Top eDiscovery Myths - BUSTED

I may not be blowing up cars in the desert like Adam Savage, but busting eDiscovery myths? That’s my happy place. Whether it’s a stubborn misconception from the early aughts or a vendor pitch dressed up as gospel, nothing gets this Technocat more fired up than calling BS on the outdated ideas that still haunt our workflows.

Let’s shine a light on the myths we’re overdue to retire—and the truths your litigation support team already knows in their bones.

Myth 1: A Gig is a Gig

Spoiler alert: it’s not. One gig of PDFs is not the same beast as one gig of Slack exports in JSON. Factor in expansion, nested data, embedded files, and parsing for review, and suddenly your “few gigs” just blew past your processing window and your budget. Data today isn’t just big, it’s messy, weird, and deeply misunderstood by anyone quoting size alone.

Whether you are an in-house team trying to budget for a pending investigation or a service provider scoping preservation and collection, it is easy to fall into the Myth of a Gig is just a gig when estimating data volumes, cost, and timing in a matter. And having the right tools for the Jobs has never been more important.  

With the prevalence of atypical data sources that leverage new data formats and compositions, the old tricks of the trade and back of the napkin estimates are often far from the truth. Electronically Stored information, (ESI) on a comment from slack in a .JSON file format may at first export as no more than a few lines, but when you parse it for review it may expand greatly. Each data type poses unique considerations in terms of timing, workflow, and which tools to use. Certainly, more to consider than merely number of Gigs at issue.

Myth 2: AI is Too... Expensive & Complicated

The Myth of costly and hard to use AI has its roots in fact, as most great myths do. That was true back when TAR needed a PhD, a linguist, and a three-day partner briefing. But we’ve evolved. AI is now baked into the platforms you’re already using, and it works more like Netflix than a NASA launch sequence. If you know how to stream a crime doc, you can run a relevance model. Cost barriers? Gone. Complexity? Optional.

Early iterations of AI in legal, al a da Silva Moore and TAR 1.0 required linguists, statisticians, time to train and could boast price tags that rivaled the cost to process data at the outset. Times, and legal AI, have changed substantially. Today many of the leading AI in legal is baked into next-gen technology at no additional cost and the user experience is more akin to google and Netflix than the onerous AI workflow of TAR 1.0.  

Using Legal AI in your eDiscovery process is much simpler than the first iterations of Predictive Coding over a decade ago. And the cost and time savings are too massive to pass up on!

Myth 3: Human Review is the Gold Standard

Let’s be honest. Unaided human review is the gold standard only if your goal is exhaustion, inconsistency, and missing hot docs at 2 a.m. Machines aren’t replacing reviewers, Yet, But they are boosting recall and precision while keeping your team sane. Grossman and Cormack proved it over a decade ago. If you’re still insisting on eyeballing every doc, you’re not being thorough, you’re being inefficient.

When legal professionals are facing a large-scale document review to uncover potentially relevant ESI, it is easy to believe that a human is the best option. Unaided human review has consistently underperformed compared to human teams leveraging technology is studies by NIST and more recently in a swath of academic studies.

Maura Grossman Said it best in her article Maura R. Grossman & Gordon Cormack, Technology-Assisted Review in E-Discovery Can Be More Effective And More Efficient Than Exhaustive Manual Review, XVII Rich. J.L. & Tech 11: . . . technology-assisted processes, while indeed more efficient, can also yield results superior to those of exhaustive manual review, as measured by recall and precision. In simple English, man plus machine is more accurate and inclusive of all potentially relevant data than unaided human review.

Myth 4: All eDiscovery Software is the Same

If you've ever tried to review a few million documents in the wrong tool and faced the spinning wheel of death, you know this is a lie. Some platforms were built for scale, others for speed. Some offer real AI, others just slapped “insight” into their UI. Your platform should fit your matter, not force you to rebuild workflows and pray the load file survives the trip.

If you ask many attorneys or case teams about eDiscovery review software, it may seem that we are talking about the difference between beige and taupe... that there is only a nominal difference between eDiscovery solutions on the market today. While that may have been the case a decade ago, for legal professionals facing eDiscovery today, the tool you choose can have a massive impact on speed to insight and both cost and efficiency of your review.

That is why at Reveal we have 2 platforms (Reveal & Logikcull) in our ecosystem to offer support on matters and challenges large or small.  

Myth 5: eDiscovery Just Means Email

This one belongs in a museum. Email is just the gateway drug. Real ESI lives in Slack, Teams, Signal, ephemeral chat, emojis, Zoom recordings, cloud links, Google Docs, and whatever third-party platform your custodians forgot to mention. The four corners of a document haven’t been enough since Blackberrys had scroll wheels.

It was easy to assume the “E” in eDiscovery stood for email back in the day, because there simply were not that many forms of ESI. Today when scoping a custodian’s potentially relevant ESI, there are potentially dozens of places to look for ESI. From Collaboration tools to social media, email to a variety of short format and ephemeral messaging platforms. Relevant “documents” are often a far cry from the four corners of a page that most people first conceived in discovery.

Myth 6: Only Big eDiscovery Cases Need AI

You don’t need a 10-million-doc matter to benefit from legal AI. You just need messy data, tight timelines, or a judge who wants results and not excuses. Smart filters, concept clustering, sentiment analysis and GAI powered search and review scale up and down. And thanks to platform evolution, you can use them out of the box, without triggering a budget panic.

The application of AI in electronic discovery has long suffered from goldilocks complex when it comes to AI. Many believing that only large, complex, or otherwise special snowflake types of cases could (if the myth was to be believed) benefit from the application of Ai in the eDiscovery process. As with a few myths that preceded this one, there is some truth in the roots of this myth. But as with technology and AI in other aspects of our life, the tech has become more robust, user friendly and adaptable.

Cases large and small can benefit from the application of legal Ai because the tech can start providing insights with hundreds of documents instead of thousands and the prior cost barriers to using AI have to a great degree been eliminated by baking the Ai into the core eDiscovery review platforms.

Myth 7: eDiscovery Software is Only for Litigation

Litigation is just the headline in the eDiscovery-verse. eDiscovery tools are quietly crushing it in investigations, DSARs, compliance audits, cyber breach response, antitrust reviews, M&A diligence, you name it. If it involves unstructured (human created) data and a need for speed and defensibility, you need more than Outlook and a spreadsheet.

When most people think of the unstructured data analytics tool that comprise eDiscovery software, the first applications that comes to mind is litigation. But that is far from the only impactful way to use eDiscovery software. While the workflow applied may differ in cases that are due diligence, investigations, proactive compliance or post breach, the insights offered by unstructured data analytics and the EDRM are still robust.

Myth 8: One eDiscovery Tool Can Rule Them All

There is no magic hammer or one eDiscovery ring to rule them all. You need connectors, overlays, specialty tools, and the wisdom to know when to switch lanes. You wouldn’t run a cross-border FCPA investigation the same way you’d review a trade secret theft from Slack. Don’t expect one tool to do both well.

As cases have evolved and workflows and objectives have expanded beyond the traditional litigation context or to data sets and metadata beyond documents and email, the tools, and techniques best suited for cases have evolved as well. A varied applications of eDiscovery has opened the world up for more bespoke applications of tool and techniques. Having many arrows in your quiver when seeking to uncover potentially relevant ESI in the high velocity digital data verse of today is critical.

Myth 10: Data Volume Is the Problem

When it comes to eDiscovery, the mountain of data is a challenge but there are other hurdles to your seamless ascent to the smoking gun. Size matters less than shape. Ten gigs of tidy emails? Manageable. One gig of nested chat threads with embedded gifs, reactions, and audio clips? That’s your weekend gone. The problem isn’t volume, it’s variability. And if your tech doesn’t parse that complexity, you’ll drown in it.

When you are looking for the right tool to fit your matter, ensure you have one that effectively renders the type of data you are reviewing. That connects to not just your M365 but also the plethora of platforms that people conduct the business of business in today. Hello Slack, Teams, Zoom, WhatsApp and SMS to name a few.

The Takeaway?

eDiscovery isn’t what it was 10 years ago. So why are we still clinging to myths from the Blackberry era? If any of these hit a nerve, you’re not alone. But the good news is you don’t have to keep settling. There are better tools, smarter workflows, and yes—actual choices now.

More myths coming soon. Because let’s be real… we’re just getting started.