Artificial Intelligence (AI) has moved from being a promising innovation to a practical tool transforming how legal teams approach document review. Once dominated by human reviewers spending hours analysing documents for relevance, privilege, and key facts, today’s document review process is evolving rapidly with AI tools offering speed, accuracy, and insights that were previously unimaginable.
In a recent webinar session Phillip Buglass, Director of Consulting and Document Review at Law In Order, shared valuable insights into how AI is being applied in real-world review projects. Drawing from over 20 years in legal tech, Phillip explained that while AI has supported document review for years through things like analytics and Technology Assisted Review, it is the recent shift into generative AI that is changing the game.
From Traditional Tools to Generative AI
Where older tools focused on sorting and predicting document relevance, newer AI systems go further. These models are trained to understand language, extract meaning, and generate concise summaries. In document review, this means AI can now interpret documents, highlight key issues, and even explain why a document might be relevant or privileged within seconds.
Phillip likened this process to briefing a review team. You start by giving the AI a clear overview of the matter, key people, issues, terms, and the AI reviews the documents based on those inputs. If you do not yet have a clear overview of your matter, AI review can help you build a clearer picture as you go by finding and offering early insights into your key documents.
While AI in legal review isn’t new, technologies like Technology Assisted Review (TAR), email threading, and clustering have been in use for over a decade. With the rise of Large Language Models (LLMs) and Generative AI, we are now seeing tools that do more than sort and prioritise. These tools can interpret content, extract meaning, summarise documents, as well as highlight inconsistencies between computer and human coding decisions.
Tools in Action: Bridging AI and Legal Review
During the session, Phillip also gave attendees a look at some of the AI tools that are already making a difference in legal workflows. Tools like Relativity aiR and Cicero are now being used to streamline document review and early case assessment, as well as to extract key data points and rapidly build chronologies of key events.
Relativity aiR supports review by predicting document relevance and privilege, while also providing rationale and citations so legal teams can understand why a document is flagged and validate the predictions being made. It allows users to brief the system much like they would a human reviewer using matter overviews, coding instructions, and key issues as prompts.
Cicero enables teams to rapidly summarise documents, extract structured information from legal content (including contracts and bank statements), and generate case timelines. It also includes validation tools to help reviewers refine their input and check for inconsistencies.
Benefits That Can’t Be Ignored
The benefits of using AI in document review are becoming more difficult to overlook:
Speed: AI can review thousands of documents per hour, giving legal teams faster access to critical insights.
Cost-efficiency: With AI, per-document costs are generally lower, especially compared to reviews led by lawyers or junior staff.
Accuracy: Studies have shown AI can outperform humans in identifying relevant documents, provided it is used correctly.
Scalability: AI makes it easier to manage large volumes of data without expanding review teams.
Human Expertise Still Matters
Despite these advances, human input remains essential. Creating clear, well-structured prompts is now a crucial skill. Lawyers need to know their facts, be able to identify key people, and define key terms. The clearer the prompt, the better the AI performs.
Equally important is validation. AI tools are powerful, but not infallible. Quality assurance (QA) workflows are still vital to ensure consistency, accuracy, and defensibility, particularly when results are presented in court. Monitoring borderline decisions, conflicts between human and AI coding, and continuously refining prompt instructions are key elements of a robust review process.
In Phillip’s experience, firms using these tools are not only meeting tight deadlines but also gaining better visibility into their data earlier in the case.
What’s Holding People Back?
Despite these benefits, adoption is still cautious. Part of that comes from early court guidance, which advised careful use of generative AI. But the guidelines are changing. There’s growing support for AI use in tasks such as document review and summarization as long the parties using them are transparent about their use and apply rigorous validation and quality checks.
Conclusion:
AI in document review is not just a buzzword, it is becoming a practical, everyday tool that’s helping legal teams save time, reduce costs and get better results, and it is steadily becoming part of everyday legal workflows. The question will soon be why you are not using AI rather than why you are not? Rather than replacing legal expertise, AI tools are helping legal teams free up their time to focus on what really matters.
If you haven’t explored how AI can support your document review processes, now is the time to start.
Want to see how these tools could fit into your workflow?
Contact our team to arrange a demo or speak with a consultant about your review needs.
