence in accounting: A comprehensive bibliometric analysis and future trends. Journal of Financial Reporting & Accounting, 11(1), 103-116. https://doi.org/10.1108/JFRA-09-2024-0639.
Eulerich, M., Sanatizadeh, A., Vakilzadeh, H., & Wood, D. A. (2024). Is it all hype? ChatGPT’s performance and disruptive potential in the accounting and auditing industries. Review of Accounting Studies, 29(3), 2318-2330. https://doi.org/10.1007/s11142-024-09833-9.
Ewertz, J., Knickrehm, C., Nienhaus, M., & Reichmann, D. (2026). Listen closely: Measuring vocal tone in corporate disclosures. Journal of Accounting Research, 64(1), 229.–277. https://doi.org/10.1111/1475-679X.70015
Fedyk, A., Hodson, J., Khimich, N. V., & Fedyk, T. (2022). Is artificial intelligence improving the audit process?. Review of Accounting Studies, 27(3), 938-985. https://doi.org/10.1007/s11142-022-09697-x.
Fristamara, Y., Irianti, D. I., & Werastuti, D. N. S. (2025). Peran SIMAN memediasi pengaruh kompetensi sumber daya manusia terhadap kinerja pengelolaan aset negara pada KPKNL Singaraja. Stratēgo: Jurnal Manajemen Modern, 7(1), 312–331.
Fülöp, M. T., Topor, D. I., Ionescu, C. A., Cifuentes-Faura, J., & Măgdaș, N. (2023). Ethical concerns associated with artificial intelligence in the accounting profession: A curse or a blessing? Journal of Business Economics and Management, 24(2), 387-402. https://doi.org/doi:10.3846/jbem.2023.19251.
Gabrielli, G., Melioli, A., & Bertini, F. (2025). Corporate financial distress prediction: A machine learning approach in the era of big data. Journal of Accounting & Organizational Change, 22(7), 31–65. https://doi.org/10.1108/JAOC-05-2025-0166.
Haidar, F. T., & Alyousef, M. A. (2026). Investigating behavioral and technical factors influencing faculty adoption of ChatGPT in accounting education. Discover Education, 5(1), 318-332. https://doi.org/10.1007/s44217-026-01309-z.
Hajek, P., Novotny, J., & Munk, M. (2026). Financial statement fraud detection using topic-driven financial sentiment analysis. Decision Support Systems, 203(1), 114-1132. https://doi.org/10.1016/j.dss.2026.114615.
Han, H., Shiwakoti, R. K., Jarvis, R., Chima, J. S., & Botchie, D. (2022). Accounting and auditing with blockchain technology and artificial intelligence: A literature review. International Journal of Accounting Information Systems, 48(2), 598-612. https://doi.org/10.1016/j.accinf.2022.100598.
Hemayani, N. M. I., & Dewi, L. G. K. (2021). Pengaruh good corporate governance, corporate social responsibility, dan corporate financial performance terhadap nilai perusahaan. JIMAT (Jurnal Ilmiah Mahasiswa Akuntansi), 12(3), 781–793. https://doi.org/10.23887/jimat.v12i3.34614.
Iwuanyanwu, U., Apeh, A. J., Adaramodu, O. R., Okeleke, E. C., & Fakeyede, O. G. (2023). Analyzing the role of artificial intelligence in IT audit: Current practices and future prospects. Computer Science & IT Research Journal, 4(2), 54-68. https://doi.org/10.1007/s44163-026-00977-y.
Jensen, M. C., & Meckling, W. H. (1976). Theory of the firm: Managerial behavior, agency costs and ownership structure. Journal of Financial Economics, 3(4), 305–360. https://doi.org/10.1016/0304-405X(76)90026-X.
Jones, S., & Free, C. (2026). What accountants need to know about artificial intelligence and machine learning: A review and call for future research. Journal of Accounting Literature, 48(1), 133-148. https://doi.org/10.1108/JAL-12-2025-0693.
Julianto, I. P., Yasa, P. I. N., & Devi, S. (2019). The analysis of Technology Acceptance Model (TAM) on the use of accounting information system. Advances in Economics, Business and Management Research, 69(1), 276–280. https://doi.org/10.2991/teams-18.2019.48.
Juma’h, A. H., Chuang, M., & Harfouche, A. (2026). Integrating AI into financial reporting and investment: multi-layered framework. Journal of Decision Systems, 35(1), 264-278. https://doi.org/10.1080/12460125.2026.2645969.
Kassar, M., & Jizi, M. (2025). Artificial intelligence and robotic process automation in auditing and accounting: A systematic literature review. Journal of Applied Accounting Research, 27(1), 217-241. https://doi.org/10.1108/JAAR-05-2024-0175.
Khan, S., & Gupta, S. (2025). Boosting the efficacy of green accounting for better firm performance: artificial intelligence and accounting quality as moderators. Meditari Accountancy Research, 33(2), 472-496. https://doi.org/10.1108/MEDAR-02-2024-2379.
Kokina, J., Blanchette, S., Davenport, T. H., & Pachamanova, D. A. (2025). Challenges and opportunities for artificial intelligence in auditing: Evidence from the field. International Journal of Accounting Information Systems, 56(1), 734-748. https://doi.org/10.1016/j.accinf.2025.100734.
Kumar, N., Agarwal, P., Gupta, G., Tiwari, S., & Tripathi, P. (2024). AI-Driven financial forecasting: the power of soft computing. In Intelligent optimization techniques for business analytics (pp. 146-170). Pennsylvania: IGI Global Scientific Publishing.
Kureljusic, M., & Karger, E. (2023). Forecasting in financial accounting with artificial intelligence: A systematic literature review and future research agenda. Journal of Applied Accounting Research, 25(1), 81-94. https://doi.org/10.1108/JAAR-06-2022-0146.
Leitner-Hanetseder, S., Lehner, O. M., Eisl, C., & Forstenlechner, C. (2021). A profession in transition: Actors, tasks and roles in AI-based accounting. Journal of Applied Accounting Research, 22(3), 539-552. https://doi.org/10.1108/JAAR-10-2020-0201.
Leitner-Hanetseder, S., Perkhofer, L., Frenkenberger, S., & Eisl, C. (2025). ChatGPT as digital accounting assistant: Evaluating output performance in financial accounting tasks. International Journal of Accounting & Information Management, 34(2), 330-361. https://doi.org/10.1108/IJAIM-01-2025-0017.
Li, W., Liu, W., Deng, M., Liu, X., & Feng, L. (2025). The impact of large language models on accounting and future application scenarios. Journal of Accounting Literature, 7(2), 78-80. https://doi.org/10.1108/JAL-12-2024-0357.
Ma, X. (2026). Detection of false financial statements in enterprises based on dual-layer knowledge graph and graph-driven approach. Discover Artificial Intelligence, 6(1) 298-310.
Murphy, B., Feeney, O., Rosati, P., & Lynn, T. (2024). Exploring accounting and AI using topic modelling. International Journal of Accounting Information Systems, 55(2), 709-724. https://doi.org/10.1108/JAL-12-2025-0693.
Nwachukwu, P. S., Chima, O. K., & Okolo, C. H. (2025). The artificial intelligence governance framework for finance: A control-by-design approach to algorithmic decision-making in accounting. Finance & Accounting Research Journal, 7(8), 350-362.
Omowole, B. M., Omokhoa, H. E., Ogundeji, I. A., & Achumie, G. O. (2022). Dynamic risk modeling in financial reporting: Conceptualizing predictive audit frameworks. International Journal of Social Science Exceptional Research, 1(1), 158-172.
Page, M. J., McKenzie, J. E., Bossuyt, P. M., Boutron, I., Hoffmann, T. C., Mulrow, C. D., Shamseer, L., Tetzlaff, J. M., Akl, E. A., Brennan, S. E., Chou, R., Glanville, J., Grimshaw, J. M., Hróbjartsson, A., Lalu, M. M., Li, T., Loder, E. W., Mayo-Wilson, E., McDonald, S., ... Moher, D. (2021). The PRISMA 2020 statement: An updated guideline for reporting systematic reviews. BMJ, 372(1), 71-95. https://doi.org/10.1136/bmj.n71.
Piven, A. (2023). Analysis of financial reports in companies using machine learning. Financial Markets Institutions and Risks, 7(4), 135-148. https://doi.org/10.61093/fmir.7(4).135-154.2023.
Putri, K. A. M. P., Yasa, I. N. P., & Wahyuni, M. A. (2018). Pengujian Technology Acceptance Model (TAM) terhadap kepatuhan wajib pajak pengguna SAMSAT Online. JIMAT (Jurnal Ilmiah Mahasiswa Akuntansi), 9(2), 17–30. https://doi.org/10.23887/jimat.v9i2.20411.
Qatawneh, A. M. (2025). The role of artificial intelligence in auditing and fraud detection in accounting information systems: moderating role of natural language processing. International Journal of Organizational Analysis, 33(6), 1391-1409. https://doi.org/10.1108/IJOA-03-2024-4389.
Rezig, K., Alshehadeh, A. R., Al-Qerim, I., & Kourtel, F. (2025). The impact of artificial intelligence tools on accounting profession challenges: an empirical study of financial brokerage companies in Jordan. In Conference on Sustainability and Cutting-Edge Business Technologies (pp. 85-95). Cham: Springer Nature Switzerland
Roos, D., Schlegel, D., & Kraus, P. (2025). Adopting artificial intelligence in accounting: Prerequisites and applications. Journal of Electronic Business & Digital Economics, 4(2), 374-388. https://doi.org/10.1108/JEBDE-03-2025-0023.
Sarna, N. J., Rithen, F. A., Jui, U. S., Belal, S., Amin, A., Oishee, T. K., & Islam, A. M. (2025). AI driven fraud detection models in financial networks: A Review. IEEE Access, 13(1), 134-152.
Sherif, K., & Mohsin, H. (2021). The effect of emergent technologies on accountant’s ethical blindness. The International Journal of Digital Accounting Research, 61(1), 12-25.
Silahtaroğlu, G., Dereköy, F., & Baytören, E. (2026). A machine learning approach to audit modification risk prediction in financial reporting: methods, data, and human-centered challenges. Journal of Risk and Financial Management, 19(1), 221-234. https://doi.org/10.3390/jrfm19030221.
Sundarasen, S., Kamaludin, K., & Nakiran, D. (2026). From adoption to audit quality: mapping the intellectual structure of artificial intelligence-enabled auditing. Journal of Risk and Financial Management, 19(1), 209-220. https://doi.org/10.3390/jrfm19030209.
Tharapos, M., Lau, K. H., Peszynski, K., Nguyen, L. A., Magdziarz, S., Morton, E., ... & Duan, S. (2025). Generative AI in accounting education: Evaluating ChatGPT’s role in assessment and skill development. Accounting & Finance, 65(3), 3231-3244. https://doi.org/10.1111/acfi.70051Digital.
Tranfield, D., Denyer, D., & Smart, P. (2003). Towards a methodology for developing evidence-informed management knowledge by means of systematic review. British Journal of Management, 14(3), 207–222. https://doi.org/10.1111/1467-8551.00375.
Usman, M., & Harto, P. (2024). Artificial Intelligence (AI) for sustainable development in MSMEs: A literature review. Research Horizon, 4(6), 109- 116. https://doi.org/10.54518/rh.4.6.2024.399.
Van Zijl, W., Burnham, K., & Ecim, D. (2026). How close is AI to replacing accounting consultants? Insights from a comparative study of multiple AI models and exit-level accounting students. Meditari Accountancy Research, 34(1), 53–78. https://doi.org/10.1108/MEDAR-07-2025-3160.
Wati, K. S. K., & Werastuti, D. N. S. (2025). Pengaruh Environmental Social and Governance (ESG) score, ukuran perusahaan dan struktur modal terhadap kinerja keuangan. JIMAT (Jurnal Ilmiah Mahasiswa Akuntansi), 16(1), 211–223.
Werastuti, D. N. S., Saputri, L. A. M., Sutoto, A., Hutomo, A. S., Purwanto, W., & Prayoga, R. A. (2023). Impact of foreign related party transactions, thin capitalization, and significant foreign ownership on tax avoidance. PREVENIRE: Journal of Multidisciplinary Science, 2(4), 196–208. https://doi.org/10.58330/prevenire.v3i1.299.
Yamani, A. (2025). The role of artificial intelligence in enhancing financial reporting quality: evidence from Saudi Arabia’s vision 2030 transformation. Journal of Modern Accounting and Auditing, 21(4), 237-525. https://doi.org/10.17265/1548-6583/2025.04.001.
Yu, Z., Wu, J., & Li, Y. (2025). LightGBM with SHAP based carbon emission risk prediction model using ESG disclosure data of listed firms. In Proceedings of the 2025 2nd International Conference on Economic Data Analytics and Artificial Intelligence (EDAI 2025) (pp. 82–85). Changsha: ACM.
Yudantara, I. G. A. P., & Yasa, P. I. N. (2020). Determinant use of behavior online shopping information system. Advances in Economics, Business and Management Research, 158(1), 413–419. https://doi.org/10.2991/aebmr.k.201212.058.
Yudantara, I. G. A. P., Diatmika, I. P. G., Musmini, L. S., & Yuniarta, G. A. (2019a). Analysis of acceptance and success implementation of Academic Information System (SIAk) based on technology. Advances in Economics, Business and Management Research, 103(2), 313–320. https://doi.org/10.2991/teams-19.2019.51.
Yudantara, I. G. A. P., Sulindawati, N. L. G. E., & Yuniarta, G. A. (2019b). Analysis use of academics information system by Undiksha new student. Advances in Economics, Business and Management Research, 69(1), 61–68. https://doi.org/10.2991/teams-18.2019.12.
Yudistira, K., & Masdiantini, P. R. (2023). Pengaruh literasi keuangan, persepsi manfaat dan kepuasan pengguna terhadap minat penggunaan e-Wallet OVO pada mahasiswa S1 Akuntansi Undiksha. Vokasi: Jurnal Riset Akuntansi, 12(3), 93–103. https://doi.org/10.23887/vjra.v12i3.68002.
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