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How Often Clients Forget a Data Source at Intake

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Quick Answer

No published study measures how often clients forget a data source at intake. The pattern is steady all the same: personal phones, home computers, chat workspaces and AI tools go unmentioned.

A written inventory, a planned second conversation and an early test against the collection catch the gap. Caught early, it is a note in the file. Caught late, it is a spoliation argument. Gartner peer respondents describe companies that permit only approved AI tools, which makes any other tool a source to ask about by name.

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Key Points

  • In a 2026 survey of 101 legal professionals republished by EDRM, 31% named working with clients to collect their own data as a firm-level challenge.
  • Federal Rule of Civil Procedure 37(e) asks whether a party "failed to take reasonable steps to preserve it," and the September 2014 amendments reserved the harshest sanctions for intent to deprive.
  • ComplexDiscovery figures show collection rising from 8% of eDiscovery task spending in 2012 to 16% in 2024, while review fell from about 73% to 64%.
Three things litigators believe about intake. Myth or fact?
Call each one, then see how other readers called it.
1 A careful client will name every data source in the first meeting.
2 Better collection software will close the gap on its own.
3 A personal device used for work can pull its whole contents into discovery.
Photorealistic editorial still life on a walnut conference table in soft late-afternoon window light: a fountain pen resting beside a bare leather desk pad, a small external hard drive set slightly apart, a brass desk

The sources a client forgets often sit within arm's reach of the intake notes.

Review costs least when it runs once, on a complete collection. A source found after review begins reopens collection, processing and review for every document it holds.

That is why this article starts at intake rather than inside the review platform. The forgotten source is rarely exotic. It is a personal account, a chat workspace someone else set up, or the mailbox of an employee who has since left, each sitting just outside the client's sense of where the work actually lived.

The newest entry on that list is AI. On Gartner's Peer Community, a director of infrastructure in healthcare and biotech described a team that uses only officially approved AI tools and keeps "passwords, personal data, client info, or financials" out of them. A vice president of AI innovation on the same forum observed that "people tend to forget about how much their data is ready to be used by LMs." When a company draws that line, whatever crossed it tends to sit in places no one thinks to list.

Approved tools leave records. Unapproved ones leave gaps.

What follows moves in order: the sources clients leave out, the moment an omission turns into a spoliation argument, and a way for a small firm to run an inventory it can afford. For a solo or small firm on a single messy matter, the early look at the data has to run without an administrator, which is the segment Relevant was built to serve.

A client's first account of where their data lives is rarely the whole account. Medicine has known this for a long time. In a 2024 thread among emergency physicians and nurses, one commenter observed that patients tell "at least 3 different stories" during a single visit, to the triage nurse, the bedside nurse and the physician, and that these "usually are all different." Another put it more plainly: "you will not get the whole story."

Legal intake, to my mind, behaves the same way. A client answers the questions put to them, in the order they are put, from memory. Memory is selective.

The gaps tend to settle where work was improvised. When remote work arrived abruptly in March 2020, firms built home arrangements that put business continuity ahead of security, and ABA Formal Opinion 498 later cautioned against free or consumer-grade products. By late 2021 the temporary had become the new normal. A home computer shared with family, a personal phone: neither feels like company data to the person who used it.

The honest starting point is a gap of its own. Statisticians, at least, have a name for an answer that is only partly complete. The U.S. Census Bureau, which studies missing data for a living, counts partial response as a distinct form of missing data: people who "give only part of the information they are being asked to provide."

Which data sources do clients forget to mention at intake?

No published study measures how often a client's source list is incomplete. The recurring omissions are known, though: personal email, vendor-run chat, phones, portable media and AI prompts.

Before I would accept a client's list as complete, I would put four plain questions to it:

  1. Did you ever forward work documents to a personal email or cloud account?
  2. Did anyone outside the company, such as a vendor, set up a workspace or chat channel for this project?
  3. Which phones, tablets or portable drives touched the matter, including ones no longer in use?
  4. Did you use an AI tool to draft anything, and do you still have what you typed into it?

The closest figure the market offers is a reported challenge, not a measured gap. In one vendor's 2026 survey of 101 legal professionals, 31% named working with clients to collect their own data as a firm-level challenge, the third most common answer. That figure does not show how many source lists were wrong. Survey statisticians hold themselves to a stricter bar: OMB's 2006 standards set an 80 percent response-rate threshold, below which a survey needed a detailed review of its errors, and I know of no equivalent test for an intake list.

The common assumption is that a client who knows the business knows where its data lives. The examples in that same vendor's guidance suggest otherwise: a custodian ticks the box for company email and never mentions the personal Gmail account used to forward documents, or the Slack workspace a vendor set up for the project.

The pattern is older than the cloud. Writing in the Florida Bar Journal in February 2002, Stephen M. Cohen listed PDAs, memory disks, telephone logs and cellular phones among the sources commonly overlooked, and observed that "while some types and sources of electronic data are commonly thought of, others are not." The devices have changed. The blind spot has kept its shape.

The newest entry is quieter still. In a September 2025 Florida Bar News report, Indiana University law professor Josh Kubicki warned that "most clients aren't disclosing when they've used AI," and that even those who do "often forget the more important part: what they told the AI to get the draft."

Volume has not made any of this easier. In 2024, 93% of 30 surveyed litigation support directors reported that the data they manage per dispute was increasing, and one respondent said sources and types worried them more than volume did.

The Census Bureau's missing-data program offers a test a lawyer can borrow: an answer that is logically inconsistent is "in effect missing," so when the client's account of the dispute mentions a channel the source list omits, the list is incomplete. The forgotten source sits just outside what the client thinks of as work. The omission is rarely deliberate. It is a matter of where attention falls.

Part of the hesitation is about where the data will go once it leaves the client's hands. That is one reason Relevant e-Discovery deploys inside the firm's own AWS account, under the firm's own keys, a posture few small-firm tools can match. Clients who ask whether a review platform learns from their files deserve a direct answer, and the question of whether your e-discovery AI trains on case data is worth settling before the custodian interview begins.

A source that surfaces only after the hold should have reached it is no longer an intake question. It becomes a preservation question, argued before a different audience.

Which source will your next client forget?

We went looking for a number: how often a client's list of data sources comes back incomplete. Nobody has published one. What we found instead was a pattern old enough to predict.

The closest figure comes from a 2026 survey of 101 legal professionals. An eDiscovery software company ran it, and EDRM republished the results. Working with clients to collect their own data ranked as the third most common firm-level challenge, named by 31% of respondents. That shows the problem is painful. It cannot show how often a source goes missing. One respondent, a litigation paralegal at a government agency, described what it feels like: "Our clients maintain records in multiple places making it difficult to collect all in one swoop."

Since nobody has counted how often sources go missing, we looked at which ones. Lawyers have been listing overlooked sources for decades, and the older lists read strangely now.

YearWho flagged itSources named as overlooked or hard to capture
2002Stephen M. Cohen, Florida Bar JournalPDAs, memory disks, phone logs from dial-up internet, cell phone call logs and calendars
2014A senior vice president at an eDiscovery provider, on The ESI Report podcastFacebook, instant messaging, phone apps, cloud storage, personal devices
2025Josh Kubicki, Indiana University law professorWhether a client used AI, and the prompts behind the draft
2026Survey guide republished by EDRMA personal Gmail account used to forward documents, a Slack workspace a vendor set up

In 2002, Cohen warned Florida lawyers that "while some types and sources of electronic data are commonly thought of, others are not." He pointed to the cell phone, which "retains computer-generated information." 12 years later, a podcast guest named social media, messaging, apps, cloud storage and personal devices as the sources hardest to bring under retention policies and legal holds. Read in order, each list names what was new at the time, sitting beside the email and desktop files everyone already expected.

The current list is more personal. The 2026 guide describes a custodian who checks a box for "company email" without mentioning "the personal Gmail account they used to forward documents, or the Slack workspace a vendor set up for the project." Its explanation is plain: "Clients don't think about their documents the way lawyers do." Nothing in that diagnosis assumes anyone is hiding anything.

The newest item on the list may be the hardest to get out of a client. "Most clients aren't disclosing when they've used AI," Kubicki wrote in 2025. Even when they do, he added, "they often forget the more important part: what they told the AI to get the draft." He was writing about privilege risk in AI drafts, but the prompts he mentions are saved somewhere: "Many consumer-grade AI tools store prompts." Tyson Martin, who advises companies on AI governance, argues that some prompts and outputs become business records once they are used in decisions or customer communication, so retention and eDiscovery rules should be set early.

Meanwhile, spending in eDiscovery has been moving toward the stage where missing sources tend to surface.

Collection, 2012 8%
Collection, 2024 16%
Review, 2012 73%
Review, 2024 64%
Where eDiscovery task spending goes. Share of total eDiscovery task spending on collection and review, 2012 and 2024, from ComplexDiscovery figures published on JD Supra in June 2025.

Pressure from the data side is growing too. In a 2024 survey of 30 litigation support directors by Ari Kaplan Advisors, sponsored by a litigation software company, 93% said the volume of data they manage for an average dispute is increasing. One director said the sources and types of data were more worrying than the volume. The ComplexDiscovery report credits collaboration tools such as Slack, mobile content and ephemeral messaging apps with pushing discovery beyond email and documents.

Seen side by side, the evidence describes a gap that moves rather than closes. The forgotten source keeps changing, and it is usually whatever arrived most recently. A checklist written for one year's tools ages along with them. We cannot say how often clients leave a source out, because nobody has counted. We can say which kind of source to suspect first.

The stakes become concrete after something is lost. Federal Rule 37(e) asks whether a party "failed to take reasonable steps to preserve it," as the next section explains. In our view, an intake list that never asked about the client's newest tools is a weak record to bring to that question. We build software that reads collections, so we have a stake in pushing that first look earlier.

Four questions for your next intake

  • Ask each custodian what they started using since the last matter that IT did not set up: an app, a personal account, or a workspace a vendor or partner created.
  • Ask whether anyone used a public AI tool for work connected to the matter, and where the prompts are kept. Kubicki recommends documenting this in the intake or engagement letter.
  • Date your questionnaire and review it before each new matter. The 2002 list did not mention cloud storage, and the 2014 list did not mention AI prompts.
  • Ask whoever handles your collection how soon you will see the collected data, and what in it would signal a source nobody mentioned, such as documents forwarded from a personal address.

How we checked this

We drew on a 2026 survey and practice guide published by an eDiscovery software company, a 2024 survey sponsored by a litigation software company, ComplexDiscovery spending figures republished by an eDiscovery services provider, a 2002 bar journal article, a 2014 podcast, a 2025 bar news report, a 2026 essay on AI governance, and the text of Federal Rule 37. None of the figures here are ours. Both surveys are small, with 101 and 30 respondents. The lists in our table were written for different purposes, including intake, legal holds and privilege. They show what experts flagged at the time. They do not measure what clients actually left out. We sell AI eDiscovery software, and the survey publishers sell legal technology, so all of us have a stake. Still unknown: how often a client's list is incomplete, and whether a structured inventory lowers that rate.

  1. EDRM, tips on working with clients to collect eDiscovery data, September 2, 2026, first published July 30, 2026.
  2. Stephen M. Cohen, Florida Bar Journal, article on electronic data and discovery, February 2002.
  3. The ESI Report, Legal Talk Network, episode on data preservation and legal holds, November 24, 2014.
  4. Jim Ash, Florida Bar News, report on hidden risks in AI-generated legal drafts, September 5, 2025.
  5. Tyson Martin, essay on decisions to lock before approving AI tools, March 29, 2026.
  6. JD Supra, 2025 eDiscovery review update with ComplexDiscovery figures, June 25, 2025.
  7. JD Supra, weekly eDiscovery roundup on the litigation support directors survey, December 12, 2024.
  8. Legal Information Institute, Federal Rule of Civil Procedure 37, retrieved October 21, 2026.

When does a forgotten data source become a spoliation argument?

A forgotten source becomes a spoliation argument once the duty to preserve has attached and the data is lost. A documented chain of custody then shapes how that argument unfolds.

Spoliation, in plain terms, is the loss or alteration of evidence a party had a duty to keep. The duty does not wait for the client's memory to catch up.

One e-discovery provider's consultant, speaking on a 2014 podcast, traced that duty to both the Federal Rules of Civil Procedure and the common law, and made a point that has aged well: once data is destroyed, it may be lost to both parties. Preservation offers no second attempt.

The same speaker described the rules amendments approved in September 2014, which reserved the most extreme sanctions for willful misconduct and intent to deprive the other side of evidence. That narrowing was real. Contrary to a hopeful reading of it, an honest omission is not a free one. A party that fails to preserve may still have to recreate data from backups or other sources, slowly and at considerable expense, while questions gather quietly about counsel's effectiveness and the client's credibility.

Courts have long asked for more than good faith. In Gates Rubber Co. v. Bando Chemical Industries, a 1996 federal decision, the court held that a party has "a duty to utilize the method which would yield the most complete and accurate results." Illinois went further, as Stephen Cohen noted in the Florida Bar Journal, by requiring counsel to review the client's computers and attach an affidavit that disclosure is complete.

Completeness is the standard. Memory is not a method.

The American Bar Association puts the human side plainly: "a lawyer cannot do their job if a client hasn't shared important details." Its guidance on client communication pictures a familiar moment, in which "the client swears they told you over the phone a few weeks ago" and the lawyer is sure they did not. Its remedy is the record, so that when something is overlooked, counsel can show "it wasn't your negligence that caused it."

The difference between a weak record and a strong one is easy to see side by side:

  • Before: "Client confirmed all relevant data is in company email."
  • After: "Client interviewed; asked about personal accounts, vendor workspaces, phones and departed users; client identified a personal cloud folder; hold extended to that folder the same day."

The second note does not prove the inventory was perfect. It proves the questions were asked, which is what a court will want to see when a source surfaces late.

That record is what Relevant e-Discovery is built to keep: immutable originals with content hashing, append-only audit trails and a documented chain of custody, so the process holds up if opposing counsel challenges it. Late-found sources also tend to sit in places automated tools pass over, which is why the gaps in one-click cloud collection deserve a careful look before anyone calls a collection complete.

None of this requires an enterprise budget. It requires asking in a particular order, and writing the answers down.

How can a small firm run a source inventory it can afford?

Pair a short questionnaire with custodian interviews, then test the inventory against the real collection early, where a missing source reveals itself before opposing counsel finds it.

A source inventory, here, means a written list of every system, account and device that may hold relevant data, built from questions rather than from the client's first answer. Three steps carry most of the weight:

  1. Send a pre-collection questionnaire covering email, file servers, cloud storage, mobile devices, messaging apps and any third-party platforms the matter touched.
  2. Follow it with custodian interviews that probe for systems or habits the questionnaire did not anticipate.
  3. Load what was collected for early assessment and read it for references to places that never made the list.

The first two steps come from one collection vendor's published guidance, which calls the questionnaire "a starting point, not the finish line" and argues that the pairing leaves a documented record of reasonable, systematic effort. I would add the third, because documents are candid about their surroundings in a way custodians rarely are. A thread that ends with a promise to continue in another app has just named a source.

The money is already moving in this direction. ComplexDiscovery's figures, published in 2025, show collection rising from 8% of eDiscovery task spending in 2012 to 16% in 2024, while review fell from about 73% to 64% and was projected to reach 52% by 2029. The same analysis noted that Slack, Microsoft Teams, mobile content and ephemeral messaging apps had pushed review well beyond email and documents.

An affordable tool still has to keep the defensible record, which is why Relevant pairs Bates numbering, privilege and chain of custody with cited answers and chronologies in one place. That record should begin at intake.

Conventional wisdom holds that careful early assessment belongs to large matters with large budgets. The 2025 ComplexDiscovery analysis argued the opposite, observing that generative AI could bring savings and scale especially to small and mid-sized matters where full technology-assisted review had been cost-prohibitive. A larger collection is also not automatically a slower one, a point worth reading in whether a bigger document set always means a longer review.

On cost, Relevant e-Discovery's position is that the economics should be visible on the firm's own matter: AI-assisted review runs cents per document, against the dollars per document and roughly $19K per gigabyte of manual review, and the proof it offers is a demonstration in which the buyer brings a messy collection and a hard question, then watches the platform read, code and cite their own evidence.

That is where the third step stops being theory. A forgotten workspace, a personal account or a departed user's mailbox tends to surface as a reference inside documents already in hand, provided someone reads them early enough to act.

What no platform can do is make a client remember. That part still happens across a table, one considered question at a time.

Could your next intake miss a source?

Relevant e-Discovery links every answer back to the exact exhibit it came from, so a late-found source can be checked in one click before anything is filed.

Processing runs single-tenant or inside your own AWS account, with no vendor retention and no model training. Speed and control rarely travel together. Here the trade is made in favor of control.

Bring the collection you already have.

Book an Early Case Assessment

What should change at your next client intake?

Plan for a second conversation. A single intake meeting captures what the client remembers that day, and the sources it misses are the ones most likely to surface later.

Professions that live by intake already assume this. In a 2026 discussion among practicing therapists, one clinician noted that about a third of the time the treatment plan takes 2 sessions, though it usually rests on data gathered in the first. The second meeting does not replace the first. It completes it.

The record matters as much as the meeting. I would have the client read the written inventory after that second conversation and confirm it, so the file shows what was asked, what was answered and when.

I would book the follow-up before the first meeting ends, and put the home computer and the personal phone on its agenda by name. A forgotten source found in the second week is an inventory note. Found later, the question becomes whether counsel's steps were reasonable, and the dated note is the answer.

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Frequently Asked Questions

What else do litigators ask about forgotten data sources?

Most questions come back to three things: what an inventory is, what technology can and cannot catch, and what an early look at the data costs.

What is a data source inventory?

A data source inventory is a written list of every place a client's relevant information may live, with the custodian and system for each. It is built at intake. It is tested against the collection itself, not against memory.

Will an AI review tool find a source the client never mentioned?

No. Review technology reads what has been collected, and a source nobody named never reaches it. The tools are also newer to many firms than people assume: in EDRM's Winter 2025 pricing survey, nearly one-third of respondents reported no familiarity with or use of GenAI-assisted review.

What does AI-assisted review cost compared with attorney review?

In that 2025 survey, GenAI-assisted review was most often priced at $0.26 to $0.50 per document, while remote per-document attorney review split between $0.50 to $1.00 and above $1.00. Relevant e-Discovery's own economics run at cents per document, a difference you can see on your own matter.

Should intake ask about the AI tools a client used?

I would ask by name. Corporate IT leaders describe allowing only officially approved AI tools, so anything else a client used sits outside sanctioned systems, and outside their recollection of where work happened.

How do I book an Early Case Assessment?

Through the contact page at relevantediscovery.com/contact-us. Bring the client's source list as it stands today, gaps included.

Written by

Michael

Kansky

Michael Kansky is a serial software entrepreneur who has spent more than two decades building and bootstrapping profitable SaaS and services companies.

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