7: IG for Legal and Compliance Functions
- Page ID
- 66728
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Introduction
Information governance (IG) matters to legal and compliance teams because legal risk is often information risk. When an organization cannot find relevant records, cannot prove they are authentic, or cannot explain why some records were deleted and others were kept, legal exposure rises quickly. Litigation, regulatory investigations, and internal misconduct inquiries all depend on evidence, and evidence is increasingly digital: email, chat, cloud files, logs, mobile data, and now AI-generated content. The legal function therefore needs IG not as an abstract “records program,” but as an operational capability that makes evidence findable, preservable, and defensible.
The modern reality is that the evidence landscape is shifting in three ways. First, collaboration platforms and cloud productivity suites have expanded the number of places where evidence lives, and they store information in ways that are not always intuitive to non-technical teams (for example, Teams messages stored across mailboxes and SharePoint-backed locations). Second, e-discovery technology is increasingly AI-assisted: technology-assisted review (TAR), continuous active learning, and newer generative AI features help teams summarize and prioritize documents, but they require careful governance to avoid overreliance, bias, and privilege mistakes. Relativity, for example, describes “Active Learning” as a technology-assisted review approach that learns continuously from reviewer coding decisions to predict relevance. Everlaw similarly markets citation-backed summaries and document Q&A to accelerate review while keeping human verification central. Third, AI regulation is becoming concrete. The EU Artificial Intelligence Act (Regulation (EU) 2024/1689) organizes AI obligations around risk tiers and specifies requirements for high-risk AI systems, including risk management, data governance, technical documentation, record-keeping, transparency, human oversight, and cybersecurity. For legal and compliance teams, those requirements are not just “AI law”; they are recordkeeping and auditability requirements. [help.relativity.com], [help.relativity.com] [everlaw.com] [eur-lex.europa.eu], [artificial...enceact.eu]
This chapter explains how IG supports legal and compliance functions. It walks through the e-discovery process and how good governance reduces cost and risk, explains legal holds and how to implement them, summarizes EU AI Act obligations most relevant to legal/compliance programs, and reviews tools used in modern matters. Practical checklists, tables, and case studies show what can go wrong and how to do better.
The Role of IG in Legal and Compliance Functions
Legal and compliance teams work in a cycle: prevent problems, detect issues early, respond to incidents and disputes, and demonstrate that the organization acted reasonably. IG supports each phase.
Litigation and investigation readiness
“Litigation readiness” is the ability to respond quickly and defensibly to a dispute, investigation, or audit. Readiness depends on knowing where information is stored, who owns it, and how to preserve it without breaking business operations. The Electronic Discovery Reference Model (EDRM) explicitly places information governance as the foundation stage that precedes identification and preservation, reflecting the idea that pre-litigation control of information reduces downstream discovery pain. [teris.com]
In practical terms, litigation readiness means:
- A current data map (major systems, repositories, and custodians)
- Clear retention schedules and disposal processes (so deletions are routine and explainable)
- Repeatable legal hold workflows
- Standard collection and chain-of-custody procedures
- An e-discovery playbook that aligns Legal, IT, Security, and business units
Compliance and audit support
Compliance teams must demonstrate adherence to laws, regulations, contracts, and internal policies. That requires evidence: training records, audit logs, approvals, and documented processes. The EU AI Act’s emphasis on technical documentation and record-keeping for high-risk AI systems is an example of modern “compliance as evidence”—you must be able to show how the system was designed, tested, monitored, and controlled. IG creates the infrastructure for that evidence. [artificial...enceact.eu], [eur-lex.europa.eu]
Risk reduction through defensible disposition
“Defensible disposition” means disposing of information according to approved rules, consistently, with documentation. It reduces the volume of data that could be discovered in litigation and reduces the amount of sensitive data that could be breached. Defensible disposition is not about hiding evidence; it is about applying retention rules consistently before any duty to preserve arises. The Sedona Principles emphasize proportionality and reasonableness in preserving and producing electronically stored information (ESI), recognizing that it is unreasonable to take disproportionate steps to preserve every possible copy of ESI. That principle supports IG programs that control data growth and focus preservation on what matters. [thesedonac...erence.org], [thesedonac...erence.org]
AI evidence and new categories of records
AI changes legal evidence in two directions. It creates new content (summaries, drafts, chat responses, automated decisions), and it creates new records about systems (prompts, training data, model logs, evaluation reports). NIST’s Generative AI Profile (NIST AI 600-1) is designed to help organizations identify genAI risks and proposes actions aligned to the AI RMF; it reinforces the need for documentation and governance across the AI lifecycle. Legal and compliance teams should therefore collaborate with AI and IT teams to define: [nvlpubs.nist.gov], [nist.gov]
- When prompts and outputs become business records
- How to preserve AI outputs that influence decisions (especially in regulated contexts)
- How to capture model logs, versioning, and evidence of human review
E-Discovery Process and IG Support
E-discovery (electronic discovery) is the process of finding, preserving, reviewing, and producing electronically stored information for legal matters. While the details vary across jurisdictions and case types, the EDRM provides a widely used conceptual framework and shared vocabulary. It describes stages including information governance, identification, preservation, collection, processing, review, analysis, production, and presentation. [teris.com]
