[EDRM Editor’s Note: This article was first published here on November 24, 2025, and EDRM is grateful to Trusted Partner Exterro for permission to republish. EDRM is happy to amplify our Trusted Partners news and events.]
Generative AI is transforming eDiscovery faster than any innovation in recent memory. Tasks that once required hours of human review now take minutes. Summaries, classifications, privilege cues, pattern identification — the appeal of automation is clear, especially for teams navigating tight budgets, demanding timelines, and ever-expanding data volumes.
But that speed and power come with a cost. GenAI is fast and inexpensive, yes — but it’s also unpredictable, easy to misuse, and capable of introducing entirely new categories of risk into discovery. In some cases, the very tools designed to lighten the workload can create exposures that undermine accuracy, privilege, and defensibility. The real challenge is not whether to adopt GenAI, but how to do so responsibly. To get there, legal teams need to separate the myths from the realities.
The real challenge is not whether to adopt GenAI, but how to do so responsibly.
Team Exterro.
The Three Myths of GenAI in eDiscovery
A few assumptions routinely steer teams in the wrong direction. The first is the idea that GenAI-generated content “isn’t real” and therefore not discoverable. In fact, AI-generated drafts, summaries, internal chatbot responses, and even experimental outputs can all qualify as ESI. If they influence legal strategy or reflect attorney impressions, they may carry privilege implications as well — and mishandling them can result in waiver.
A second misconception is that GenAI is inherently reliable. Yet hallucinations are a consistent characteristic of language models, not an edge case. A confident but incorrect summary, a fabricated date, an invented citation — these errors can silently seep into work product and open the door to defensibility challenges.
The third myth is that GenAI tools inherently protect sensitive information. Some do. Many do not. Data exposure can occur through prompts, logs, cached requests, or model training processes — even in tools marketed as “secure.” Without enterprise-grade controls and clear governance, teams may not fully understand where their data travels or how it’s stored.
These myths lead to the same problem: legal teams adopt GenAI quickly, enthusiastically, and without the guardrails necessary to preserve accuracy and privilege.
Understanding Where the Risks Really Are
When legal teams integrate GenAI into discovery workflows, the risks don’t appear all at once — they appear quietly, and often unintentionally. One major vulnerability involves privilege exposure. Even a well-meaning reviewer can accidentally embed sensitive context into a prompt, especially if the team hasn’t been trained in “prompt hygiene” or if they’re using consumer tools that store interaction histories.
Accuracy poses another challenge. Because GenAI prioritizes fluency over precision, it can generate summaries that appear reasonable but contain subtle distortions or invented details. If those summaries are used to triage documents, shape case strategy, or inform privilege calls, they undermine the credibility of the entire review process.
Equally concerning is what happens when AI use is undocumented or decentralized. Shadow AI — a reviewer using an unapproved tool, or a well-intentioned attorney experimenting without visibility — creates inconsistencies that are difficult to defend. Absence of documentation is just as problematic: if a team can’t explain how AI was used, when it was used, or who validated its output, opposing counsel is likely to seize on that uncertainty.
And underpinning all these issues is the simple fact that GenAI systems often generate artifacts — logs, cached data, interim versions — that teams may not realize are discoverable. Without awareness of these digital footprints, organizations can inadvertently expose information they never intended to preserve, let alone produce.
Where GenAI Helps — When It’s Managed Well
Despite these risks, GenAI can significantly strengthen eDiscovery workflows when used in a controlled, well-governed environment. It excels at synthesizing large volumes of data, surfacing early patterns, and helping teams navigate the initial stages of case assessment with speed and consistency. By automating repetitive, low-value tasks—like categorizing documents or generating preliminary summaries—GenAI frees reviewers to focus on higher-confidence analysis and strategic decisions.
GenAI also has the potential to improve consistency across large review teams. Unlike human reviewers, who may approach documents with varying levels of experience or fatigue, AI can apply hints and heuristics uniformly. With proper validation and sampling, these tools can reduce drift and help identify outliers more quickly.
The key is remembering that GenAI serves as a companion — not a replacement. Its outputs must be logged, validated, contextualized, and subjected to the same quality controls that have long defined defensible discovery. When that discipline is in place, AI becomes a powerful accelerator without compromising legal standards.
How to Keep GenAI Fast — Without Making It Dangerous
As GenAI becomes a larger part of eDiscovery, the path to safe adoption lies in balancing efficiency with deliberate oversight. Legal teams should begin by documenting exactly where GenAI fits into their workflows, including what it’s allowed to do and what remains strictly human-driven. They must ensure the technology operates within secure, enterprise-controlled environments that prevent the leakage of privileged or sensitive data. Prompt guidance is essential as well: reviewers should know what can and cannot be entered into an AI system, and why.
Validation is non-negotiable. Every AI-assisted task, from clustering to summarization, should be checked against samples to confirm accuracy. Logs must be preserved to provide a traceable chain-of-custody for all AI interactions. And because AI risk spans legal, IT, security, and compliance, governance must be collective — not confined to one department.
When teams adopt GenAI intentionally, with reasonable controls and shared accountability, the technology enhances rather than endangers defensibility. When they adopt it recklessly, it exposes exactly the weaknesses that opposing counsel hopes to find. GenAI is not a shortcut. It’s a multiplier — one that amplifies the quality of the processes, culture, and awareness already in place. Strong governance, strong habits, and thoughtful oversight allow legal teams to harness GenAI’s benefits without letting it overshadow the accuracy and integrity of their work.
GenAI is not a shortcut. It’s a multiplier — one that amplifies the quality of the processes, culture, and awareness already in place. Strong governance, strong habits, and thoughtful oversight allow legal teams to harness GenAI’s benefits without letting it overshadow the accuracy and integrity of their work.
Team Exterro.
For those looking to deepen their understanding of where the real risks lie — and how to adopt GenAI without turning it into a liability — this year’s eDiscovery Day webcast, GenAI on the Record: Redefining eDiscovery Without Raising Risk, will feature experts who have been navigating these challenges firsthand. Their guidance aims to help teams embrace AI’s potential while ensuring that defensibility, privilege, and sound legal judgment remain firmly at the center of discovery.
Learn more about eDiscovery Day, happening on December 4th!
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Assisted by GAI and LLM Technologies per EDRM GAI and LLM Policy.
