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Editor’s Note: The composition of where eDiscovery dollars are spent across collection, processing, and review is shifting more meaningfully than the aggregate market line suggests. Reconciled estimates place review’s share of total task spend at 62 percent in 2025, declining to 52 percent by 2030. Over the same period, collection’s share rises from 17 percent to 25 percent, marking a redistribution of value creation within the eDiscovery workflow that is not immediately visible in topline growth figures.

This shift is driven by sharply divergent growth dynamics across segments. Collection expands at a compound annual rate approaching 16 percent through 2030—roughly four times the growth rate of review. The disparity reflects a tension long signaled in the market data: AI-assisted review continues to compress per-document review costs faster than data growth can offset them, while collection remains structurally exposed to expanding data volumes that AI has not yet materially reduced or eliminated.

For cybersecurity, data privacy, regulatory compliance, and eDiscovery professionals, three observations follow. First, vendor selection criteria continue to shift away from review labor capacity and toward forensic depth and modern collection capabilities. Second, pricing pressure in managed review not only persists but accelerates as AI-assisted review becomes the default rather than an optional enhancement. Third, the discoverable surface area continues to expand into domains—such as AI prompt logs, ephemeral messaging, and structured operational systems—where automation has not yet caught up with the work.

Industry Research – eDiscovery Market Sizing Beat

Market Intelligence: The eDiscovery task composition shift from 2025 to 2030

Review still leads in absolute spend, but collection grows fastest – climbing from $3.33 billion in 2025 to $7.02 billion in 2030 at roughly 16 percent CAGR – reshaping how worldwide eDiscovery dollars get resourced

ComplexDiscovery Staff

The worldwide eDiscovery market spent approximately $19.61 billion across the three core tasks of collection, processing, and review in 2025. Six in every ten of those dollars went to review. By 2030, the reconciled view places review’s share at five in every ten – even as absolute review spending continues to rise. Collection’s share over the same five years climbs from 17 percent to 25 percent. The composition shift inside the market reveals a story the aggregate growth line does not: AI is compressing per-document review costs faster than data growth offsets them, while collection – exposed to data-volume expansion but largely insulated from AI-driven cost compression – pulls dollars toward itself at premium rates.

The 2025 task-share baseline

In 2025, the reconciled view places worldwide review spending at approximately $12.16 billion, processing at approximately $4.12 billion, and collection at approximately $3.33 billion. Review accounts for 62 percent of total task spend, processing for 21 percent, and collection for 17 percent. The dollar-share lines establish the starting point for a five-year period in which all three task categories grow in absolute terms but at substantially different rates – and in which the composition of where work actually gets resourced shifts more meaningfully than the aggregate $19.61 billion to $28.08 billion trajectory suggests on its own.

Chart: eDiscovery Market by Task (2025-2030)

eDiscovery Market By Task (2025-2030)

Where the growth is concentrating: collection

Of the three task categories, collection grows fastest by a wide margin. Reconciled estimates project collection spending to climb from $3.33 billion in 2025 to approximately $7.02 billion in 2030 – a compound annual growth rate near 16 percent. Processing grows at approximately 9 percent CAGR, reaching $6.46 billion. Review grows at approximately 4 percent CAGR, reaching $14.60 billion. Collection’s CAGR runs roughly four times the review CAGR. The widening gap reflects two structural forces operating in opposite directions on the same underlying data growth: AI-assisted review continues to compress per-document review labor at scale, while data sources subject to potential collection – cloud collaboration platforms, mobile devices, ephemeral messaging, IoT and connected devices, structured operational systems, and now generative AI prompt and output logs – have proliferated faster than collection automation can absorb.

Review: still the largest task, still losing share

Review remains the single largest task category by absolute spend throughout the period, but its share of total task spend continues to decline. Reconciled 2030 review spending of $14.60 billion represents a 20 percent increase over 2025, but it accounts for only 52 percent of total task spend in 2030 versus 62 percent in 2025. AI-assisted review is the central mechanism: predictive coding (the prior decade’s automation default), generative-AI-assisted review (the current decade’s emerging default), and early agentic workflow features are reducing per-document review hours faster than data growth can offset on the spend side. The result is a structural pattern that has been visible since the RAND Corporation’s 2012 baseline study, Where the Money Goes, when review took 73 percent of total task spend – a pattern that absolute review dollars continue to rise even as review’s relative share recedes.

Collection: where the data-volume gap shows up

If review is the task most exposed to AI cost compression, collection is the task most exposed to data-volume expansion. The data sources subject to potential collection have proliferated across the past decade – cloud collaboration platforms (Slack, Teams, Google Workspace), mobile and ephemeral messaging, IoT and connected devices, structured operational systems, and an emerging category of generative AI prompt logs and model outputs that are themselves subject to discovery. Each new data source expands the collection scope; each presents specialized forensic, technical, and legal challenges that have so far resisted commoditization. The 16 percent CAGR for collection reflects this. Specialized expertise around forensic collection, modern data sources, cross-border data transfer, and AI-related artifact preservation commands premium rates that the underlying data-volume surge has so far protected from compression. The same AI capability that compresses review labor has not yet meaningfully reduced the human and technical effort required to identify, preserve, and collect from new data sources.

Processing: the steady middle

Processing sits in the middle of the task-share evolution. Reconciled estimates project processing spending to grow from $4.12 billion in 2025 to $6.46 billion in 2030 at a 9 percent CAGR – faster than review, slower than collection. Processing’s share of total task spend rises modestly, from 21 percent in 2025 to 23 percent in 2030. The category benefits from data-volume growth (more data to process) but also faces partial AI cost compression as automated processing pipelines, AI-driven analytics, and modernized infrastructure handle higher data volumes per unit of human attention. Processing’s growth pattern reflects this dual exposure: rising in absolute terms, gaining modest share, but neither leading the task composition shift the way collection does nor trailing it the way review does.

What the 2025-2030 task composition implies

The forward five years suggest a gradual rebalancing in how eDiscovery work gets resourced. Vendors and providers anchored primarily to review labor face continued pricing pressure and a slowly declining share of total task spend – a structural reality that supports the qualitative shift inside services from traditional managed review toward higher-value advisory and specialized response work. Vendors and providers with strong forensic and modern-collection capabilities are positioned to capture the fastest-growing absolute spend in the market. Processing-centric capability remains durable but does not lead. For buyers, vendor selection criteria continue to shift – from review labor capacity toward technical breadth in collection, processing throughput, and AI workflow integration.

Chart: Relative Task Expenditures for Core eDiscovery Tasks

Relative Task Expenditures for Core eDiscovery Tasks

What comes next in the Market Intelligence series

Subsequent Market Intelligence analyses in the 2025-2030 cycle will examine the segmentation views that surround the task composition: software deployment (on-premise versus off-premise), cloud composition (SaaS, PaaS, IaaS), geography (United States versus rest of world), demand sector (government and regulatory versus non-government), direct delivery approach, and the long-horizon task-share view extending back to the 2012 baseline. The aggregate market and software-versus-services pieces from earlier in the series provide the headline context against which each segment-level analysis can be read.

The figures presented here are reconciled estimates aligned to a common scope (worldwide eDiscovery, software, and services), a common geography, and a common timeframe (calendar years 2025 through 2030). They draw on publicly available third-party research, vendor disclosures, and analyst evaluation aggregated within the underlying market model. Forward estimates from past and present industry data sources are included in the model and presented as the current reconciled view. The 2025-2030 eDiscovery Marketplace Mashup is complete in its underlying analysis but remains unpublished in its consolidated form at this time. It will be published as the culmination of the Market Intelligence series, with the full source list, citation guidance, and methodology disclosure included at that time.

For practitioners reading the task-composition shift for the first time, the question is not whether review remains the dominant single task – it does, and will through 2030 – but whether the steady drift of share toward collection will outpace the AI-driven cost compression that has so far protected review’s absolute trajectory. Will the next decade of eDiscovery be a collection-heavy market with an AI-automated review tail, or will AI-assisted collection eventually compress collection labor the way it now compresses review?

About the eDiscovery Market Size Mashup from ComplexDiscovery OÜ

The eDiscovery Market Size Mashup from ComplexDiscovery OÜ is an annual analytical report that provides a comprehensive overview of eDiscovery market trends, task-based expenditures, and technological advancements. Drawing on data from historical studies, market modeling, and future forecasting, the Mashup offers actionable insights for legal, business, and technology professionals. By examining key factors such as data growth, task allocation, and the impact of emerging technologies like generative AI, the Mashup serves as a citable resource for understanding the evolving dynamics of eDiscovery. The 2025-2030 edition of the report is complete in its underlying analysis and will be published in its consolidated form as the culmination of the Market Intelligence series.

News sources

The following list is a directional resource set rather than an exact bibliography. It identifies representative inputs that shape this analysis; the core source listing, which provides a general understanding of data point sources over the lifecycle of the model, will be published with the consolidated 2025-2030 eDiscovery Market Size Mashup at the culmination of the Market Intelligence series.

Assisted by GAI and LLM Technologies

Additional reading

Source: ComplexDiscovery OÜ

ComplexDiscovery’s mission is to enable clarity for complex decisions by providing independent, data‑driven reporting, research, and commentary that make digital risk, legal technology, and regulatory change more legible for practitioners, policymakers, and business leaders.

The post Market Intelligence: The eDiscovery task composition shift from 2025 to 2030 appeared first on ComplexDiscovery.

Photo of Alan N. Sutin Alan N. Sutin

Alan N. Sutin is Chair of the firm’s Technology, Media & Telecommunications Practice and Senior Chair of the Global Intellectual Property & Technology Practice. An experienced business lawyer with a principal focus on commercial transactions with intellectual property and technology issues and privacy

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Alan N. Sutin is Chair of the firm’s Technology, Media & Telecommunications Practice and Senior Chair of the Global Intellectual Property & Technology Practice. An experienced business lawyer with a principal focus on commercial transactions with intellectual property and technology issues and privacy and cybersecurity matters, he advises clients in connection with transactions involving the development, acquisition, disposition and commercial exploitation of intellectual property with an emphasis on technology-related products and services, and counsels companies on a wide range of issues relating to privacy and cybersecurity. Alan holds the CIPP/US certification from the International Association of Privacy Professionals.

Alan also represents a wide variety of companies in connection with IT and business process outsourcing arrangements, strategic alliance agreements, commercial joint ventures and licensing matters. He has particular experience in Internet and electronic commerce issues and has been involved in many of the major policy issues surrounding the commercial development of the Internet. Alan has advised foreign governments and multinational corporations in connection with these issues and is a frequent speaker at major industry conferences and events around the world.

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