Evidence discovery has always been demanding work. But the nature of that demand has changed in ways that many legal teams and the organisations supporting them have not fully reckoned with yet.
It used to be a volume problem. How do you get through enough documents quickly enough to find what matters? That was difficult, but it was at least a problem with a familiar shape. Hire more people, allocate more time, work through it systematically.
What has changed is not just the volume. It is the complexity underneath it.
The environment discovery was designed for no longer exists
Most discovery processes were built around a set of assumptions that made sense at the time.
That documents live in predictable places. That review can happen sequentially. That the challenge is thoroughness rather than navigation. In a world of paper files and contained email archives, those assumptions held reasonably well.
They do not anymore. According to research cited by Pinsent Masons, 99.7% of correspondence is now electronic[1], and around 80% of all enterprise data is unstructured, growing roughly three times faster than structured data[2]. Evidence today is dispersed across email systems, collaboration platforms, cloud environments, shared drives, legacy databases, and devices that may or may not be actively managed by the organisation’s IT function. The average organisation generates more data in a week than it might once have generated in a year. And when litigation arises, all of it is potentially in scope.
Manual review was not designed for this environment. Applying it anyway does not just create inefficiency. It creates risk. Not because the people doing the review are not diligent, but because the sheer scale of what needs to be reviewed makes it genuinely difficult to be confident that nothing significant has been missed. The Civil Procedure Rules in England and Wales recognise this directly. Practice Direction 31B requires parties and their legal representatives to discuss the use of technology in managing electronic documents before the first case management conference[3], an obligation that assumes a level of capability traditional manual review processes are not built to deliver.
What gets missed, and what that costs
This is the part of the conversation that does not get enough attention.
When discovery processes cannot keep pace with data volumes, the instinct is to talk about timelines and costs. Both are real. But they are not the most serious consequence.
The most serious consequence is invisible, and that is precisely what makes it dangerous.
A pattern across a series of communications that only becomes visible when you can interrogate them as a dataset. A connection between two documents sitting in different systems that nobody thought to look for because the review was structured around individual files rather than relationships. Evidence that existed, was technically accessible, and never surfaced because the search was not built to find it.
By the time those gaps become apparent, you are usually deep into a case. The cost of adjusting strategy is high. The cost of not adjusting it can be higher. And the uncomfortable truth is that you do not always know what you missed. You just know that the picture you built your case around turned out to be incomplete.
That is not a process failure in the abstract. That is a case outcome that went the wrong way because the discovery foundation was not fit for the environment it was operating in.
What digital transformation actually makes possible
Here is where the conversation usually pivots to technology, and it is worth being specific about what that actually means in practice, because “digital transformation” gets used loosely enough that it can mean almost anything.
In the context of evidence discovery, the meaningful shift is this: modern tools make it possible to work across entire datasets rather than through individual documents.
Instead of reviewing sequentially and hoping the important material surfaces before the deadline, legal teams can search across the full body of evidence simultaneously. Relationships between documents become visible. Patterns in language, timing, and communication emerge. Relevant material can be identified and prioritised much earlier, and the analysis that follows is built on a more complete picture.
The market has responded accordingly. The legal AI software market is projected to grow from $3.11 billion in 2025 to $10.82 billion by 2030, with eDiscovery dominating the application segment driven by the exponential growth of electronically stored information across litigation, compliance and regulatory investigations[4]. Lighthouse’s second annual State of AI in eDiscovery Report found that enterprise AI usage among the legal teams surveyed nearly doubled in a year, from 20% to 39%, with the industry shifting from “experimental AI” to “operational AI” embedded directly in workflows[5].
AI does not replace legal judgement. It handles the parts of the process that do not require it (sorting, prioritising, flagging connections) so that the people whose judgement actually matters can spend their time on analysis and strategy rather than retrieval. Used well, it makes experienced legal teams considerably more effective. It does not make them redundant.
The gap between having the tools and being able to use them
There is a version of this story where organisations invest in modern discovery platforms and find that they do not deliver what was promised. It happens more than the technology vendors tend to acknowledge.
The reason, almost invariably, is the data.
Advanced discovery tools are only as effective as the information they are working with. If documents are unstructured, inconsistently indexed, stored in formats that are not searchable, or spread across systems in ways that make them difficult to access, the technology cannot compensate for that. It will surface what it can find, structured the way it finds it. The gaps in the data become gaps in the insight.
This is where a lot of organisations fall short. They focus the investment on the tool and underinvest in preparing the data that makes the tool work. The result is sophisticated technology running on a foundation that limits what it can deliver.
What a better foundation looks like
Getting discovery right in a modern data environment starts with the data itself.
Documents need to be digitised properly. Not just scanned and stored, but indexed, structured, and made searchable in a consistent way. Information needs to be accessible from the systems where it lives without requiring manual extraction every time. Metadata needs to be applied consistently enough that analytical tools can orient themselves within the dataset and surface what is relevant.
None of this is technically complicated. But it requires deliberate attention, and it tends to be the work that gets deprioritised in favour of the more visible parts of a technology implementation.
When it is done well, the difference is tangible. Faster access to relevant material. Earlier identification of key evidence. Case preparation that is informed by a more complete picture from the outset. And the kind of confidence that comes from knowing that the process is working with the full dataset rather than whatever portion of it was easiest to reach.
How Dajon helps organisations build that foundation
At Dajon Data Management, this is precisely the kind of challenge we work on.
We help organisations digitise, structure, and prepare their legal data so that it is genuinely ready for modern discovery. Not just stored digitally, but accessible, searchable, and organised in a way that analytical tools can actually work with. The goal is to make sure that the technology investment an organisation makes in discovery is supported by a data foundation capable of delivering on it.
For legal teams, that means being able to work with the full picture. For the organisations they support, it means discovery that moves at the pace the situation demands rather than the pace the data allows.
The organisations that will struggle and the ones that will not
Evidence discovery is evolving whether organisations are prepared for it or not. But it is worth being direct about what the difference actually looks like in practice, because it is not as simple as who has invested in technology and who has not.
The organisations that will struggle are not necessarily the ones ignoring the problem. Many of them have invested in platforms. Some have run pilots. A few have launched transformation programmes with discovery somewhere on the roadmap.
What they have not done is fix the data underneath it.
And without that foundation, the investment in tooling delivers a fraction of what it should. Faster searches through incomplete data. More sophisticated analysis of a dataset that does not reflect the full picture. The appearance of modern discovery without the substance of it.
The organisations that will not struggle have understood that the technology is the easy part. The harder, less visible, less celebrated work is making sure the data those tools run on is structured, accessible, and genuinely ready to be used. That is where the real capability gap sits. And in litigation, where the quality of your evidence preparation has a direct bearing on outcomes, closing that gap is not an operational nicety.
It is a strategic necessity.
Is your discovery process evolving with your data, or is it still built for an environment that no longer exists?
Dajon Data Management helps organisations prepare their legal data for modern evidence discovery. Get in touch to understand where your current data environment might be limiting what your discovery process can deliver.
References
- Electronic disclosure in England and Wales Pinsent Masons[↩]
- Possibilities and limitations of unstructured data Research World[↩]
- PRACTICE DIRECTION 31B – Disclosure of Electronic Documents Civil Procedure Rules[↩]
- Legal AI Software Market Report 2025-2030 MarketsAndMarkets[↩]
- 2025 AI in eDiscovery Report: Key Insights & Trends Lighthouse[↩]