For many legal teams, that question is becoming harder to ignore.

Over the last two decades, AI has transformed eDiscovery. Review is faster. Analytics are more powerful. Workflows are more automated. Yet despite these advancements, total discovery spend often remains unchanged, or in some cases, continues to rise.

This disconnect reflects a fundamental reality: AI technology applied too late cannot fix inefficiencies introduced too early.

The Cost Myth of AI-Driven eDiscovery

There is no question that AI has improved downstream discovery workflows. Document review, issue identification, clustering, prioritization, and quality control are more efficient and defensible than ever before.

But faster review does not automatically equate to lower total cost.

Why? Because AI is typically deployed after the most consequential (and expensive) decisions have already been made. These include:

    • Which custodians are included
    • Which data sources are collected
    • How broadly the ESI protocol is defined
    • Whether early culling decisions are strategic or overly conservative

Once scope expands, AI can help manage the volume, but it cannot undo it. At that point, even the most sophisticated AI technology is working on a dataset that is already too large.

The Real Leverage Point: The Left Side of the EDRM

The greatest opportunity for cost and risk reduction exists on the far left side of the EDRM, long before documents ever reach a review platform. This approach is firmly grounded in longstanding court decisions and industry guidance, which consistently emphasize that proportionality and reasonableness — not maximalism — should define discovery practices.1 2

Early-stage decisions have an outsized impact on everything that follows:

    • Identifying truly relevant custodians
    • Selecting the right data sources instead of defaulting to “collect it all”
    • Right-sizing collection scope before preservation and processing begins
    • Negotiating ESI protocols grounded in proportionality, not fear of missing something
    • Establishing defensible culling strategies from the outset

Each of these decisions carries significant downstream consequences. Every unnecessary gigabyte collected multiplies cost across processing, hosting, review, privilege analysis, and production. AI may reduce the marginal cost of reviewing data, but it cannot eliminate the cumulative cost of over-collection and maintenance of it.

Data Minimization: From Concept to Execution

Data minimization is no longer a theoretical best practice — it is a business imperative. Yet many organizations struggle to operationalize it in a way that is consistent, defensible, and scalable across matters.

Effective data minimization requires:

    • Clear, documented rationale for custodian and data source selection
    • Early insight into where relevant data is most likely to reside
    • Repeatable workflows that reduce reliance on ad hoc decision-making
    • Coordination between legal, IT, and discovery teams

Without this structure, teams default to over-collection — not because it is necessary, but because it feels safer. When data minimization becomes a disciplined and documented process, organizations gain control over both cost and risk.

Where Service Providers Make the Difference

This is where the role of a strategic eDiscovery partner becomes critical.

While many providers focus on optimizing review, fewer prioritize getting the scope right before data is ever collected. The most effective partners help clients:

    • Make informed, defensible early-stage decisions
    • Reduce unnecessary data volume before costs accrue
    • Document decision-making to withstand scrutiny
    • Align discovery strategy with legal and business objectives

By shifting focus upstream, legal teams can mitigate downstream problems that should never exist. Unless that changes, AI will continue to optimize an already inflated problem.

Rethinking What “Savings” Really Means

AI is essential to modern discovery, but it is not a silver bullet. Its value is maximized only when paired with smarter upstream decisions.
Organizations seeing meaningful cost and risk reduction are shifting from asking, “How fast can we review this data?” to “Why are we collecting it in the first place?”

Technology matters. But the shift from reactive review to proactive strategy is where real savings are realized.

Looking Ahead: A Smarter Approach to Discovery

Moving forward, success in eDiscovery will be defined less by how advanced your review technology is and more by how disciplined your early-case strategy becomes.

We are already seeing:

    • Increased scrutiny of early discovery decisions by courts and opposing counsel3
    • Greater internal pressure on legal teams to explain, not just accept, discovery costs
    • A shift from reactive discovery toward a proactive, repeatable matter framework

Prism Litigation Technology helps organizations take control of discovery at its most critical stage — before costs escalate. By combining strategic guidance with practical workflows and defensible processes, Prism enables legal teams to:

    • Scope matters more precisely from the outset
    • Reduce unnecessary data collection and downstream costs
    • Implement repeatable, defensible discovery practices
    • Align technology with strategy for better outcomes

The result is not just faster discovery, but smarter, more controlled discovery.

Take Control Before Costs Escalate

When discovery strategy begins at review, key opportunities to manage cost and scope may already have passed.

Prism Litigation Technology helps you take advantage of those early opportunities.

Learn more at prismlit.com and start building a more strategic approach to eDiscovery.
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1Federal Rules of Civil Procedure, Rule 26(b)(1). https://www.law.cornell.edu/rules/frcp/rule_26
2The Sedona Principles (Third Edition: Best Practices, Recommendations & Principles for Addressing Electronic Document Production). https://thesedonaconference.org/publication/The_Sedona_Principles
3DR Distributors, LLC v. 21 Century Smoking, Inc., https://www.jdsupra.com/legalnews/court-orders-spoliation-sanctions-6824477. See also, Rimkus Consulting Group, Inc. v. Cammarata, https://www.govinfo.gov/content/pkg/USCOURTS-txsd-4_07-cv-00405/pdf/USCOURTS-txsd-4_07-cv-00405-19.pdf