Back to Professional-Advisers-Litigation-Support Rankings

USA: An Introduction to eDiscovery

The Modern eDiscovery Landscape 

For legal teams, the current eDiscovery landscape presents an interesting paradox: It’s a moment of immense opportunity with the advancements in technology like AI, however, challenges with data, risk, and economic uncertainty persist, sometimes amplified by this technological evolution. How does the industry move forward?

Despite economic, regulatory, and technological obstacles, leaders in eDiscovery and legal continue to exhibit resilience and an innovative mentality that is paving a path for the future. In this overview, we outline the key challenges for these leaders and teams and highlight the innovative ways they’re overcoming them.

What are the key challenges for the legal industry? 

Economic uncertainty  

While the dire warnings of a recession have dissipated, high interest rates and above-average inflation have contributed to a climate of economic uncertainty. Corporate legal departments face continued pressure to innovate and provide strategic guidance—through areas such as information governance and risk assessment—while doing a higher volume of work with fewer or limited resources. As corporations approach spending more cautiously, outside counsel face pressure to reduce billable hours, accelerate matter resolution, and expand their skills and use of new technology to weather these economic headwinds.

The upcoming U.S. presidential election is also contributing to a climate of uncertainty. Timing for mergers and acquisitions is being evaluated as organisations see a potential shift in regulatory posture if the administration changes. While the DOJ and FTC are currently taking a more aggressive stance on M&A activity, it could evolve in 2025. However, regardless of political changes, the proposed and enacted regulatory changes will certainly impact how organisations respond to these requests.

Increased regulatory scrutiny 

Although forecasts for the economy are not completely clear, regulatory signs are less ambiguous: oversight is becoming more stringent, particularly for M&A and technology.

For mergers and acquisitions, new guidelines published by the FTC identify stricter procedures and enforcement practices for antitrust law investigations and procedures. These guidelines codify the regulatory response to harms caused by what the US government deems as “excessive corporate consolidations” with more vigorous merger enforcement. In addition, proposed changes to HSR premerger notification rules and preservation requirements could potentially increase the burden in filings for parties entering mergers. All considered, this heightened scrutiny will require legal teams to prepare better and explore new technology to expedite and streamline the Second Request process.

Compared to M&A, the regulation of AI is nascent but has recently gained traction, with legal teams taking note. Much like data privacy, the European Union has taken the lead in passing the world’s first comprehensive law on artificial intelligence, the EU AI Act. The law establishes an assessment framework and obligations for providers and users relative to the level of risk posed by artificial intelligence. In the United States, a patchwork of state laws and guidance has emerged with individual states, including California, Connecticut, Massachusetts, and Utah, creating new laws, or adding to existing consumer protection laws to include AI. As the use and adoption of AI tools continue to grow, legal teams must understand the technology, its use cases, and data implications to appropriately navigate these various regulatory obligations.

Transformation with AI 

Laws governing the use of AI may be in their infancy, but the transformative effects of the technology are well underway, presenting both opportunity and challenge. The release of generative AI for enterprise-wide use, with platforms such as Microsoft Copilot and ChatGPT Enterprise, has accelerated the dynamic from more hypothetical questions surrounding data—how it is stored, collected, reviewed, and processed; custodians, and security, for example—to a tangible and urgent reality. This has created a need for legal teams to not only assess the eDiscovery and information governance implications of these tools but also develop frameworks for managing them.

With more available AI solutions, there is competitive pressure to find the most beneficial and efficient ways to utilise it while minimising risk, including for eDiscovery. Understanding the right use case for your business needs is a challenge and corporate legal teams are educating themselves and looking for guidance from technology providers and outside counsel on pragmatic application of both predictive and generative AI.

Courts are beginning to monitor and govern the use of AI in some instances, but no clear standards have emerged. Even with a lag in legal precedent, as legal teams encounter and utilise AI more frequently, they’ll need to understand the technology to negotiate in court and defend their process.

Continued evolution of modern data 

If anything has been a constant for legal teams over the past decade, it’s been the continuous growth in data variety, volume, and velocity. In terms of variety, the emergence of generative AI has created novel data sources and storage, with organisations looking to legal teams to understand their compliance obligations and risk. More intricate and varied collaboration platforms, mobile devices, and virtual work continue to drive an uptick in data volumes and velocity, putting pressure on teams to manage and proactively reduce it before running it through costly review. Finally, legal teams must keep up with emerging legal precedents in handling modern data, including hyperlinks or modern attachments. Even with this case law, however, teams must be proactive in their understanding of the data, including how it’s stored and processed, to have a strategic advantage.

How is innovation moving the industry forward? 

Highlighting the resiliency in the space, legal teams confronted with these challenges were not met with defeat but instead thoughtful and impactful innovation.

Strategic and human-centric approach to AI and analytics

Building on work that innovative legal technologists had done before the launch of popular AI tools such as Copilot and ChatGPT, leaders can now be more discerning about how and why they’re utilising AI for eDiscovery. Natural language processing (NLP) and large language models (LLMs) have been used to develop advanced AI tools built specifically for eDiscovery. Unlike newly released generative AI tools, the advanced AI tools being used in eDiscovery today are purpose-built to accurately learn from and classify corporate data within a closed environment for legal review.

We’re seeing a combination of AI and linguistic modeling deliver production-ready responsive review results at a fraction of the price of traditional review and more accurate classification models for privilege review. Building on this, we’re seeing generative AI used to automate the creation of privilege logs and as a quality control check to ensure that existing privilege logs are consistent and accurate. These advancements in responsive and privilege review have been useful under stringent scrutiny in the antitrust space. In this context, teams are deploying these tools with great success in HSR Second Requests.

In terms of analytics, advanced tools can help isolate key documents much earlier on in a matter, and even help prove a negative inference or theory. This early access to information empowers corporate legal teams and law firms to make better, more strategic decisions from the outset of a matter, including in high-pressure scenarios like Second Requests.

More nuanced and proactive approaches to assessing and governing modern data

To manage the rapid innovation with AI, forward-thinking teams are developing thoughtful and unified positions on AI, which include robust assessments of predictive and generative AI capabilities, risk, and security. Adopting these assessments for AI and other emerging technologies allows for a secure and compliant implementation.

Along with individual assessments, organisations should have a well-thought-out, standardised, and documented information governance framework, including a robust records retention and deletion policy and practical guidance for employees. Company policies must consider enterprise systems (and how they are used by employees)—especially around communication and collaboration platforms.

Optimising workflows for modern and future challenges

Technology is not the only area where legal teams have advanced. They’ve made great strides in refining workflows and strategies to adapt to modern challenges and confront what they see will be the major hurdles in the future. We’ve seen a strategic combination of human expertise and technology deployed to update a variety of workflows, including those used to meet the short deadlines and documentation required for Second Requests. Bolstering standardised TAR workflows with LLMs brings TAR to the current state-of-the-art in predictive AI, enabling eDiscovery practitioners to benefit from unprecedented efficiency and scale.

Innovative leaders are also moving beyond a rigid and expensive approach to review by partnering with experts in linguistics, AI and advanced analytics, review strategy consultants, and technology-forward review teams. This approach optimises review by segregating review tasks into distinct workflows for better, faster outcomes.

Finally, legal teams are seeing long-term benefits by consistently collaborating with innovative partners. These relationships not only help to solve urgent challenges now but experimentation and communication builds to prepare for the next source of disruption that technology alone will not be able to overcome.