E-Discovery in 2025: A Case-Based Look at the Challenges Ahead

Last updated: 03 Dec, 2025By
E Discovery Challenges

The 2024 decision in In re StubHub Refund Litigation marked a turning point in how courts view discovery obligations. The issue was whether producing massive volumes of electronically stored information (ESI) was proportional to the needs of the case. The court’s reasoning was clear: discovery must be defensible, measured, and cost-conscious, not a limitless burden.

StubHub is not just more than a precedent. It reflects the e-discovery challenges that now define e-discovery in 2025—managing explosive data growth, integrating AI responsibly, meeting rising expectations of technical competence, ensuring preservation across ephemeral platforms, and protecting sensitive information in high-stakes disputes.

Each area presents risks, but also opportunities for firms that adopt smarter practices. So, let’s examine the core e-discovery challenges, along with solutions and their impact.

Core eDiscovery Challenges Facing Legal Teams in 2025

1. Data Volume and Proportionality

In StubHub, the dispute centered on whether the scope of production was disproportionate to the burden. Courts signaled clearly that sheer volume is no defense—lawyers must show how discovery aligns with the principles of proportionality.

  • Challenge: Data sets in 2025 extend beyond emails to terabytes of Slack messages, shared documents, and video files. Traditional review approaches collapse quickly under this weight.
  • Solution: Early case assessment and analytics-based culling help to narrow data before review. Using sampling and predictive filtering demonstrates a disciplined approach to proportionality.
  • Impact: Firms that master proportionality cut discovery costs, reduce client frustration, and build credibility with courts. Those who fail to do so risk sanctions and wasted resources.

2. AI and Privilege Review

StubHub did not hinge on AI-assisted review, but its scale illustrates why AI is increasingly relied upon. While AI accelerates classification, it also raises privacy risks that legal teams cannot ignore.

  • Challenge: Misclassification by AI can expose privileged or confidential materials, jeopardizing strategy and triggering disputes.
  • Solution: Pair AI with human-in-loop verification, maintain audit trails, and negotiate robust clawback provisions tailored to AI related risks.
  • Impact: This balance preserves the efficiency benefits of AI while protecting privilege and demonstrating to courts that review methods are reasonable and defensible.

3. Technology Competence

A broader lesson from StubHub is that courts expect legal teams to competently manage the tools they employ. Technical missteps are no longer viewed as excusable mistakes but as professional lapses that can impact case outcomes.

  • Challenge: Inadequate command of discovery platforms or AI tools undermines both client confidence and judicial trust.
  • Solution: Regular training, reliance on litigation support professionals, and clear documentation of workflows ensure that counsel can meet rising expectations.
  • Impact: Demonstrates compliance with the duty of technological competence, mitigates malpractice risks, and reassures clients that their cases are handled with technical and strategic rigor.

4. Preservation Obligations

StubHub also underscores the importance of proactive preservation. Courts today are less tolerant of discovery gaps, particularly as ephemeral data becomes central to disputes.

  • Challenge: Messaging apps and collaboration platforms often auto-delete, overwrite, or rotate content, creating spoliation risks.
  • Solution: Implement litigation holds early, engage IT to capture high-risk data sources, and document all preservation steps so the process is transparent and defensible.
  • Impact: Avoids sanctions, protects evidentiary integrity, and signals to courts that preservation is being handled responsibly.

5. Specialized Litigation Risks

Though StubHub was not an intellectual property matter, its lessons extend naturally. In IP disputes, discovery often involves proprietary research and trade secrets. Mishandling such data can cause competitive harm with consequences far beyond the litigation itself.

  • Challenge: Balancing discovery obligations with safeguarding sensitive IP and confidential business data.
  • Solution: Use protective orders, targeted production, and confidentiality protocols that protect IP while meeting obligations.
  • Impact: Preserves competitive advantage, ensures compliance, and demonstrates to clients that litigation risks are being managed proactively and strategically.

Conclusion

In re StubHub Refund Litigation is not just a 2024 precedent; it is a roadmap for 2025. The case illustrates that discovery is no longer about producing “more” but about producing smarter—with proportionality, defensibility, and competence as guiding principles.

For firms and in-house counsel, the path forward is clear: adopt structured approaches to proportionality, govern AI responsibly, invest in competence, and preserve proactively. These steps not only avoid judicial sanctions but also reassure clients that discovery is being managed strategically and efficiently.

For many, the most practical way to achieve this is through litigation support services that combine technology oversight, cost management, and compliance expertise. StubHub’s lesson is simple: in 2025, discovery will define outcomes—and those prepared to meet its challenges will define success.

If you’re seeking a reliable partner to navigate e-discovery challenges with precision and expertise, Legal Support World is ready to help. Connect with our experts today.

Frequently Asked Questions

How is Generative AI (GenAI) impacting e-discovery?

Generative AI is moving from hype to practical application, particularly in document review. Legal teams are using it for coding suggestions, document summaries, chat interrogation, and narrative building, all with the goal of increasing speed and accuracy while significantly reducing the time and cost associated with reviewing massive data sets. However, its use requires human-in-the-loop verification and clear audit trails to maintain legal defensibility and protect privilege.

What is the role of predictive coding and TAR?

Predictive coding (a form of TAR) is becoming the standard rather than an exception. It uses machine learning to prioritize documents by relevance, moving away from linear, manual review. In 2025, there’s a push for smarter, faster methods that combine different types of search (keyword, concept, and AI-driven) to uncover insights more efficiently.

Are organizations moving to the cloud for e-discovery?

Yes. Cloud-centric and hybrid e-discovery solutions are growing rapidly due to their scalability, cost-effectiveness, and ability to facilitate secure collaboration across geographies. Cloud deployment makes it easier to leverage advanced AI and analytics tools.

What is the most critical first step in the e-discovery process?

Courts increasingly expect legal teams to demonstrate competency in managing the technologies they employ for e-discovery. This means legal professionals must understand and properly apply tools for data collection, AI-assisted review, and metadata preservation to avoid sanctions for spoliation or inefficient processes. Ongoing training and expertise are critical.

How do data security and privacy regulations affect e-discovery?

Data security is a top priority. Legal teams are adopting zero-trust security frameworks (continuous verification for all users), implementing stronger encryption and granular access controls, and ensuring compliance with evolving global data privacy regulations like GDPR and CCPA throughout the entire e-discovery lifecycle.

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