Impacto da inteligência artificial nos processos contábeis: revisão sistemática
DOI:
https://doi.org/10.29352/mill0223e.43148Palavras-chave:
inteligência artificial; processos contábeis: automação contábil, algoritmos de aprendizado automático; tecnologias emergentesResumo
Introdução: A transformação digital e o avanço acelerado da inteligência artificial (IA) geraram um impacto significativo em diversas áreas, entre elas a contabilidade. Essa disciplina, tradicionalmente focada em processos manuais e repetitivos, começou a passar por uma evolução substancial graças à incorporação de tecnologias inteligentes. A IA é uma ferramenta fundamental para que as empresas obtenham informações financeiras de forma oportuna e precisa.
Objetivo: O presente estudo teve como objetivo descrever o impacto da inteligência artificial nos processos contábeis das organizações.
Métodos: Foi realizada uma revisão sistemática da literatura com enfoque bibliométrico, analisando uma amostra de 59 artigos originais provenientes de diversos países e autores, selecionados por meio de critérios de inclusão e exclusão e diretrizes PRISMA.
Resultados: As descobertas revelam que a integração da inteligência artificial com tecnologias como a cadeia de blocos (Blockchain) permite automatizar tarefas rotineiras, como emissão de faturas, registros contábeis, conciliações bancárias e geração de relatórios financeiros. Além disso, foram identificados algoritmos de IA eficazes, como BPNN, BP-ANN, KMP, aprendizado profundo e KG, que fortalecem a precisão, eficiência, confiabilidade e segurança dos processos contábeis.
Conclusão: A inteligência artificial está revolucionando o campo da contabilidade nas organizações, tornando-a uma função mais estratégica, automatizada e orientada para a tomada de decisões. Sua implementação contribui para otimizar a gestão empresarial, reduzir erros e melhorar a análise financeira.
Downloads
Referências
Abdullah, A. A. H., & Almaqtari, F. A. (2024). The impact of artificial intelligence and Industry 4.0 on transforming accounting and auditing practices. Journal of Open Innovation: Technology, Market, and Complexity, 10(1), 100218. https://doi.org/10.1016/j.joitmc.2024.100218
Abouelela, O., Diab, A., & Saleh, S. (2025). The relationship between AI and audit planning in emerging economies: Does audit firm size matter? SAGE Open, 15(4). https://doi.org/10.1177/21582440251381155
Adebiyi, O. (2023). Exploring the impact of predictive analytics on accounting and auditing expertise: A regression analysis of LinkedIn survey data. Asian Journal of Economics, Business and Accounting, 23(22), 286–305. https://doi.org/10.9734/ajeba/2023/v23i221153
Adeoye, I., Akintoye, R., Aguguom, T., & Olagunju, O. (2023). Artificial intelligence and audit quality: Implications for practicing accountants. Asian Economic and Financial Review, 13(11), 756–772. https://doi.org/10.55493/5002.v13i11.4861
Afroze, D., & Aulad, A. (2020). Perception of professional accountants about the application of artificial intelligence (AI) in auditing industry of bangladesh. Journal of Social Economics Research, 7(2), 51–61. https://doi.org/10.18488/journal.35.2020.72.51.61
Al-Hashimy, H., Hussein, W., Al Jubair, A., & Yao, J. (2024). Enhancing Data Integrity in Computerized Accounting Information Systems Using Supervised and Unsupervised Machine Learning Algorithms Implement A SEM-PLS Analysis. Informatica, 48(20), 107–118. https://doi.org/10.31449/inf.v48i20.6823
Almarri, S. O., Alotaibi, E. M., Khallaf, A., Gleason, K. C., & Abdallah, A. A. N. (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
Alnaimat, M., Korsun, I., Lutsenko, K., Khodorkovskyi, O., & Artemchuk, M. (2025). Artificial intelligence in accounting: Revolutionizing financial management in the digital landscape. Theoretical and Practical Research in the Economic Fields, 16(1), 130–141. https://doi.org/10.14505/tpref.v16.1(33).11
Alotaibi, E. M. (2023). Risk assessment using predictive analytics. International Journal of Professional Business Review, 8(5), e01723. https://doi.org/10.26668/businessreview/2023.v8i5.1723
Alrjoub, A., Bataineh, A., Al-Qudah, L., Al-Othman, L., Alkarabsheh, F., & Aburisheh, K. (2023). The impact of quality costs as a mediator in the relationship between management accounting systems and financial performance: The case of Jordan. International Journal of Professional Business Review, 8(4), 1–16. https://doi.org/10.26668/businessreview/2023.v8i4.1462
Altawalbeh, M., Al Frijat, Y., & Alhajaya, M. (2025). Pros and cons of using artificial intelligence in accounting: The dual effect and financial control. International Review of Management and Marketing, 15(2), 200–208. https://doi.org/10.32479/irmm.17854
Anh, N., Hoa, L., Thao, L., Nhi, D., Long, N., Truc, N., & Ngoc Xuan, V. (2024). The effect of technology readiness on adopting artificial intelligence in accounting and auditing in Vietnam. Journal of Risk and Financial Management, 17(1). https://doi.org/10.3390/jrfm17010027
Anton, C., Ciobanu, E., Brătucu, G., & Bucs, L. (2024). Using chatbots to enhance integrated reporting: Insights from accounting and consultancy companies from Romania. Electronics, 13(23). https://doi.org/10.3390/electronics13234801
Artene, A., Domil, A., & Ivascu, L. (2024). Unlocking business value: Integrating AI-driven decision-making in financial reporting systems. Electronics, 13(15). https://doi.org/10.3390/electronics13153069
Azman, N., Mohamed, A., & Jamil, A. (2021). Artificial intelligence in automated bookkeeping: A value-added function for small and medium enterprises. International Journal on Informatics Visualization, 5(3), 224–230. https://doi.org/10.30630/JOIV.5.3.669
Bou, F., & Jabbour, N. (2024). Assessing the transformative impact of AI adoption on efficiency, fraud detection, and skill dynamics in accounting practices. Journal of Risk and Financial Management, 17(12). https://doi.org/10.3390/jrfm17120577
Bravidor, M. (2024). Auditing algorithms in the (non-)financial audit: Status quo and way forward. In AI in business and economics (pp. 45–55). De Gruyter. https://doi.org/10.1515/9783110790320-004
Cabanillas, S., Rengifo, G., Alfaro, J., & Castillo, E. (2025). Artificial intelligence in accounting: Advances and challenges. Revista Venezolana de Gerencia, 30(111), 1469–1483. https://doi.org/10.52080/rvgluz.30.111.14
Casanova-Villalba, C., Herrera-Sánchez, M., & Almeida-Blacio, J. (2025). Aplicaciones de inteligencia artificial en la auditoría financiera contemporánea. Revista Científica Ciencia Y Método, 3(2), 30-43. https://doi.org/10.55813/gaea/rcym/v3/n2/3
Chen, J. (2022). Application analysis of artificial intelligence algorithm in accounting field under the background of innovation economy. Mobile Information Systems, 2022 1–9. https://doi.org/10.1155/2022/7970237
Chen, Y. (2021). Framework of the smart finance and accounting management model under the artificial intelligence perspective. Mobile Information Systems, 2021. https://doi.org/10.1155/2021/4295191
Chen, Y., Wu, Z., & Yan, H. (2022). A full population auditing method based on machine learning. Sustainability, 14(24). https://doi.org/10.3390/su142417008
Chen, H., Zhang, M., Zeng, J., & Wang, W. (2024). Artificial intelligence and corporate risk-taking: Evidence from China. China Journal of Accounting Research, 17(3), 100372. https://doi.org/10.1016/j.cjar.2024.100372
Chi, D.-J., & Chu, C.-C. (2021). Artificial intelligence in corporate sustainability: Using lstm and gru for going concern prediction. Sustainability, 13(21). https://doi.org/10.3390/su132111631
Chi, D.-J., & Shen, Z.-D. (2022). Using hybrid artificial intelligence and machine learning technologies for sustainability in going-concern prediction. Sustainability, 14(3). https://doi.org/10.3390/su14031810
Cho, O.-H. (2024). Analysis of the impact of artificial intelligence applications on the development of accounting industry. Nanotechnology Perceptions, 20(S1), 74–83. https://doi.org/10.62441/nano-ntp.v20iS1.7
Clerkin, B., & McConville, D. (2022). Integrating AIS and contemporary technologies. Queen’s University Belfast. https://doi.org/10.4324/9781003132943-24
Coman, D., Ionescu, C., Duică, A., Coman, M., Uzlau, M., Stanescu, S., & State, V. (2022). Digitization of accounting: The premise of the paradigm shift of role of the professional accountant. Applied Sciences, 12(7). https://doi.org/10.3390/app12073359
Coronado, B. (2024). Herramientas IA para impulsar tu productividad. RA-MA Editorial.
Díaz-Avelino, J., Casanova-Villalba, C., Castillo-Barragán, C., Cueva-Jiménez, M., Herrera-Sánchez, M. y Zambrano-Muñoz, C. (2024). Integrando IA en los nuevos paradigmas de las ciencias económicas y gestión empresarial. Editorial Grupo AEA. https://shre.ink/7yzl
Dumitru, V., Ionescu, B.-Ú., Rîndașu, S.-M., Barna, L.-E.-L., & Crîjman, A.-M. (2023). Implications for sustainability accounting and reporting in the context of the automation-driven evolution of ERP systems. Electronics, 12(8). https://doi.org/10.3390/electronics12081819
Dwivedi, Y., Sharma, A., Rana, N., Giannakis, M., Goel, P., & Dutot, V. (2023). Evolution of artificial intelligence research in Technological Forecasting and Social Change: Research topics, trends, and future directions. Technological Forecasting and Social Change, 192, 122579. https://doi.org/10.1016/j.techfore.2023.122579
Gkegkas, M., Kydros, D., & Pazarskis, M. (2025). Using data analytics in financial statement fraud detection and prevention: A systematic review of methods, challenges, and future directions. Journal of Risk and Financial Management, 18(11), 598. https://doi.org/10.3390/jrfm18110598
Gonçalves, M., da Silva, A., & Ferreira, C. (2022). The future of accounting: How will digital transformation impact the sector? Informatics, 9(1), 1–17. https://doi.org/10.3390/informatics9010019
Grajales, L., & Sánchez, C. (2025). Auditoría GPT (2.a ed.). Grupo Editorial Nueva Legislación SAS.
Grosu, V., Cosmulese, C., Socoliuc, M., Ciubotariu, M., & Mihaila, S. (2023). Testing accountants’ perceptions of the digitization of the profession and profiling the future professional. Technological Forecasting and Social Change, 193, 122630. https://doi.org/10.1016/j.techfore.2023.122630
Gusc, J., Bosma, P., Jarka, S., & Biernat-Jarka, A. (2022). The big data, artificial intelligence, and blockchain in true cost accounting for energy transition in Europe. Energies, 15(3). https://doi.org/10.3390/en15031089
Haddad, H. (2021). The effect of artificial intelligence on the AIS excellence in Jordanian banks. Montenegrin Journal of Economics, 17(4), 155–166. https://doi.org/10.14254/1800-5845/2021.17-4.14
Hamza, R. A. E. M., Alnor, N. H. A., Al-Matari, E. M., Benzerrouk, Z. S., Mohamed, A. M. E., Bennaceur, M. Y., Elhefni, A. H. M., & Elshaabany, M. M. (2024). The impact of artificial intelligence (AI) on the accounting system of Saudi companies. WSEAS Transactions on Business and Economics, 21, 499–511. https://doi.org/10.37394/23207.2024.21.42
Hermansyah, Y. (2023). Assessing the impact of communicative artificial intelligence based accounting information systems on small and medium enterprises. Journal of Wireless Mobile Networks, Ubiquitous Computing, and Dependable Applications, 14(3), 230–239. https://doi.org/10.58346/JOWUA.2023.I3.017
Herrera-Sánchez, M., Casanova-Villalba, C., Concha-Ramirez, J., & López-Pérez, P. (2024). Impacto de la inteligencia artificial en los procesos de auditoría contable. Innova Science Journal, 2(1), 1-14. https://doi.org/10.63618/omd/isj/v2/n1/28.
Hou, X. (2022). Design and application of intelligent financial accounting model based on knowledge graph. Mobile Information Systems, 2022, 8353937. https://doi.org/10.1155/2022/8353937
Hu, K. -H., Chen, F. -H., Hsu, M. -F., & Tzeng, G. -H. (2021). Identifying key factors for adopting artificial intelligence-enabled auditing techniques by joint utilization of fuzzy-rough set theory and MRDM technique. Technological and Economic Development of Economy, 27(2), 459–492. https://doi.org/10.3846/tede.2020.13181
Hu, K. -H., Dong, C., Chen, F. -H., Lin, S. -J., & Hung, M. -C. (2022). A Fusion Decision-Making Architecture for COVID-19 Crisis Analysis and Management. Electronics, 11(11), 1–19. https://doi.org/10.3390/electronics11111793
Hurtado-Guevara, R. F., & Casanova-Villalba, C. I. (2022). La auditoría forense como herramienta para la detección de fraudes financieros en Ecuador. Revista Científica Zambos, 1(1), 33-50. https://doi.org/10.69484/rcz/v1/n1/52
Ilugbusi, B. S., & Dorasamy, N. (2025). Analysis of disruptive business models: leveraging AI to transform accounting services. International Journal of Accounting and Economics Studies, 12(2), 43–46. https://doi.org/10.14419/W04BMY85
Ionescu, L. (2022). Big data algorithms and artificial intelligence technologies in cloud-based accounting information systems. Analysis and Metaphysics, 21, 42–57. https://doi.org/10.22381/AM2120223
Ivanova, E., Darinskaya, V., Andreeva, L., Golovetsky, N., & Borisova, E. (2021). Modeling accounting information in the internal control system of enterprises. In Frontier Information Technology and Systems Research in Cooperative Economics. https://doi.org/10.1007/978-3-030-57831-2_57
Jiang, D., Ni, Z., Chen, Y., Chen, X., & Na, C. (2023). Influence of financial shared services on the corporate debt cost under digitalization. Sustainability, 15(1). https://doi.org/10.3390/su15010428
Karbekova, A., Мakhkamova, S., Inkova, N., & Pakhomova, O. (2023). Automation based on datasets and AI of corporate accounting and sustainability reporting in quality management in industry 4.0. Proceedings on Engineering Sciences, 5(S2), 265–278. https://doi.org/10.24874/PES.SI.02.007
Klius, Y., Ivchenko, Y., Izhboldina, A., & Ivchenko, Y. (2020). International approaches to organizing an internal control system at an enterprise in the digital era. Economic Annals-XXI, 185(9–10), 133–143. https://doi.org/10.21003/EA.V185-13
Kokina, J., Blanchette, S., Davenport, T., & Pachamanova, D. (2025). Challenges and opportunities for artificial intelligence in auditing: Evidence from the field. International Journal Accounting Information Systems, 56, 100734. https://doi.org/10.1016/j.accinf.2025.100734
Kowalczyk, M. (2024). Robotic process automation in accounting for public sector entities from the perception of clerks – evolution or revolution? ZTR, 48(3), 197-214. https://doi.org/10.5604/01.3001.0054.7263
Kristandl, G. (2022). Technologies underpinning accounting information systems. In E. Strauss & M. Quinn (Eds.), The Routledge handbook of accounting information systems (2nd ed., pp. 33–49). Routledge. https://doi.org/10.4324/9781003132943-5
Larikova, T., Ivankov, P., Novichenko, L., & Kydysiuk, K. (2024). Possibilities of integrating artificial intelligence technologies into the system of accounting and analytical support to public sector entities. Eastern European Journal of Enterprise Technologies, 6(13(132)), 88–97. https://doi.org/10.15587/1729-4061.2024.319051
Le Guyader, L. (2020). Artificial intelligence in accounting: GAAP’s “FAS133.” Journal of Corporate Accounting and Finance, 31(3), 185–189. https://doi.org/10.1002/jcaf.22407
Leitner-Hanetseder, S., & Lehner, O. (2023). AI-powered information and big data: Current regulations and ways forward in IFRS reporting. Journal of Applied Accounting Research, 24(2), 282–298. https://doi.org/10.1108/JAAR-01-2022-0022
Li, J. (2022). Construction and model realization of financial intelligence system based on multisource information feature mining. Computational Intelligence and Neuroscience, 2022, 9363023. https://doi.org/10.1155/2022/9363023
Liu, J., Wu, S., & Pham, V. T. (2022). Design of accounting earnings forecasting model based on artificial intelligence. Scientific Programming, 2022. https://doi.org/10.1155/2022/8793596
Liu, R., Wang, Y., & Zou, J. (2022). Research on the transformation from financial accounting to management accounting based on drools rule engine. Computational Intelligence and Neuroscience, 2022. https://doi.org/10.1155/2022/9445776
Manterola, C., Astudillo, P., Arias, E. y Claros, N. (2013). Revisiones sistemáticas de la literatura. Qué se debe saber acerca de ellas. Cirugía Española, 91(3), 149–155. https://doi.org/10.1016/j.ciresp.2011.07.009
Marchesano, M., Scavone, G. y Pavón, N. (2023). Impactos de la inteligencia artificial en la profesión contable. In XIX Simposio Regional de Investigación Contable. Universidad Nacional de la Plata. https://sedici.unlp.edu.ar/handle/10915/162132
Marques, S., Gonçalves, R., Lopes, R., Pereira, L., & Dias, A. (2023). The impact of intelligent systems on management accounting. International Journal of Intelligent Information Technologies, 19(1). https://doi.org/10.4018/IJIIT.324601
Melliani, H., Mouhtat, I., Kerfal, W., & Razouk, A. (2024). Artificial Intelligence in recruitment: Navigating the era of Web 4.0. Qubahan Academic Journal, 4(2), 558–568. https://doi.org/10.48161/qaj.v4n2a283
Mgammal, M. (2024). The influence of artificial intelligence as a tool for future economies on accounting procedures: Empirical evidence from Saudi Arabia. Discover Computing, 27(1). https://doi.org/10.1007/s10791-024-09452-7
Miñán, S., Estrada, J., Cruz, A., Moreno, J., & Cisneros, H. (2023). Business intelligence as a competitive advantage in organizations: A systematic review of the literature (2012-2022). In Proceedings of the LACCEI International Multi-Conference for Engineering, Education and Technology. LACCEI. https://shre.ink/7yEx
Mohammad, S., Hamad, A., Borgi, H., Thu, P., Sial, M., & Alhadidi, A. (2020). How artificial intelligence changes the future of accounting industry. International Journal of Economics and Business Administration, 8(3), 478–488. https://doi.org/10.35808/ijeba/538
Mohammed, A., & Wahha, A. (2024). The relationship between artificial intelligence and e-accounting programs: Impact on the quality of financial reports in Iraqi banks. Financial and Credit Activity: Problems of Theory and Practice, 6(59), 180–193. https://doi.org/10.55643/fcaptp.6.59.2024.4522
Murikah, W., Nthenge, J., & Musyoka, F. (2024). Bias and ethics of AI systems applied in auditing: A systematic review. Scientific African. https://doi.org/10.1016/j.sciaf.2024.e02281
Nobanee, H. (2021). A bibliometric review of big data in finance. Big Data, 9(2), 73–78, https://doi.org/10.1089/big.2021.29044.edi
Olivares, B. (2023). La inteligencia artificial en la relación entre los obligados y la administración tributaria: Retos ante la gestión tecnológica. La Ley Soluciones Legales.
Oliveira, M. de P. C. de, Azevedo, M. S., & Ávila, W. (2024). Inteligência artificial aplicada à contabilidade: Análise de tendências e possibilidades. Revista Foco, 17(6), e5487. https://doi.org/10.54751/revistafoco.v17n6-141
Oneshko, S., Nazarenko, O., Yaremko, I., Koval, O., & Pysarchuk, O. (2023). Accounting and financial reporting in the it sphere of Ukraine: Opportunities of artificial intelligence. Financial And Credit Activity-Problems of Theory and Practice, 5(52), 79–96. https://doi.org/10.55643/fcaptp.5.52.2023.4151
Ordóñez-Sánchez, S., Hernández, G. y Martínez, A. (2025). Automatización contable con inteligencia artificial: Beneficios y desafíos para las empresas. Vincula Tégica EFAN, 11(5). https://doi.org/10.29105/vtga11.5-1165
Page, M., McKenzie, J., Bossuyt, P., Boutron, I., Hoffmann, T., Mulrow, C., Shamseer, L., Tetzlaff, J., Akl, E., Brennan, S., Chou, R., Glanville, J., Grimshaw, J., Hróbjartsson, A., Lalu, M., Li, T., Loder, E. W, Mayo-Wilson, E., McDonald, S., McGuinness, L., Stewart, L., Thomas, J., Tricco, A., Welch, V., Whiting, P., & Moher, D. (2021). The PRISMA 2020 statement: An updated guideline for reporting systematic reviews. BMJ, 372(71). https://doi.org/10.1136/bmj.n71
Pantea, M., Cilan, T., Cuc, L., Rad, D., Bâtcă-Dumitru, G., Șendroiu, C., Almași, R., Feher, A., & Gomoi, B. (2024). Optimizing Romanian managerial accounting practices through digital technologies: A resource-based and technology-deterministic approach to sustainable accounting. Electronics, 13(16), 1–20. https://doi.org/10.3390/electronics13163206
Pérez, M. (2023). Inteligencia artificial: ChatGPT práctico para empresas. ICB Editores.
Qin, J., & Qin, Q. (2021). Cloud platform for enterprise financial budget management based on artificial intelligence. Wireless Communications and Mobile Computing, 2021, 1–10. https://doi.org/10.1155/2021/8038433
Rahman, S., Haque, E., Afrad, S., Hasan, S., & Rahman, A. (2023). Impact of mobile phone usage on empowerment of rural women entrepreneurs: Evidence from rural Bangladesh. Heliyon, 9(11). https://doi.org/10.1016/j.heliyon.2023.e21604
Rautiainen, A., Scapens, R., Järvenpää, M., Auvinen, T., & Sajasalo, P. (2024). Towards fluid role identity of management accountants: A case study of a Finnish bank. British Accounting Review, 56(4). https://doi.org/10.1016/j.bar.2024.101341
Shapovalova, A., Kuzmenko, O., Polishchuk, O., Larikova, T., & Myronchuk, Z. (2023). Modernization of the national accounting and auditing system using digital transformation tools. Financial and Credit Activity: Problems of Theory and Practice, 4(51), 33–52. https://doi.org/10.55643/fcaptp.4.51.2023.4102
Solikin, I., & Darmawan, D. (2023). Impact of artificial intelligence in improving the effectiveness of accounting information systems. Journal of Wireless Mobile Networks, Ubiquitous Computing, and Dependable Applications, 14(2), 82–93. https://doi.org/10.58346/JOWUA.2023.I2.007
Szortyka, K. (2024). Intelligent automation of financial and accounting processes in business process outsourcing centers in Poland. Zeszyty Teoretyczne Rachunkowosci, 48(3), 155–175. https://doi.org/10.5604/01.3001.0054.7261
Tian, Y., & Zhang, Y. (2022). Evaluation of accounting data of water company based on combination model. Scientific Programming, 2022. https://doi.org/10.1155/2022/3373420
Tlili, H. (2025). Bibliometric analysis of artificial intelligence in accounting: Trends and future directions. International Journal of Advanced and Applied Sciences, 12(8), 149–165. https://doi.org/10.21833/ijaas.2025.08.015
Torres, R. (2023). Los riesgos y los desafíos que enfrentan los trabajadores frente al uso de la inteligencia artificial en el trabajo. Revista de Derecho Procesal del Trabajo, 6(7), 289–313. https://doi.org/10.47308/rdpt.v6i7.778
Turing, A. (1950). Computing machinery and intelligence. Mind, 59(236), 433–460. https://doi.org/10.1093/MIND/LIX.236.433
Vărzaru, A. (2022). Assessing artificial intelligence technology acceptance in managerial accounting. Electronics, 11(14). https://doi.org/10.3390/electronics11142256
Vărzaru, A. (2022). Assessing the impact of AI solutions’ ethical issues on performance in managerial accounting. Electronics, 11(14), 2221. https://doi.org/10.3390/electronics11142221
Wassie, F., & Lakatos, L. (2024). Artificial intelligence and the future of the internal audit function. Humanities and Social Sciences Communications, 11, 1-13. https://doi.org/10.1057/s41599-024-02905-w
Wood, D., Achhpilia, M., Adams, M., Aghazadeh, S., Akinyele, K., Akpan, M., Allee, K., Allen, A., Almer, E., Ames, D., Arity, V., Barr-Pulliam, D., Basoglu K. Asli and Belnap, A., Bentley, J., Berg, T., Berglund, N., Berry, E., Bhandari, A., Bhuyan, M., … Zoet, E. (2023). The ChatGPT artificial intelligence chatbot: How well does it answer accounting assessment questions? Issues in Accounting Education, 38(4), 81–108. https://doi.org/10.2308/ISSUES-2023-013
Wutzler, J. (2024). Outsmarting artificial intelligence in the classroom—Incorporating large language model-based chatbots into teaching. Issues in Accounting Education, 39(4), 183–206. https://doi.org/10.2308/ISSUES-2023-064
Yang, N. (2022). Financial big data management and control and artificial intelligence analysis method based on data mining technology. Wireless Communications and Mobile Computing, 2022. https://doi.org/10.1155/2022/7596094
Yang, Y., & Yin, Z. (2023). Resilient supply chains to improve the integrity of accounting data in financial institutions worldwide using blockchain technology. International Journal of Data Warehousing and Mining, 19(4). https://doi.org/10.4018/ijdwm.320648
Yi, Z., Cao, X., Chen, Z., & Li, S. (2023). Artificial intelligence in accounting and Finance: Challenges and opportunities. IEEE Access, 11, 129100–129123. https://doi.org/10.1109/ACCESS.2023.3333389
Ying, Y., Cui, X., & Jin, S. (2023). Artificial intelligence and green total factor productivity: The moderating effect of slack resources. Systems, 11(7), 356. https://doi.org/10.3390/systems11070356
Yoon, S. (2020). A study on the transformation of accounting based on new technologies: Evidence from Korea. Sustainability, 12(20), 1–23. https://doi.org/10.3390/su12208669
Zakharkina, L., Rubanov, P., Alibekova, B., Zakharkin, O., & Moldashbayeva, L. (2022). The impact of digital transformation in the acounting system of fuel and energy complex enterprises (international experience). International Journal of Energy Economics and Policy, 12(5), 152–161. https://doi.org/10.32479/ijeep.13317
Zeng, Y. (2022). Neural network technology-based optimization framework of financial and management accounting model. Computational Intelligence and Neuroscience, 2022, 1–9. https://doi.org/10.1155/2022/4991244
Zhang, W., & Zhu, M. (2022). Environmental accounting system model based on artificial intelligence blockchain and embedded sensors. Computational Intelligence and Neuroscience, 2022, 1–11. https://doi.org/10.1155/2022/3803566
Zhang, Y., Xiong, F., Xie, Y., Fan, X., & Gu, H. (2020). The impact of artificial intelligence and blockchain on the accounting profession. IEEE Access, 8, 110461–110477. https://doi.org/10.1109/ACCESS.2020.3000505
Zheng, M. (2022). Advanced artificial intelligence model for financial accounting transformation based on machine learning and enterprise unstructured text data. Mobile Information Systems, 2022. https://doi.org/10.1155/2022/5708652
Zheng, Y., Ye, X., & Wu, T. (2021). Using an optimized learning vector quantization- (LVQ-) based neural network in accounting fraud recognition. Computational Intelligence and Neuroscience, 2021, 1–10. https://doi.org/10.1155/2021/4113237
Downloads
Publicado
Como Citar
Edição
Secção
Licença
Direitos de Autor (c) 2026 Millenium - Journal of Education, Technologies, and Health
Este trabalho encontra-se publicado com a Licença Internacional Creative Commons Atribuição 4.0.
Os autores que submetem propostas para esta revista concordam com os seguintes termos:
a) Os artigos são publicados segundo a licença Licença Creative Commons (CC BY 4.0), conformando regime open-access, sem qualquer custo para o autor ou para o leitor;
b) Os autores conservam os direitos de autor e concedem à revista o direito de primeira publicação, permitindo-se a partilha livre do trabalho, desde que seja corretamente atribuída a autoria e publicação inicial nesta revista.
c) Os autores têm autorização para assumir contratos adicionais separadamente, para distribuição não-exclusiva da versão do trabalho publicada nesta revista (ex.: publicar em repositório institucional ou como capítulo de livro), com reconhecimento de autoria e publicação inicial nesta revista.
d) Os autores têm permissão e são estimulados a publicar e distribuir o seu trabalho online (ex.: em repositórios institucionais ou na sua página pessoal) já que isso pode gerar alterações produtivas, bem como aumentar o impacto e a citação do trabalho publica
Documentos necessários à submissão
Template do artigo (formato editável)
