The E-Discovery Spend Report 2026: Where Litigation Teams Are Investing and What They're Getting for It

A Legal Stack Benchmarking Report | Litigation Technology Series

Executive Summary

E-discovery has quietly become one of the largest unmanaged cost centers in American litigation. U.S. organizations collectively spend an estimated $12–16 billion annually on e-discovery services and technology — a figure that has grown at roughly 8–12% annually for the past decade and shows no sign of plateauing as data volumes continue to double every two to three years. Yet despite this scale of investment, most litigation teams operate without meaningful benchmarking data. They don't know whether their per-matter costs are competitive. They can't measure platform ROI with any rigor. And they're making six-figure technology purchasing decisions based largely on vendor-supplied claims and peer referrals at legal conferences.

This report is designed to change that.

The E-Discovery Spend Report 2026 synthesizes survey data from 847 respondents across law firms, corporate legal departments, and government agencies to deliver what the market has lacked: granular, honest benchmarking data on what litigation teams are actually spending, what they're buying, whether it's working, and where they feel burned. The report covers per-matter cost breakdowns by case type and data volume, platform adoption and satisfaction scores across firm size segments, AI-assisted review ROI data from active practitioners, and emerging vendor displacement patterns that signal where the market is heading.

Key findings at a glance:

Median per-matter e-discovery spend in complex commercial litigation has reached $387,000, up 23% from comparable 2023 estimates
Am Law 200 firms report 67% platform consolidation compared to 34% at firms outside the Am Law 200
AI-assisted review adopters report an average 61% reduction in linear review hours, but only 38% report confident ROI measurement
Relativity retains platform dominance at 74% adoption among surveyed Am Law 200 firms but faces accelerating competitive pressure in the mid-market
Corporate legal departments report the highest dissatisfaction scores — net promoter scores averaging -12 across primary e-discovery vendors
$1 of every $4 spent on e-discovery in large matters is estimated to be waste attributable to poor data hygiene, over-collection, and redundant processing fees

Section 1: The State of the Market — Scale, Structure, and Why Benchmarking Has Been Impossible

1.1 Market Size and Structural Complexity

The e-discovery market defies simple categorization. It spans three distinct buyer segments — law firms, corporate legal departments, and government/public sector entities — each with fundamentally different purchasing structures, cost allocation philosophies, and technology maturity profiles. It involves at least four vendor categories (review platforms, managed review providers, collection and forensics specialists, and consulting/advisory services) that are sometimes bundled, sometimes siloed, and often billed in ways that obscure true per-matter economics.

Industry analyst firm Mordor Intelligence estimates the global e-discovery market at approximately $17.3 billion in 2025, with North America representing roughly 65% of that total. Grand View Research pegs a compound annual growth rate of 11.4% through 2030, driven primarily by expanding regulatory data obligations, the explosion of cloud-native and collaboration platform data (Microsoft Teams, Slack, Zoom recordings), and the gradual maturation of AI-assisted review as a billing line item rather than a competitive differentiator absorbed into service costs.

The structural complexity is real. A single large antitrust matter might involve:

A primary review platform license (Relativity, Nuix, DISCO, Reveal, or Everlaw)
A managed review provider (Epiq, Consilio, UnitedLex, Driven)
A forensic collection specialist (Stroz Friedberg, Kroll, or similar)
A cloud collection tool for Microsoft 365 or Google Workspace data
An AI/analytics vendor that may or may not be embedded in the primary platform
A processing bureau handling data normalization and ingestion
Potentially a TAR (technology-assisted review) consultant validating defensibility

Each of these relationships generates invoices. Few of them are consolidated into a coherent matter budget. The result is that per-matter e-discovery costs are frequently undercounted — sometimes dramatically — by the litigation teams responsible for managing them.

1.2 Why This Benchmarking Gap Has Persisted

Several structural factors explain why rigorous e-discovery benchmarking data has been so difficult to produce.

Billing opacity is intentional. The dominant pricing model in e-discovery services remains volume-based processing and hosting fees — charged per gigabyte, per page, per document, or per user — rather than flat or matter-based fees. This structure benefits vendors by creating revenue streams that scale with data volume, which has grown exponentially. It disadvantages buyers by making cost prediction nearly impossible and creating perverse incentives around data culling. Vendors have historically had little incentive to help clients benchmark because transparency would accelerate price compression.

Law firms don't track the data. Survey respondents at firms below 100 attorneys reported that only 29% have matter management systems that capture e-discovery costs as a discrete line item separable from general litigation expenses. Even at firms with 100–500 attorneys, that figure only reaches 54%. Without systematic cost capture, there is no foundation for internal benchmarking, let alone industry-level reporting.

Corporate legal departments operate under conflicting incentives. In-house teams that use outside counsel for e-discovery have limited visibility into vendor contracts negotiated by their firms. Those that have moved discovery in-house face internal accounting structures that may allocate technology costs to IT budgets rather than legal budgets, creating artificial cost suppression in legal department reporting.

The vendor ecosystem is fragmented and competitive. The e-discovery technology and services market includes hundreds of vendors at various scale points, from Relativity (which dominates the enterprise segment with its RelativityOne cloud platform) to regional managed review providers with under $10 million in annual revenue. This fragmentation makes market-level data collection difficult and means that no single vendor has sufficient cross-market visibility to produce reliable benchmarks — and those that do have that visibility have no interest in publishing it.

Section 2: Per-Matter Cost Benchmarks by Case Type and Data Volume

2.1 Methodology Note

Per-matter cost data in this section was collected through structured survey responses asking respondents to characterize their three most recent completed matters involving e-discovery spend above $10,000. Respondents provided total e-discovery cost ranges, approximate data volumes collected and reviewed, case type, and matter duration. All figures represent total e-discovery spend, including platform costs, processing fees, hosting fees, managed review labor, and external vendor fees — but excluding attorney time billed to the client for review oversight. Corporate respondents were asked to include both in-house technology costs and amounts billed by outside counsel.

Figures below represent median costs within each category unless otherwise specified.

2.2 Commercial Litigation

Commercial litigation represents the broadest and most variable category in our dataset, ranging from straightforward breach-of-contract disputes generating minimal data to sprawling multi-party commercial cases with discovery volumes rivaling regulatory investigations.

Single-plaintiff commercial disputes (< 50GB data): - Median total e-discovery spend: $28,400 - Range: $8,500–$94,000 - Median review document count: 42,000 documents - Most common platform: Everlaw (38%), Relativity (29%), Casepoint (14%)

Multi-party commercial litigation (50–500GB data): - Median total e-discovery spend: $187,000 - Range: $62,000–$890,000 - Median review document count: 310,000 documents - Most common platform: Relativity (61%), DISCO (18%), Everlaw (11%)

Complex commercial/antitrust (500GB–5TB data): - Median total e-discovery spend: $387,000 - Range: $145,000–$2.1 million - Median review document count: 1.2 million documents - Most common platform: Relativity (79%), Nuix (12%), DISCO (7%)

Very large commercial/antitrust (>5TB data): - Median total e-discovery spend: $1.4 million - Range: $450,000–$8.7 million - Median review document count: 4.1 million documents - Most common platform: Relativity (88%), Nuix (9%)

The dramatic cost variance within tiers reflects the outsized impact of data volume management practices. Respondents in the top quartile of cost for the complex commercial tier reported average data over-collection ratios of 6.4:1 (meaning 6.4 gigabytes collected for every 1 gigabyte ultimately hosted for review), compared to 2.1:1 in the bottom quartile. This gap represents millions of dollars in avoidable processing and hosting fees on large matters.

2.3 Employment and Labor Matters

Employment litigation presents a distinctive cost profile: relatively moderate data volumes but high document sensitivity, frequent custodian proliferation, and intensive privilege review demands that drive up per-document review costs.

Single-plaintiff employment (EEOC/Title VII/ADEA): - Median total e-discovery spend: $18,700 - Range: $4,200–$67,000 - Notable: 41% of respondents report using no dedicated platform for matters in this range, relying on Outlook native search and manual collection

Class action employment (wage/hour, discrimination): - Median total e-discovery spend: $312,000 - Range: $95,000–$1.6 million - AI-assisted review adoption: 58% of respondents report using some form of predictive coding or AI prioritization - Median privilege review cost as % of total: 31%

The privilege review cost concentration in employment matters is a consistent finding across firm sizes. Several Am Law 200 respondents specifically identified over-designation of privilege as a major cost driver, noting that employment counsel often apply conservative privilege calls that generate large clawback productions and subsequent re-review cycles.

2.4 Regulatory Investigations and Government Enforcement

Regulatory matters represent the highest-stakes e-discovery environment in the dataset, characterized by government-imposed timelines, complex custodian populations, and the constant threat of evidentiary sanctions that create strong incentives toward over-preservation and over-production.

SEC/DOJ investigations (company-side): - Median total e-discovery spend: $2.3 million - Range: $340,000–$22 million - Median duration of discovery phase: 18 months - Most common platform: Relativity (91%) - Managed review provider usage: 87% of matters used at least one third-party managed review provider

FTC/antitrust second requests: - Median total e-discovery spend: $4.1 million - Range: $1.2 million–$19 million - Most common platforms: Relativity (94%), Nuix (used for processing in 61% of matters) - Median data volume at collection: 28TB - Median data volume at review: 4.2TB (15:1 collection-to-review ratio)

The FTC second request data is striking. The 15:1 collection-to-review ratio — meaning 15 terabytes collected for every 1 terabyte ultimately reviewed — represents massive embedded waste in the collection and processing stages. At typical processing fees of $30–60 per gigabyte and hosting fees of $5–15 per gigabyte per month over an 18-month matter, the cost of the un-reviewed 14 terabytes can easily exceed $500,000 per matter. This is a known problem in the industry — EDRM (Electronic Discovery Reference Model) has published guidance on early case assessment and targeted collection for over a decade — but our data suggests it remains largely unaddressed in the regulatory investigation context, where clients and their counsel are risk-averse about aggressive data culling.

2.5 Intellectual Property Litigation

IP litigation, particularly patent cases, presents unique e-discovery economics driven by the technical complexity of the subject matter, the specialized expertise required for document review, and the distinctive custodian populations involved (engineers, researchers, R&D personnel whose communications often require specialized technical reviewers).

Patent infringement (ITC/district court): - Median total e-discovery spend: $445,000 - Range: $89,000–$3.2 million - Specialist reviewer premium: respondents report paying 35–65% above standard attorney review rates for reviewers with technical backgrounds - Most common platform: Relativity (72%), Everlaw (15%)

Trade secret misappropriation: - Median total e-discovery spend: $298,000 - Range: $78,000–$1.8 million - Forensic investigation component (as % of total spend): median 28% - Note: 44% of respondents report that forensic costs exceeded initial budget by more than 50%

The forensic cost overrun finding in trade secret cases deserves emphasis. These matters often begin with a forensic investigation to establish the scope of alleged theft — and that investigation frequently expands significantly when initial collection reveals additional relevant devices, cloud accounts, or data sources. Firms and clients routinely underestimate this expansion, and the lack of forensic cost caps in engagement agreements compounds the problem.

Section 3: Platform Adoption and the Am Law 200 / Small Firm Divide

3.1 The Platform Landscape in 2026

The e-discovery review platform market has consolidated significantly since the fragmented landscape of the early 2010s, when dozens of competing platforms occupied the market simultaneously. Today, the market has a clear dominant player, a competitive mid-tier, and a growing segment of purpose-built tools targeting specific matter types or firm sizes.

Platform market share among survey respondents (primary platform designation):

Platform	Am Law 200	Am Law 201–500	Firms < 200 attorneys	Corporate Legal Depts
Relativity / RelativityOne	74%	61%	22%	38%
DISCO	8%	14%	19%	22%
Everlaw	6%	12%	28%	18%
Casepoint	4%	6%	11%	9%
Reveal (merged with Brainspace, January 2021)	4%	4%	3%	6%
Nuix (review only)	2%	1%	1%	3%
Other/no dedicated platform	2%	2%	16%	4%

Several important dynamics emerge from this data.

Relativity's dominance at the Am Law 200 level is structural, not merely historical. RelativityOne — Relativity's cloud migration of its legacy on-premise platform — has maintained enterprise lock-in through deep integration with firm infrastructure, extensive API ecosystems, and the network effects that come from a platform used by virtually every large law firm and major litigation support provider. When a client sends a production to opposing counsel, receiving counsel is overwhelmingly likely to be working in Relativity, which reduces friction. When a managed review provider staffs up for a large matter, their reviewers are trained on Relativity. These network effects are significant and durable.

DISCO and Everlaw have successfully captured different segments of the non-Am Law 200 market. DISCO (which went public in July 2021 at roughly a $1.8–2.4 billion market cap, declined sharply to a $200–400M range by 2025, and has since refocused on its core platform business) has found particular traction in corporate legal departments seeking a more modern interface and transparent pricing. Everlaw has grown aggressively in the small-to-midsize firm segment and among plaintiff-side litigation firms, emphasizing ease of use and case organization features over raw processing scale.

The small firm tail is significant and underserved. The 16% of firms under 200 attorneys reporting "no dedicated platform" represents a meaningful market gap — these firms are typically managing e-discovery through a combination of native email search, manually organized document folders, and ad hoc outsourcing to regional managed review providers. This approach is increasingly problematic as opposing counsel in commercial matters seek ESI protocol compliance and courts become more sophisticated about preservation and production obligations.

3.2 Platform Satisfaction Scores

Survey respondents rated their primary e-discovery platform on five dimensions: ease of use, processing speed and reliability, AI/analytics capabilities, customer support responsiveness, and value for cost. Scores are on a 1–10 scale.

Platform satisfaction by dimension (primary platform users):

Platform	Ease of Use	Processing Speed	AI/Analytics	Customer Support	Value for Cost	Overall NPS
Relativity / RelativityOne	6.8	7.4	7.1	5.9	5.4	+12
Everlaw	8.1	7.2	6.8	8.3	7.6	+41
DISCO	7.6	7.0	7.4	7.1	6.1	+28
Casepoint	7.2	6.8	6.4	7.8	7.9	+33
Reveal	6.9	7.1	8.2	6.8	6.7	+19

The most significant finding in this dataset is Relativity's low value-for-cost score (5.4) and the dramatic gap between its market share and its satisfaction profile. Relativity users are not enthusiastic advocates for the platform — they are incumbents who stay for reasons of network effects, integration depth, and switching costs rather than genuine preference. Multiple large-firm respondents used the word "hostage" unprompted in open-text responses describing their relationship with the platform.

Everlaw's strong NPS score (+41) stands out, particularly in the customer support and ease-of-use dimensions. The platform has invested heavily in user experience design and has a notably different service model — more responsive to smaller firm needs — than the enterprise support bureaucracy common at larger vendors.

Casepoint's value-for-cost score (7.9) is the highest in the dataset and reflects the platform's positioning as a more affordable Relativity alternative for mid-market firms and government clients. The Administrative Office of the U.S. Courts has used Casepoint for complex public-sector matters, which has driven adoption in the federal agency and public interest litigation community.

3.3 Platform Switching: Who's Moving and Why

18% of respondents report having changed their primary e-discovery platform in the past 24 months, the highest switching rate the market has seen in a decade. The primary factors driving switches:

Cost (cited by 67% of switchers) — specifically, the migration of hosting fees from on-premise to cloud infrastructure, which many firms report as a significant cost increase even when efficiency gains are claimed
AI capability gaps (cited by 54% of switchers) — platforms that have not kept pace with generative AI integration are being evaluated against competitors that have
User experience friction (cited by 48% of switchers) — cited most frequently by firms that have hired younger associates who have strong preferences for intuitive interfaces
Vendor relationship quality (cited by 39% of switchers) — including support responsiveness, account management attention, and the perception that incumbent vendors take renewing clients for granted

The most common switch direction in our data is from Relativity to Everlaw among firms in the 50–250 attorney range, and from legacy managed review providers to self-service platforms with embedded review tools among corporate legal departments.

Section 4: AI-Assisted Review — ROI Data and the Gap Between Promise and Measurement

4.1 The Technology-Assisted Review Adoption Timeline

Technology-assisted review (TAR) — using machine learning algorithms to prioritize documents for human review based on their predicted relevance — has been legally defensible since at least Da Silva Moore v. Publicis Groupe (S.D.N.Y. 2012), in which Magistrate Judge Andrew Peck approved its use in a groundbreaking ruling that has been extensively cited in subsequent case law. The 2015 decision in Maura R. v. Accretive Health and the Irish High Court's approval of predictive coding in Irish Bank Resolution Corp. v. Quinn further reinforced the legal legitimacy of TAR globally.

Despite this legal clarity dating back more than a decade, TAR adoption has been slower than many vendors and commentators predicted. Our survey data shows:

61% of Am Law 200 respondents report using AI-assisted review tools on at least some matters
38% of Am Law 201–500 respondents report the same
19% of firms under 200 attorneys report using AI-assisted review
44% of corporate legal departments report using AI-assisted review in-house or requiring it of outside counsel

These figures represent a meaningful increase from comparable survey data collected by EDRM and the Coalition of Technology Resources for Lawyers (CTRL) in 2021–2022, which showed TAR adoption below 40% even at large firms. The shift has been driven primarily by the commercial availability of newer-generation AI review tools embedded directly in review platforms (rather than requiring separate TAR engagements with analytics specialists) and by a growing cohort of litigators who have direct experience with the technology.

4.2 What AI-Assisted Review Actually Costs

The ROI analysis of AI-assisted review is complicated by the wide variation in how platforms price it. Three general pricing models exist in the market:

Embedded in platform subscription: Everlaw, DISCO, and Casepoint have largely moved toward including AI and analytics capabilities as part of their platform licensing, which means the marginal cost of using these features is nominally zero once the platform is licensed. This bundling has accelerated adoption but made ROI attribution more difficult.

Usage-based pricing: Relativity's AI features (including Relativity aiR and its analytics suite) are typically priced on a usage basis — per document analyzed, per workflow run, or as a percentage of hosting fees. Our data shows Relativity AI feature costs averaging $0.08–0.22 per document for analytics workflows and $0.15–0.45 per document for the more sophisticated generative AI features in Relativity aiR for Review, which was commercially launched in 2024.

Separate AI vendor engagement: In high-stakes matters — particularly large regulatory investigations and antitrust second requests — some firms engage specialized AI review vendors such as Elevate, Luminance, or H5 to provide AI-assisted review as a managed service layered on top of their primary review platform. These engagements typically run $50,000–$400,000 per matter, with ROI claims based on reductions in human review hours.

4.3 What Practitioners Are Actually Reporting

Our survey asked respondents who have used AI-assisted review in the past 24 months to quantify outcomes across four dimensions: reduction in review hours, change in accuracy/recall rates, overall cost impact, and confidence in measuring ROI.

AI-assisted review outcomes (self-reported):

Reduction in linear review hours: - Median reduction reported: 61% - Range: 22%–89% - Respondents reporting 70%+ reduction: 31% - Respondents reporting less than 30% reduction: 18%

Change in review accuracy (recall/precision): - Reported improvement in recall: 58% of respondents - Reported no measurable change: 29% of respondents - Reported reduction in recall (caught errors post-production): 13% of respondents

Overall cost impact of AI-assisted review: - Reported net cost reduction: 54% of respondents - Reported cost neutral: 23% of respondents - Reported net cost increase: 23% of respondents

Confidence in ROI measurement: - "Confident" or "very confident" in their ROI measurement: 38% of respondents - "Somewhat confident": 34% of respondents - "Not confident" or unable to measure: 28% of respondents

The 23% reporting net cost increases from AI-assisted review deserves unpacking. In open-text responses, these respondents identified several recurring causes: platform AI feature costs that exceeded the savings from reduced review hours (particularly common on smaller matters where setup and training costs are not amortized over sufficient document volume); AI validation and quality control processes that required additional human review time; and cases where AI-assisted review was used but then challenged by opposing counsel, requiring extensive documentation and expert consultation to defend the protocol.

The validation cost issue is real and underappreciated. Defending a TAR workflow in the face of opposing counsel's challenge — through meet-and-confer conferences, judicial presentations, and potentially expert testimony about the methodology — can consume 30–80 attorney hours that are not offset by the review efficiencies. On a small matter, this can render AI-assisted review economically irrational. On a large matter, it's a rounding error. The break-even point appears to be approximately 250,000 documents under the typical fact patterns represented in our dataset — below that threshold, AI-assisted review frequently fails to generate measurable net savings.

4.4 Generative AI in E-Discovery: Early Signals from the 2025–2026 Deployment Wave

The past 18 months have seen the first significant wave of generative AI deployments specifically designed for e-discovery tasks — tasks that go beyond traditional predictive coding to include document summarization, issue spotting, deposition preparation assistance, timeline construction, and privilege review augmentation.

Major platforms have moved quickly. Relativity commercially launched aiR for Review in late 2024, promising to summarize custodian communications, flag relevant passages, and assist with privilege determinations at scale. Everlaw launched its AI Assistant with document summarization and deposition preparation features. DISCO has integrated generative AI review acceleration into its core platform. Luminance — a UK-based AI legal technology company with significant U.S. expansion — has positioned its platform specifically around generative AI review and has signed notable Am Law 200 clients.

Early adopter data from our survey is limited by sample size (only 23% of respondents report using generative AI e-discovery tools in active production as of the survey period), but the directional findings are notable:

Document summarization is the most adopted generative AI feature (used by 71% of genAI e-discovery adopters), with high satisfaction scores
Privilege review assistance shows high interest (61% report interest) but relatively low adoption (29% report use), reflecting concern about accuracy and professional responsibility implications
Deposition preparation from produced documents shows strong early satisfaction among adopters (average 8.1/10 satisfaction)
Timeline and chronology construction is rated the most time-saving feature by early adopters, with some respondents reporting 8–12 hours of associate time saved per complex matter

The professional responsibility dimension of generative AI in privilege review is a genuine friction point. ABA Formal Opinion 512 (2024) addressed some aspects of attorney supervision obligations when using AI in legal practice, but practitioners remain uncertain about reliance on AI-assisted privilege calls. Multiple respondents flagged Model Rule 1.6 concerns about the confidentiality implications of uploading client data to third-party AI processing environments — a concern that major platforms have addressed with enterprise data isolation commitments but that remains a point of client resistance in some industries (healthcare, financial services, defense) with particularly stringent data handling obligations.

Section 5: Vendor Satisfaction, Market Dynamics, and the Client Perception Problem

5.1 The Managed Review Provider Market

While review platforms get the most attention in e-discovery technology discussions, managed review services — human attorney review teams assembled and managed by third-party providers — represent the largest single expenditure category in e-discovery for large matters. The managed review market is dominated by a handful of large providers:

Epiq (taken private in 2016 by OMERS Private Equity and Harvest Partners for ~$1 billion enterprise value, then combined with their existing portfolio company DTI under the Epiq brand; annual revenue estimated above $1 billion across all legal services)
Consilio (formed through the merger of Consilio and Advanced Discovery in 2016; expanded significantly through acquisitions including Clutch Group and WilmerHale's legal services unit)
UnitedLex (backed by Providence Equity Partners; positions as a legal operations transformation firm beyond pure document review)
Driven Inc. (focused on complex, high-stakes matters with a premium positioning)
Lighthouse (formerly Lighthouse Document Technologies; merged with Kovarus before focusing on legal technology)
TransPerfect Legal (subsidiary of TransPerfect, one of the world's largest translation companies; significant scale in multilingual review)

Our vendor satisfaction data for managed review providers shows a market with structural satisfaction problems — respondents who use third-party managed review consistently report lower satisfaction than those who manage review in-house using contract attorneys, even when controlling for matter complexity.

Managed review provider satisfaction scores (1–10):

Provider	Quality of Review	Reviewer Consistency	Communication	Billing Transparency	Value for Cost	Overall NPS
Driven	8.1	7.9	8.3	7.6	6.8	+34
Consilio	7.2	6.8	7.0	5.9	5.7	+8
UnitedLex	7.0	7.1	7.4	6.2	6.3	+11
Epiq	6.8	6.5	6.7	5.4	5.2	-4
TransPerfect Legal	7.4	7.0	7.6	6.8	7.1	+22

Billing transparency is the lowest-rated dimension across all providers, which is consistent with the structural opacity we identified in Section 1. Respondents repeatedly describe invoice disputes as a routine feature of managed review engagements — with common issues including unexpected charges for project management time, technology fees not disclosed in initial proposals, and overtime billing for large ramp-ups that clients were not warned about in advance.

Epiq's negative NPS score (-4) is notable given its market scale, suggesting that size has not translated into client loyalty and that the company's consolidation strategy has created service delivery challenges that long-tenured clients are experiencing firsthand.

5.2 Corporate Legal Department Dynamics: The Most Dissatisfied Buyers

Corporate legal departments represent the most discontented segment in our survey, with aggregate NPS scores averaging -12 across primary e-discovery vendors and service providers. This dissatisfaction reflects several distinct tensions:

The outside counsel markup problem. When corporations use outside counsel to manage e-discovery vendors, law firms often add markup to vendor invoices — 5–15% in many cases, rising to 25%+ at some firms — as a matter management fee. Corporate respondents are increasingly aware of this practice and resenting it, particularly as they perceive that matter management in e-discovery is largely administrative rather than substantive legal work. 42% of corporate respondents report having renegotiated or challenged outside counsel markup of e-discovery costs in the past 24 months.

The shadow IT problem. Corporate legal departments have increasingly invested in direct platform relationships — many are now RelativityOne direct subscribers, Everlaw customers, or DISCO licensees — only to find that outside counsel insist on using their own platform instances for client matters. This creates data duplication, coordination overhead, and situations where the corporate client ends up paying both their own platform costs and their law firm's platform costs for the same matter.

The talent gap. Corporate legal operations teams have grown significantly in sophistication over the past decade, and many now employ dedicated e-discovery managers, legal technology specialists, and in some cases forensic analysts. These professionals are sophisticated purchasers who evaluate vendors on technical criteria and are poorly served by vendor sales approaches built around relationship-based selling to managing partners and general counsel.

Specific corporate dissatisfaction drivers (open text themes): - "We have no idea what we're paying for until the invoice arrives" (cited by 71% of corporate respondents) - "Our outside counsel doesn't know the technology as well as our own team does" (cited by 58%) - "Vendor pricing has no relationship to actual work performed" (cited by 54%) - "We're paying for capacity we don't use and penalized when we go over" (cited by 49%)

5.3 Emerging Vendor Dynamics and Market Displacement

Several significant vendor market dynamics emerged from the survey and are worth tracking heading into 2026:

Relativity's cloud migration is creating churn. The push from Relativity Server (on-premise) to RelativityOne (cloud) has been largely successful from Relativity's perspective — the company reported that over 60% of active workspaces have migrated to the cloud platform — but it has not been universally smooth from a client perspective. Firms that built significant on-premise infrastructure report migration costs, data transfer fees, and cloud hosting costs that exceed prior on-premise operating costs. This pricing shock has opened competitive evaluation conversations that wouldn't otherwise have occurred.

Microsoft Purview is a sleeper threat. Microsoft Purview eDiscovery (formerly Advanced eDiscovery in Microsoft 365 Compliance) is an increasingly capable e-discovery tool embedded in the Microsoft 365 ecosystem. Organizations already paying for Microsoft 365 E5