Skip to content
Review

The role of AI in sourcing and mining data to identify, secure and manage relevant evidence: Is it really the panacea it claims to be?

Sep 2026 · Journal of financial compliance · Vol 10, pp. 29 · 0 citations

TL;DR

Against the backdrop of the UK’s sector-led, principles-based approach to AI regulation, the paper explores how legal and compliance teams can use AI responsibly while maintaining essential safeguards relating to accountability, transparency, fairness, and auditability.

Abstract

The rapid expansion of digital data has transformed the demands of modern legal practice, particularly in investigations, regulatory enquiries, and disputes. This paper examines the evolving role of artificial intelligence (AI) — especially generative AI (GenAI) — in sourcing, analysing, and managing evidence within this increasingly complex landscape. While traditional AI tools such as predictive coding and machine learning classifiers have long supported document review, emerging GenAI capabilities now enable the drafting of summaries, extraction of themes, and generation of structured narratives from large, diverse datasets. Against the backdrop of the UK’s sector-led, principles-based approach to AI regulation, the paper explores how legal and compliance teams can use AI responsibly while maintaining essential safeguards relating to accountability, transparency, fairness, and auditability. It outlines the benefits of AI across e-discovery, evidence triage, communication monitoring, privilege screening, and regulatory response preparation, drawing on practical examples from recent large-scale legal matters. At the same time, it offers a clear-eyed assessment of AI’s limitations. The paper highlights risks linked to data quality, admissibility, bias, privacy, and cross-border processing, as well as the inherent opacity of GenAI systems. It underscores why experienced human oversight remains indispensable, both to validate AI outputs and to ensure that nuanced legal judgments, including those on privilege and proportionality, are not compromised. Readers will gain practical insight into the capabilities and boundaries of AI in evidence management, learn how to integrate AI tools safely and effectively within governance frameworks, and understand the skills — such as prompt engineering and critical oversight — required to harness these technologies with confidence and rigour. This article is also included in The Business & Management Collection which can be accessed at http://hstalks.com.business/.

View source

Similar papers

Sep 2026

Governing data risks in the age of AI

This paper proposes a practical, audit-ready approach to governing data risks in the AI era, and introduces the concept of critical data elements (CDEs): data elements whose inaccuracy, unavailability, or misuse can produce material regulatory, financial, or customer-facing impact.

Xin-Fa Tu · 0 citations
Review Open access Aug 2026

Auditing Artificial Intelligence Systems: A Survey of Current Frameworks, Principles and Approaches

A systematic review of the literature on methodologies, frameworks, and techniques for auditing AI systems, focusing on legal and ethical considerations and compliance with regulations, reveals gaps in current auditing practices and highlights the importance of incorporating AI value chain stages and AI maturity levels...

Usman Shahbaz, A. Beheshti, B. Abedin et al. · 0 citations
Review Open access Aug 2026

A Study into the Evolving Challenges in Regulating Artificial Intelligence and Machine Learning in the Future Legal Profession: Analysing Regulatory Gaps, Ethical Dilemmas and Adaptive Strategies

The rapid diffusion of artificial intelligence (AI) and machine learning (ML) tools across the legal profession, ranging from predictive analytics and e-discovery platforms to generative-AI drafting assistants and algorithmic dispute-resolution systems, has outpaced the capacity of existing regulatory frameworks to gov...

Sushanta Kumar Das, Shantanu Ganguly · 0 citations
Review Open access Sep 2026

Artificial Intelligence and the Future of Subject Access Request: Transforming Data Disclosure Under the Uk GDPR

This article critically examines the transformative impact of Artificial Intelligence (AI) on the administration of Subject Access Requests (SARs) under the United Kingdom General Data Protection Regulation (UK GDPR). As organisations contend with exponential growth in electronically stored information, traditional...

Temitope Olodo · 0 citations

We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.