The Role of AI: from Conventional Methods to Digital Crime Analysis.

• Autores: Aya, L.T.P., Polo, O.C.C., Escobar, S.B.V., Saldaña, O.T., Tarrillo, L.A.B., Morales, M.E.L., Castillo, L.R., Araujo, P.A.V., Rosas, C.G.
• Formato: artículo
• Fecha de Publicación: 2025
• Institución: Universidad Nacional de Cajamarca
• Repositorio: UNC-Institucional
• Lenguaje: inglés
• OAI Identifier: oai:repositorio.unc.edu.pe:20.500.14074/9831
• Enlace del recurso: http://hdl.handle.net/20.500.14074/9831; https://doi.org/10.14419/ap57rx96
• Nivel de acceso: acceso abierto
• Materia: Artificial Intelligence; Digital Forensics,; Machine Learning; Forensic Technology; Cybersecurity Law; https://purl.org/pe-repo/ocde/ford#1.02.01

Current research highlights how artificial intelligence (AI) affects digital forensics, considering its development in methods, specific im-plementations, and repercussions on the justice system. In addition to its technical effects, emphasis is placed on its influence in reducing legal costs and improving institutional resources. According to the Europol report (2025), the processing of information in the organization of digital evidence has reduced forensic analysis time by up to 70%, representing significant savings in working hours and case backlogs (p. 4). These findings show that AI not only speeds up the identification of patterns and risks but also helps to reduce the financial burden on justice systems(Europol, 2025, March 18).Several studies support these findings. Fakiha (2024) indicates that an orderly and finite set of operations can reduce the time required to examine digital evidence by up to 96% (Fakiha, 2024, pp. 3-4). Furthermore, Khattak (2025) demonstrates that the accuracy of threat identification and digital evidence classification exceeds 90% (Khattak, 2025, p.112). These advances allow us to measure theeconomic benefits: if an analysis that previously took up to two weeks can now be completed in less than two days, the savings in expert salaries, storage costs, and legal expenses can vary between 40% and 60% (OECD, 2025, p.17).However, the obstacles are significant. Tageldin and Venter (2023) point out the great dangers posed by biases in algorithms and the lack of uniform regulations (p.4). In addition, there is concern about the lack of transparency in decisions that are made automatically. A recent example, reported by the Associated Press (2024), revealed how an artificial intelligence tool, which claimed to be 90% accurate, resulted in wrongful convictions in the courts due to its inability to be explained. These drawbacks make the discussion about digital transformation essential: the application of AI in the judicial sphere requires not only technical specifications but also adequate regulations, constant supervision, and sustainable development (Associated Press News, 2024).