Intelligence Layering in Accounting Information Systems: A Theory of Progressive AI Embedding in Financial Reporting
DOI:
https://doi.org/10.59413/ajocs/v7.i5.15Keywords:
Artificial Intelligence, Accounting Information Systems, Management Information Systems, Intelligence Layering, Financial Reporting, AI Integration, Human–AI Collaboration, Technology Adoption, AIS TheoryAbstract
Artificial intelligence (AI) is increasingly embedded in accounting information systems (AIS), yet much of the emerging literature conceptualizes AI either as a collection of discrete technologies or as an organizational innovation whose adoption can be explained through established technology-acceptance and technology-adoption models. Such approaches provide limited theoretical explanation of what occurs between the decision to adopt AI and the emergence of an AI-enabled accounting information system. This paper develops intelligence layering as a theoretical construct that explains how AI capabilities are progressively embedded within established management information systems (MIS) and AIS architectures. Intelligence layering is defined as the progressive embedding, integration and orchestration of AI-enabled capabilities into an existing information-system architecture through which the system acquires enhanced capacities for automation, learning, language interpretation, prediction and adaptive decision support while remaining subject to human, organizational and governance controls. Drawing on the Technology Acceptance Model (TAM), Technology–Organization–Environment (TOE) framework, Resource-Based View (RBV), and socio-technical systems theory, the paper distinguishes adoption antecedents from the post-adoption mechanism through which AI changes information-processing capability. A multidimensional model is proposed comprising infrastructural compatibility, data readiness, integration depth, automation intelligence, learning intelligence, language intelligence, predictive intelligence, human interpretive integration, and governance integration. Nine propositions specify relationships among enabling conditions, intelligence layering, professional interpretation, governance and AI-enabled financial-reporting capability. A seven-level maturity model is proposed, ranging from conventional rule-based AIS to adaptive intelligent AIS. The paper also differentiates intelligence layering from a recently published multi-layered framework for AI in financial reporting by positioning layering not as an organizing taxonomy of AI themes but as a theoretical and architectural mechanism of post-adoption integration. Finally, the paper proposes an empirical operationalization strategy and research agenda. The contribution is to provide AIS scholarship with a middle-range theoretical mechanism linking technology adoption and resource conditions to progressive transformation of accounting information-processing capability.
Downloads
References
Abbas, K. (2026). Management accounting and artificial intelligence: A comprehensive literature review and recommendations for future research. The British Accounting Review, 58(2), 101551. https://doi.org/10.1016/j.bar.2025.101551 DOI: https://doi.org/10.1016/j.bar.2025.101551
Abdo-Salloum, A., & Chehade, S. (2026). The role of artificial intelligence in transforming accounting and auditing practices: A systematic review. SAGE Open, 16(1). https://doi.org/10.1177/21582440251403296 DOI: https://doi.org/10.1177/21582440251403296
Al-Okaily, M., et al. (2025). Artificial intelligence and its applications in the context of accounting and disclosure. Journal of Financial Reporting and Accounting, 23(4), 1387–1401. https://doi.org/10.1108/JFRA-04-2024-0209 DOI: https://doi.org/10.1108/JFRA-04-2024-0209
Ashraf, M. (2025). Does automation improve financial reporting? Evidence from internal controls. Review of Accounting Studies, 30, 436–479. https://doi.org/10.1007/s11142-024-09822-y DOI: https://doi.org/10.1007/s11142-024-09822-y
Barney, J. (1991). Firm resources and sustained competitive advantage. Journal of Management, 17(1), 99–120. https://doi.org/10.1177/014920639101700108 DOI: https://doi.org/10.1177/014920639101700108
Bavaresco, R. S., Nesi, L. C., Barbosa, J. L. V., Antunes, R. S., Righi, R. R. D., da Costa, C. A., Vanzin, M., Dornelles, D., Junior, S. C., Gatti, C., Ferreira, M., & Silva, E. (2023). Machine learning-based automation of accounting services: An exploratory case study. International Journal of Accounting Information Systems, 49, 100618. https://doi.org/10.1016/j.accinf.2023.100618 DOI: https://doi.org/10.1016/j.accinf.2023.100618
Berkin, A., Aerts, W., & Van Caneghem, T. (2023). Feasibility analysis of machine learning for performance-related attributional statements. International Journal of Accounting Information Systems, 48, 100597. https://doi.org/10.1016/j.accinf.2022.100597 DOI: https://doi.org/10.1016/j.accinf.2022.100597
Blankespoor, E., deHaan, E., & Li, Q. (2026). Generative AI in financial reporting. Journal of Accounting Research, 64(3), 1189–1232. https://doi.org/10.1111/1475-679X.70050 DOI: https://doi.org/10.1111/1475-679x.70050
Booker, A., Chiu, V., Groff, N., & Richardson, V. J. (2024). AIS research opportunities utilizing machine learning: From a meta-theory of accounting literature. International Journal of Accounting Information Systems, 52, 100661. https://doi.org/10.1016/j.accinf.2023.100661 DOI: https://doi.org/10.1016/j.accinf.2023.100661
Cebi, S., Karakurt, N. F., Kurtulus, E., & Tokgoz, B. (2024). Development of a decision support system for client acceptance in independent audit process. International Journal of Accounting Information Systems, 53, 100683. https://doi.org/10.1016/j.accinf.2024.100683 DOI: https://doi.org/10.1016/j.accinf.2024.100683
Choi, J. H., & Xie, C. L. (2026). Human + AI in accounting: Early evidence from the field. Journal of Accounting Research, 64(3), 1333–1373. https://doi.org/10.1111/1475-679X.70052 DOI: https://doi.org/10.1111/1475-679x.70052
Commerford, B. P., Dennis, S. A., Joe, J. R., & Ulla, J. W. (2022). Man versus machine: Complex estimates and auditor reliance on artificial intelligence. Journal of Accounting Research, 60(1), 273–305. https://doi.org/10.1111/1475-679X.12407 DOI: https://doi.org/10.1111/1475-679X.12407
Commerford, B. P., Eilifsen, A., & Hatfield, R. C. (2024). Control issues: How providing input affects auditors’ reliance on artificial intelligence. Contemporary Accounting Research. https://doi.org/10.1111/1911-3846.12974 DOI: https://doi.org/10.1111/1911-3846.12974
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 DOI: https://doi.org/10.2307/249008
Dong, M. M., Stratopoulos, T. C., & Wang, V. X. (2024). A scoping review of ChatGPT research in accounting and finance. International Journal of Accounting Information Systems, 55, 100715. https://doi.org/10.1016/j.accinf.2024.100715 DOI: https://doi.org/10.1016/j.accinf.2024.100715
Duan, H. K., Vasarhelyi, M. A., Codesso, M., & Alzamil, Z. (2023). Enhancing the government accounting information systems using social media information: An application of text mining and machine learning. International Journal of Accounting Information Systems, 48, 100600. https://doi.org/10.1016/j.accinf.2022.100600 DOI: https://doi.org/10.1016/j.accinf.2022.100600
Eisikovits, N., Johnson, W. C., & Markelevich, A. J. (2024). Should accountants be afraid of AI? Risks and opportunities of incorporating artificial intelligence into accounting and auditing. Accounting Horizons. DOI: https://doi.org/10.2139/ssrn.4748690
Fedyk, A., Hodson, J., Khimich, N., & Fedyk, T. (2022). Is artificial intelligence improving the audit process? Review of Accounting Studies, 27, 938–985. https://doi.org/10.1007/s11142-022-09697-x DOI: https://doi.org/10.1007/s11142-022-09697-x
Fotoh, L. E., & Mugwira, T. (2025). Exploring large language models in external audits: Implications and ethical considerations. International Journal of Accounting Information Systems, 56, 100748. https://doi.org/10.1016/j.accinf.2025.100748 DOI: https://doi.org/10.1016/j.accinf.2025.100748
Frey, C. B., & Osborne, M. A. (2017). The future of employment: How susceptible are jobs to computerisation? Technological Forecasting and Social Change, 114, 254–280. https://doi.org/10.1016/j.techfore.2016.08.019 DOI: https://doi.org/10.1016/j.techfore.2016.08.019
Gu, H., Schreyer, M., Moffitt, K., & Vasarhelyi, M. A. (2024). Artificial intelligence co-piloted auditing. International Journal of Accounting Information Systems, 54, 100698. https://doi.org/10.1016/j.accinf.2024.100698 DOI: https://doi.org/10.1016/j.accinf.2024.100698
Haenlein, M., & Kaplan, A. (2019). A brief history of artificial intelligence: On the past, present, and future of artificial intelligence. California Management Review, 61(4), 5–14. https://doi.org/10.1177/0008125619864925 DOI: https://doi.org/10.1177/0008125619864925
Han, H., Shiwakoti, R. K., Jarvis, R., Mordi, C., & Botchie, D. (2023). Accounting and auditing with blockchain technology and artificial intelligence: A literature review. International Journal of Accounting Information Systems, 48, 100598. https://doi.org/10.1016/j.accinf.2022.100598 DOI: https://doi.org/10.1016/j.accinf.2022.100598
Harrast, S. A. (2020). Robotic process automation in accounting systems. Journal of Corporate Accounting & Finance, 31(4), 209–213. https://doi.org/10.1002/jcaf.22457 DOI: https://doi.org/10.1002/jcaf.22457
Jackson, D., & Allen, C. (2024). Enablers, barriers and strategies for adopting new technology in accounting. International Journal of Accounting Information Systems, 52, 100666. https://doi.org/10.1016/j.accinf.2023.100666 DOI: https://doi.org/10.1016/j.accinf.2023.100666
Jones, M., & 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(5), 133–158. https://doi.org/10.1108/JAL-12-2025-0693 DOI: https://doi.org/10.1108/JAL-12-2025-0693
Juma’ha, A. H., Chuang, M., & Harfouche, A. (2026). Integrating AI into financial reporting and investment: Multi-layered framework. Journal of Decision Systems, 35(1), Article 2645969. https://doi.org/10.1080/12460125.2026.2645969 DOI: https://doi.org/10.1080/12460125.2026.2645969
Kaplan, A., & Haenlein, M. (2019). Siri, Siri, in my hand: Who’s the fairest in the land? On the interpretations, illustrations, and implications of artificial intelligence. Business Horizons, 62(1), 15–25. https://doi.org/10.1016/j.bushor.2018.08.004 DOI: https://doi.org/10.1016/j.bushor.2018.08.004
Knudsen, D.-R. (2020). Elusive boundaries, power relations, and knowledge production: A systematic review of the literature on digitalization in accounting. International Journal of Accounting Information Systems, 36, 100441. https://doi.org/10.1016/j.accinf.2019.100441 DOI: https://doi.org/10.1016/j.accinf.2019.100441
Kokina, J., & Davenport, T. H. (2017). The emergence of artificial intelligence: How automation is changing auditing. Journal of Emerging Technologies in Accounting, 14(1), 115–122. https://doi.org/10.2308/jeta-51730 DOI: https://doi.org/10.2308/jeta-51730
Law, K. K. F., & Shen, M. (2024). How does artificial intelligence shape audit firms? Management Science. https://doi.org/10.1287/mnsc.2022.04040 DOI: https://doi.org/10.1287/mnsc.2022.04040
Libby, R., & Witz, P. D. (2024). Can artificial intelligence reduce the effect of independence conflicts on audit firm liability? Contemporary Accounting Research. https://doi.org/10.1111/1911-3846.12941 DOI: https://doi.org/10.1111/1911-3846.12941
Lombardi, D. R., Kim, M., Sipior, J. C., & Vasarhelyi, M. A. (2025). The increased role of advanced technology and automation in audit: A Delphi study. International Journal of Accounting Information Systems, 56, 100733. https://doi.org/10.1016/j.accinf.2025.100733 DOI: https://doi.org/10.1016/j.accinf.2025.100733
Murphy, B., Feeney, O., Rosati, P., & Lynn, T. (2024). Exploring accounting and AI using topic modelling. International Journal of Accounting Information Systems, 55, 100709. https://doi.org/10.1016/j.accinf.2024.100709 DOI: https://doi.org/10.1016/j.accinf.2024.100709
Pei, D., & Vasarhelyi, M. A. (2020). Big data and algorithmic trading against periodic and tangible asset reporting: The need for U-XBRL. International Journal of Accounting Information Systems, 37, 100453. https://doi.org/10.1016/j.accinf.2020.100453 DOI: https://doi.org/10.1016/j.accinf.2020.100453
Perdana, A., Lee, W. E., & Kim, C. M. (2023). Prototyping and implementing robotic process automation in accounting firms: Benefits, challenges and opportunities to audit automation. International Journal of Accounting Information Systems, 51, 100641. https://doi.org/10.1016/j.accinf.2023.100641 DOI: https://doi.org/10.1016/j.accinf.2023.100641
Rikhardsson, P., & Dull, R. (2016). An exploratory study of the adoption, application and impacts of continuous auditing technologies. International Journal of Accounting Information Systems, 20, 1–19. DOI: https://doi.org/10.1016/j.accinf.2016.01.003
Rikhardsson, P., & Yigitbasioglu, O. (2018). Business intelligence and analytics in management accounting research: Status and future focus. International Journal of Accounting Information Systems, 29, 37–58. https://doi.org/10.1016/j.accinf.2018.03.001 DOI: https://doi.org/10.1016/j.accinf.2018.03.001
Rikhardsson, P., & Yigitbasioglu, O. (2022). Artificial intelligence and auditing in small- and medium-sized firms: Expectations and applications. AI Magazine. https://doi.org/10.1002/aaai.12066 DOI: https://doi.org/10.1002/aaai.12066
Rodgers, W. (2020). Accounting by and for digital technology: The role of AI and machine learning in accounting. In related accounting technology scholarship.
Russell, S. J., & Norvig, P. (2020). Artificial intelligence: A modern approach (4th ed.). Pearson.
Saxena, D. (2022). A conceptual framework for assessing the application of artificial intelligence for financial reporting. Universal Journal of Accounting and Finance, 10(5), 897–911. https://doi.org/10.13189/ujaf.2022.100502 DOI: https://doi.org/10.13189/ujaf.2022.100502
Schiavi, G. S., Behr, A., & Marcolin, C. B. (2024). Institutional theory in accounting information systems research: Shedding light on digital transformation and institutional change. International Journal of Accounting Information Systems, 52, 100662. https://doi.org/10.1016/j.accinf.2023.100662 DOI: https://doi.org/10.1016/j.accinf.2023.100662
Stratopoulos, T. C., & Wang, V. X. (2025). Artificial intelligence and accounting research: A framework and agenda. International Journal of Accounting Information Systems, 56, 100760. https://doi.org/10.1016/j.accinf.2025.100760 DOI: https://doi.org/10.1016/j.accinf.2025.100760
Tiron-Tudor, A., Lacurezeanu, R., Bresfelean, V. P., & Dontu, A. N. (2024). Perspectives on how robotic process automation is transforming accounting and auditing services. Accounting Perspectives. DOI: https://doi.org/10.1111/1911-3838.12351
Tornatzky, L. G., & Fleischer, M. (1990). The processes of technological innovation. Lexington Books.
Trist, E. L., & Bamforth, K. W. (1951). Some social and psychological consequences of the longwall method of coal-getting. Human Relations, 4(1), 3–38. https://doi.org/10.1177/001872675100400101 DOI: https://doi.org/10.1177/001872675100400101
Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425–478. https://doi.org/10.2307/30036540 DOI: https://doi.org/10.2307/30036540
Vitali, S., & Giuliani, M. (2024). Emerging digital technologies and auditing firms: Opportunities and challenges. International Journal of Accounting Information Systems, 53, 100676. https://doi.org/10.1016/j.accinf.2024.100676 DOI: https://doi.org/10.1016/j.accinf.2024.100676
Warren, J. D., Moffitt, K. C., & Byrnes, P. (2015). How big data will change accounting. Accounting Horizons, 29(2), 397–407. https://doi.org/10.2308/acch-51069 DOI: https://doi.org/10.2308/acch-51069
Zhang, C. A., Cho, S., & Vasarhelyi, M. A. (2022). Explainable artificial intelligence (XAI) in auditing. International Journal of Accounting Information Systems, 46, 100572. https://doi.org/10.1016/j.accinf.2022.100572 DOI: https://doi.org/10.1016/j.accinf.2022.100572
Zhang, C., et al. (2024). The role of IT governance in the integration of AI in accounting and auditing operations. Economies.
Zhang, C., Zhu, W., Dai, J., Wu, Y., & Chen, X. (2023). Ethical impact of artificial intelligence in managerial accounting. International Journal of Accounting Information Systems, 49, 100619. https://doi.org/10.1016/j.accinf.2023.100619. DOI: https://doi.org/10.1016/j.accinf.2023.100619
Downloads
Published
Issue
Section
License
Copyright (c) 2026 Michesk Mushani, Nchimunya Chaamwe, Joseph Phiri, Dr. Joe Likando Silondiso (Author)
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
