Defensibility in the Age of GenAI Review: What Every Practitioner Needs to Know

Defensibility in the Age of GenAI in Document Review: Clear Insights for Legal Practitioners

The Game-Changer in eDiscovery

The emergence of Generative AI (GenAI) has transformed eDiscovery and legal document review faster than most imagined possible. With capabilities like automated definition crafting, citation verification, and predictive calibration based on past data, what practitioners once viewed as the most painful part of legal cases—document review—has the potential to become efficient, defensible, and even enjoyable. But advancements come with new questions. Can legal professionals trust the insights generated by AI? Will the courts accept GenAI review processes? How can practitioners defend GenAI-assisted results to clients and opposing counsel?

These are critical tensions in the modern legal landscape, and Reveal’s webinar titled “Defensibility in the Age of GenAI Review: What Every Practitioner Needs to Know” tackled them head-on. Hosted by George Socha(SVP of Brand Awareness at Reveal) and featuring expert insights from Bennett Borden (Founder & CEO of Clarion AI Partners) and Irina Matveeva(Chief of Data Science & AI at Reveal), the session broke down practical frameworks for integrating GenAI into discovery workflows without losing defensibility or transparency.

In this webinar, we unpack key takeaways from the webinar and explore how Reveal’s GenAI-powered review system addresses the most pressing practitioner concerns.

What Does “Defensibility” Mean in the GenAI Era?

In the legal discovery process, "defensibility" isn’t just an abstract quality—it’s the cornerstone of a reliable workflow. It means being able to explain, validate, and defend the steps taken during document review to your client, opposing counsel, and potentially, a judge. Historically, defensibility has relied on human oversight, statistical checks, and technology-assisted solutions like predictive coding.

GenAI, a type of artificial intelligence that makes sense of unstructured data at unprecedented speed and scale by fine-tuning prompts, calibrating results, and adapting human-like contextual reasoning. While these capabilities sound revolutionary, many in the legal field remain cautious, pondering questions like:

1. Can GenAI truly replicate the nuance of traditional legal analysis?
2. How do we ensure transparency in complex models?
3. What happens when results need to be explained in court or cross-examined?

Answering these questions requires an updated framework for defensibility. One of the webinar’s most practical contributions was revealing how Reveal’s GenAI-assisted workflow, assessed independently by Bennett Borden, meets these challenges head-on.

Webinar Takeaways: A Practitioner-Focused View

1. Transparency Builds Trust

Transparency is the foundation of defensibility, and Reveal’s GenAI framework offers multiple layers of it. Bennett Borden, who evaluated the platform independently by analyzing over 33,000 legal documents from his firm, emphasized this point. He highlighted Reveal’s built-in reasoning engine, which doesn’t just classify documents as relevant but tells users why with contextual “definitions” and fully traceable citation trails.

This feature is designed to address a growing concern among legal teams. Even if GenAI produces accurate results, how can its outputs be assessed by humans without a PhD in data science? Reveal’s tools simplify this process, practitioners can now scrutinize results without relying on blind trust in algorithms, strengthening confidence for internal teams and external defenses alike.

2. Defensible Calibration Is Key

One of the webinar’s standout moments was Bennett Borden’s walkthrough of how calibration works with Reveal’s GenAI tool. He described the process as iterative but intuitive:

Start by crafting a definition—a plain-language prompt describing what you’re looking for.

Test sample documents against the AI’s initial output.

Refine the definition iteratively until you achieve alignment between your legal strategy and the AI’s interpretations.

In Bennett’s experiment with Reveal, he ran multiple calibration rounds until the system’s results consistently reached a near-perfect agreement rate:

“I went through several 10 to 12 iterations of a definition... My definition got better and better as I went along through this calibration process.”

– Bennett Borden, Founder & CEO of Clarion AI Partners

Calibration is a big shift for legal teams, who are used to relying heavily on long lists of search terms. But GenAI’s ability to refine contextual prompts makes the arduous validation process more streamlined. Bennett ended up with a remarkable 96.95% agreement rate between the AI’s classifications and his independent review—an unheard-of outcome compared to traditional techniques.

3. Empirical Evidence Strengthens Defensibility

One of the most significant hurdles for GenAI adoption in eDiscovery is the lack of existing judicial precedents to validate it. Currently, no court has expressly blessed GenAI review protocols. However, the panelists argued that practitioners can still build credible workflows by relying on established defensibility practices: empirical validation processes like sampling, testing definitions, and statistical reporting.

In Bennett’s case, applying these tried-and-true methods to generative AI enabled him to confidently defend his results, even in the absence of case law precedents:

“If you use a GenAI workflow well and then do all the things you know to do... there’s nothing for the other side to hang their hat on.”

– Bennett Borden, Founder & CEO of Clarion AI Partners

If courts could eventually accept predictive coding and Technology-Assisted Review (TAR), there’s no reason GenAI-assisted workflows—with sufficient evaluation and documentation—can’t achieve similar recognition.

4. Practitioners Need Intuitive Tools

Adopting a highly technical solution like GenAI doesn’t have to mean hiring data scientists or slogging through elaborate training manuals. Bennett praised Reveal’s user experience, noting that even complex workflows were easy to navigate:

“Some of these interfaces can be so complex... what I found really easy to use was that it kind of walked you through the process... Optimizing my prompt actually helped clarify my thinking about what it was I was asking for.”

– Bennett Borden

Reveal’s definition coach feature proved especially valuable, guiding users to tighten their prompts and calibrate effectively, a design decision that simplifies the onboarding process for busy attorneys juggling high-stakes projects.

Moving From Hesitation to Confidence

The webinar demonstrated that legal professionals can overcome hesitation about GenAI adoption by focusing on three core principles: transparency, defensibility, and ease of use. While GenAI is undoubtedly powerful, its adoption doesn’t require completely reinventing workflows or relying on blind trust in automation. Thoughtful calibration and empirical validation remain hallmarks of robust document review processes.

Reveal shines as a leader in this space by combining cutting-edge AI with practitioner-focused tools designed for real-world defensibility. As Irina Matveeva, Reveal’s Chief of Data Science & AI, indicated, the platform is built to support attorneys every step of the way.

“What we’ve created is a system deeply integrated with the calibration process and built-in AI advisors to help guide users through crafting definitions that are meaningful... That’s your starting point.”

Want to Learn More?

Missed the webinar? Catch the full conversation on-demand to hear directly from Bennett Borden and George Socha about how Reveal’s GenAI system provides defensibility and transparency for document review.

Ready to see Reveal in action? Request a demo to explore how this tool could transform your workflows today.