AI in Document Review Is Evolving—But It’s Not Plug-and-Play

The conversation around AI in the legal industry has shifted dramatically. Today, clients have more tools, more options, and more access to generative AI than ever before. From Harvey to Claude to a growing ecosystem of AI-powered applications, it can feel like document review should be faster, easier, and fully automated.

But that assumption is where the disconnect begins. The future of document review isn’t about choosing a single AI tool. It’s about orchestrating the right combination of technology, workflows, and expertise to deliver accurate, defensible outcomes at scale.

The Expanding AI Landscape—and the Knowledge Gap

Legal teams are exploring a wide range of AI capabilities. Many tools are powerful, intuitive, and highly effective—within the right context. But not all AI is built for document review.

That distinction matters.

As noted in our conversations with clients, many assume these tools can be applied universally—that you can “put information in and get exactly what you want out.” In practice, different AI technologies are designed for very different purposes.

The Three Broad Categories of AI in Review

To understand where the market is headed, it helps to break AI in document review into three functional categories:

1. Generative AI (e.g., Harvey, Claude)
These tools excel at:

• Drafting legal memos
• Summarizing documents
• Answering prompts in natural language

They are incredibly useful for knowledge work and early-stage analysis. But they are not purpose-built for review. They are designed to generate responses, not to manage large-scale document populations or support defensibility. Outputs still require validation—sometimes negating efficiency gains if applied incorrectly.

2. Analytics-Driven Review (e.g., TAR, CAL)
These tools represent the evolution of technology-assisted review:

• Prioritizing likely responsive documents
• Reducing overall review population
• Supporting validation workflows

They improve efficiency but still operate within defined boundaries. They help you find things faster—but they do not fully explain or justify decisions.

3. AI-Powered Review Workflows (e.g., Relativity aiR)
This is where the market is moving. AI workflows designed for review:

• Leverage frontier LLMs guided by user-defined relevancy prompts
• Apply consistent, document-level reasoning
• Provide transparency into why a document is responsive or privileged with information that is pulled directly from the document itself
• Extend into downstream workflows (deposition prep, case strategy, trial readiness)

These systems are purpose-built to handle large-scale review—whether 40,000 documents or millions—while maintaining defensibility. They don’t just surface documents. They connect insights across the lifecycle.

What Makes Document Review Unique

Document review is not just another AI use case. It carries unique requirements:

• Defensibility: Every decision must be explainable
• Consistency: Decisions must be applied uniformly across large datasets
• Scale: Reviews often involve hundreds of thousands to millions of documents
• Downstream impact: Review decisions influence depositions, case strategy, and trial

This is where many emerging AI tools fall short. They can support pieces of the workflow, but they are not designed to manage the full lifecycle of review. Purpose-built AI enabled workflows, on the other hand, are designed to show their work—linking outputs directly back to the source documents and providing a defensible record of decision-making.

The Rise of AI Orchestration

With so many tools available, the challenge is no longer access to AI—it’s knowing how to use it effectively. This is where orchestration becomes essential.

AI orchestration is the practice of:

• Selecting the right tools for each stage of review
• Integrating workflows across platforms
• Validating outputs to ensure accuracy and defensibility
• Aligning technology decisions with legal strategy

It’s not about replacing one tool with another. It’s about coordinating multiple capabilities into a cohesive, outcome-driven process. Because even the most advanced AI tools—on their own—are incomplete. Many solutions “only encompass one piece” of the workflow. Without orchestration, gaps emerge between analysis, review, and downstream use.

The Role of Cimplifi: From Tools to Outcomes

This is where Cimplifi plays a critical role. In a market full of options, we serve as the connective layer—bringing together:

• Purpose-built review technologies like Relativity aiR, designed for large-scale, defensible document review
• Complementary analytics capabilities, including conceptual analytics, machine learning and custom generative AI, applied where they add the most value
• Structured review workflows and proven methodologies that ensure consistency, quality, and defensibility
• Deep domain expertise across litigation, investigations, and regulatory matters

Our role is not just to deploy technology—it’s to guide clients from start to finish, ensuring that every decision supports the broader goals of the matter.

That includes:

• Designing review strategies aligned to case objectives
• Validating AI outputs to reduce risk
• Connecting review insights to deposition prep and trial strategy
• Anticipating next steps—not just immediate deadlines

Because document review is not a stand-alone task. It’s a foundational step in achieving successful legal outcomes.

The Bottom Line

AI is transforming document review—but not in the way many expect.

The future isn’t:

• One tool replacing human reviewers
• Or a single AI generating perfect answers

The future is:

• Intelligent, purpose-built workflows
• Multiple AI technologies working together
• Expert orchestration ensuring accuracy, defensibility, and impact

AI can accelerate review, but only orchestration makes it work.

About the Author

Lisa Moini is the director of AI‑powered review at Cimplifi, where she leads the delivery of scalable, defensible managed review services. With over 20 years of experience in complex review programs, she brings deep expertise in review strategy, workflow design, and operational execution across high‑stakes matters, including antitrust, government investigations, and intellectual property litigation. Lisa holds a J.D. from Syracuse University College of Law and is admitted to the New York State Bar.