The role of AI in standardizating contracts and its impact on business process optimization
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Abstract
The relevance of the research is due to the rapid development of artificial intelligence technologies and the need to increase the efficiency of contractual work in the conditions of the modern economy and digital transformation of business. The use of artificial intelligence technologies in the standardization of contracts opens new opportunities for increasing the efficiency of legal processes, minimizing risks and reducing the cost of time and resources. Standardized contracts created with the help of artificial intelligence contribute to ensuring high quality documentation and efficiency in concluding agreements. The purpose of the study is to determine the role of artificial in the process of standardization of contracts and analyze its impact on the optimization of internal business processes of enterprises, as well as assess the effectiveness of the implementation of relevant technological solutions in the practical activities of companies. The following methods of scientific knowledge were used in the study: formal-logical method and generalization method, classification and grouping methods, observation method, analytical method, comparison and analogy method, empirical analysis, modeling, methods of economic and statistical analysis, content analysis of publications, reports and documents, methods of abstraction and concretization. The study identified key benefits and risks of implementing AI, including the need for staff training and ensuring high data quality. It highlights the importance of standardizing contracts to optimize legal processes, which can reduce legal risks, facilitate document review, and ensure compliance with legal requirements. The study explored the use of AI to update contract templates in line with changes in legislation, which helps avoid errors and maintain the relevance of contracts at all stages of their lifecycle. Also, based on simulated practical examples, it is shown how AI-based automation and contract standardization contribute to reducing the time for preparing contracts, reducing the burden on the legal department, and improving the efficiency of business processes. In addition, comprehensive measures are proposed to improve the process of contract standardization. The importance of creating state contract standards alongside private sector solutions is identified.
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References
LawGeex (2018). AI with a human touch. Retrieved from: https://www.lawgeex.com/platform/managed-ai/
BBC. (2019). Apple's 'sexist' credit card investigated by US regulator. Retrieved from: https://www.bbc.com/news/business-50365609
Statista. (2024). (AI) use in the legal services industry worldwide - statistics & facts. Retrieved from: https://www.statista.com/topics/12085/ai-usage-in-the-legal-services-industry/#statisticChapter
Tran, B. (2025). AI’s role in supply chain optimization: Market growth and efficiency stats. PatentPC. Retrieved from: https://patentpc.com/blog/ais-role-in-supply-chain-optimization-market-growth-and-efficiency-stats
Bila, I., & Nasikan, N. (2021). Optimization of the management system in the modern business environment. Economics and Society, 27. https://doi.org/10.32782/2524-0072/2021-27-32
Butenko, T., Imangulova, Z., & Protsenko, N. (2025). Analysis of the impact of artificial intelligence on the optimization of business processes in the sphere of information technology. Science and Technology go Hand in Hand, 3(44), 1035–1050. Retrieved from: https://www.researchgate.net/publication/390523358
Capocasale, V., & Perboli, G. (2022). Standardizing Smart Contracts. IEEE Access. PP. 1-1.
Chernyshova, O.O., Domashenko, S.V., & Domashenko, D. G. (2024). Vplyv shtuchnoho intelektu na biznes-protsesy z metoiu optymizatsii ta pokrashchennia efektyvnosti roboty orhanizatsii. Vcheni zapysky TNU imeni V. I. Vernadskoho, 35(74), 196–204. https://www.tech.vernadskyjournals.in.ua/journals/2024/2_2024/29.pdf
Derba, V.S. (2024). Artificial intelligence as an instrument for improving key business processes of an enterprise. Achievements of Economics: Prospects and Innovations, 8. https://doi.org/10.5281/zenodo.13284225
Fareed, M. (2020). Core concepts of natural language processing. Retrieved from: https://www.researchgate.net/publication/359350788_Core_concepts_of_Natural_Language_Processing
Future of Professionals Report. (2025). AI-powered technology & the forces shaping professional work. Thomson Reuters. Retrieved from: https://www.thomsonreuters.com/en/c/future-of-professionals
García-Peñalvo, F., & Vázquez-Ingelmo, A. (2023). What do we mean by genai? a systematic mapping of the evolution, trends, and techniques involved in Generative AI. International Journal of Interactive Multimedia and Artificial Intelligence. 8. 7-16. Retrieved from: https://www.researchgate.net/publication/372788822_What_do_we_mean_by_GenAI_A_systematic_mapping_of_the_evolution_trends_and_techniques_involved_in_Generative_AI
Hryshko, V.I. (2024). Problem aspects of the implementation of artificial intelligence in the sphere of jurisprudence. In: Analytical-comparative jurisprudence/ ed.: YU. M. Bysaha, V. V. Zaborovsky, D. M. Byelov, S. B. Buletsa (Eds) (29-34). Uzhhorod: DVNZ «UzhNU».
Khalid, M.S., Moussa, A., Wu, J., & Ekstroem, J. (2025). Generative AI tools for systematic approaches to literature review: Insights from danish librarians. Retrieved from: https://www.researchgate.net/publication/390689003_Generative_AI_Tools_for_Systematic_Approaches_to_Literature_Review_Insights_from_Danish_Librarians#pf14
Kobko-Odariy, V.S. (2025). The legal nature of artificial intelligence: the problem of determining legal subjectivity and legal compliance. Legal Scientific Electronic Journal, 1(2025), 30-33. Retrieved from: http://lsej.org.ua/1_2025/6.pdf
Linarelli, J. (2019). Advanced artificial intelligence and contract. Uniform Law Review, Retrieved from: https://ssrn.com/abstract=3341307
Hrab, M.I., & Tomashivsʹkyy, M.O. (2024). Artificial intelligence in law: effectiveness. accuracy and democratization of the judicial right. Law and State Administration, 4, 318-322. https://doi.org/10.32782/pdu.2024.4.42
Mata v. Avianca, Inc. (2023). Case No. 1:2022cv01461, 2023 WL 4114965. Retrieved from: https://law.justia.com/cases/federal/district-courts/new-york/nysdce/1:2022cv01461/575368/55/
Möslein, F. (2023). Digitized terms: the regulation of standard contract terms in the digital age. European Review of Contract Law, 19(4), 300-320. https://doi.org/10.1515/ercl-2023-2019
Muzychenko, T.O., Skorba, O.A., & Shevchuk, A.A. (2023). Artificial intelligence as a tool for optimizing business processes in electronic commerce. Academic Visions, 25. Retrieved from: https://www.academy-vision.org/index.php/av/article/view/696
Plakhotnik, O.V. (2024). Artificial intelligence as an assistive technology in the work of lawyers and prosecutors. Legal Scientific Electronic Journal, 8, 441—445. Retrieved from: http://www.lsej.org.ua/8_2024/106.pdf
Priya, S. (2023). Samsung employees accidentally leaked company secrets via ChatGPT: Here’s what happened. Retrieved from: https://www.businesstoday.in/technology/news/story/samsung-employees-accidentally-leaked-company-secrets-via-chatgpt-heres-what-happened-376375-2023-04-06
Quoine Pte Ltd v B2C2 Ltd. (2020). SGCA(I) 02. Court of Appeal — Civil Appeal. Court Of Appeal Of The Republic Of Singapore. Retrieved from: https://www.elitigation.sg/gd/s/2020_SGCAI_2
Rotenberg, M., Aldama, A., Visco, C. & Alarcón, N.. (2024). International the future is now: Artificial intelligence and the legal profession. Journal of AI Law and Regulation, 1, 448-457.
Scaria, A.G., Subramanian, V., George, N.K., & Sengupta, N. (2024). Algorithms and recidivism: A multi-disciplinary systematic review. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society, 7(1), 1292-1305. https://doi.org/10.1609/aies.v7i1.31724
Shapovalova, A., Kuzmenko, O., & Prokopova, O. (2024). The role of artificial intelligence in optimizing taxation and development in small businesses. Economy and Society, 62, article number 116. https://economyandsociety.in.ua/index.php/journal/article/view/3987
Sri Adibhatla, H., & Shrivastava, M. (2023). SConE: Contextual relevance based significant component extraction from contracts. Retrieved from: https://www.researchgate.net/publication/374743086_SConEContextual_Relevance_based_Significant_CompoNent_Extraction_from_Contracts
Stavnichenko, M.V. (2024). Artificial intelligence in the preparation of legal documents. Artificial Intelligence in Higher Education: Risks and Prospects of Integration: Materials of the All-Ukrainian Scientific and Pedagogical Improvement of Qualifications, 2024, 274-278. Retrieved from: https://cuesc.org.ua/images/informlist/%D0%9C%D0%B0%D0%BA%D0%B5%D1%82%20advanced_training_OLA.pdf
The business case for AI-enabled legal technology. (2021). Thomson Reuters. Retrieved from: https://legalsolutions.thomsonreuters.co.uk/content/dam/ewp-m/documents/legal-uk/en/pdf/reports/the-business-case-for-ai-enabled-legal-technology.pdf
The total economic impact™ of LawGeex. (2021). Cost Savings And Business Benefits Enabled By LawGeex. Retrieved from: https://www.lawgeex.com/wp-content/uploads/2021/10/May2021-Forrester_TEI_Report-LawGeex.pdf
Williams, T. (2023). How AI helped Orangetheory’s legal team complete a 6-month project in half the time: ‘It’s straightforward math to see the cost savings. Fortune. https://fortune.com/2023/11/14/orangetheory-ai-artificial-intelligence-automation-legal-attorneys-contracts/