For two decades, eDiscovery has been defined by reaction. A subpoena lands or litigation begins, and the scramble follows: collect, preserve, review, produce. Legal teams shift into high gear, often working under extraordinary pressure to deliver results at speed and scale.

But the script is changing. A growing number of organizations are no longer waiting for litigation to dictate their moves. They’re embedding intelligence—data visibility, automation, and analytics—into the foundation of their legal operations. The result is a shift from reactive to proactive eDiscovery, where preparedness and insight replace firefighting and reactivity.

At Alvarez & Marsal (A&M), we see this transition every day across industries. It’s not just about adopting new tools; it’s about reengineering processes, aligning stakeholders, and reimagining how data and intelligence drive legal strategy.

Rethinking Discovery as a Continuous Process

When Roger Rutkowski joined Mercedes-Benz USA to build and lead Legal Operations, one of his first objectives was to move from episodic responses to continuous readiness. That meant treating data as an asset, something to be governed, measured, and understood, not simply stored.

Through collaboration between Legal, IT, and Privacy, the company integrated eDiscovery into its broader data-governance ecosystem. Data flows are mapped, retention standards enforced, and preservation triggers automated. The payoff is significant: When litigation or investigation arises, much of the work is already done.

From our perspective at A&M, this evolution is a hallmark of mature eDiscovery programs. When discovery is built into the daily operations of a company’s data environment, rather than sitting as a separate, reactive process, the organization gains control. You know where your data lives, how it’s changing, and how to retrieve it efficiently. That readiness shortens response cycles, reduces risk, and eliminates the panic that often defines the early stages of a matter.

Embedding intelligence Into Legal Operations

Intelligence in eDiscovery isn’t about replacing human judgment with algorithms; it’s about giving people the right context, insight, and foresight.

At Mercedes-Benz USA, the Legal Operations team introduced automation and AI across several systems: matter management, contract lifecycle management, and eDiscovery review. Machine learning and analytics are now integrated into day-to-day workflows, creating real-time visibility into data volumes, costs, and risks.

Dashboards provide immediate insight. Predictive models continually refine how documents are classified and prioritized. Review cycles are faster, decisions are better informed, and outside-counsel spend is optimized. Intelligence has become the connective tissue of the department’s operations.

At A&M, we’ve taken a similar approach across our global eDiscovery practice. Intelligence operates in three tiers:

1. Visibility – Dashboards and metrics that reveal where data, cost, and risk reside
2. Automation – Repeatable workflows that reduce manual effort
3. Prediction – Analytics and machine learning that anticipate patterns and outcomes

These layers collectively transform how eDiscovery functions. Large language models (LLMs) are now used to summarize documents, identify privilege, and accelerate early case assessment. Predictive coding and continuous active learning remain essential, but they’re now enhanced by generative tools that add speed and nuance.

The shift isn’t about novelty; it’s about maturity. As Roger describes it, “Legal as a business” means applying the same data-driven discipline to Legal that other corporate functions use to manage performance. As with Mercedes, at A&M we also see that mindset as the key to unlocking value: transforming Legal from a cost center to a strategic contributor.

The Human Factor in Digital Transformation

Every technology transformation begins and ends with people. The most sophisticated systems will fail without trust, fluency, and accountability across departments.

At Mercedes-Benz USA, success depends on close coordination between Legal, IT, and business functions. The team invested in data literacy, process discipline, and shared ownership of outcomes.

The introduction of AI or automation into legal workflows requires governance, validation, and defensibility. Our teams emphasize explainable AI—models and processes that can be audited, tested, and defended in court. Training and change management are essential, not optional.

Digital transformation works when technology supports people, not the other way around. That’s how innovation becomes durable.

From Prediction to Prevention

The next frontier for eDiscovery isn’t prediction; it’s prevention. As data volumes explode and regulatory expectations intensify, the organizations that succeed will be those that identify risk before it becomes exposure.

At A&M, we’re helping clients make that leap through integrated intelligence:

• Chat and collaboration analytics surface key communications from Teams, Slack, and other platforms in real time.
• AI-driven early case assessment uses LLMs to summarize and prioritize documents, cutting first-pass review times dramatically.
• Automated preservation triggers integrate legal hold systems with IT workflows, ensuring defensibility without manual bottlenecks.
• Performance dashboards track spend, and review velocity and risk metrics, giving Legal leadership operational control.

When these capabilities are embedded throughout the data ecosystem, discovery stops being a reactive service. It becomes a proactive intelligence layer that informs broader business strategy.

Challenges Along the Way

Transformation doesn’t come without obstacles. From both the in-house and advisory lens, we see several recurring challenges:

1. Data complexity. Organizations are managing unprecedented data diversity: email, chat, mobile, social, structured systems, and cloud storage. Without clear governance and ownership, intelligence can’t take root.
2. Tool fragmentation. The market is saturated with point solutions. Integrating them into cohesive workflows—and ensuring interoperability—is often harder than selecting the technology itself.
3. Change management. Technology adoption depends on culture. Without executive sponsorship and training, even the best tools remain underused.
4. Measurement and ROI. Transformation must be quantified. Metrics like cost per document, review speed, automation rate, and cycle time validate the business case for investment.
5. Cross-border and privacy complexity. Global discovery now spans multiple jurisdictions with conflicting regulations. Proactive intelligence helps organizations plan for these constraints before they face them in court.

Building the Intelligent eDiscovery Function

From the combined experiences of Mercedes-Benz and A&M, several best practices emerge for organizations ready to embed intelligence:

1. Start with data mapping. Understand your data sources, ownership, and retention policies. Visibility is the prerequisite for intelligence.
2. Connect systems. Integrate legal hold, matter management, and discovery tools to automate hand-offs and reduce manual error.
3. Apply AI early. Use analytics at intake and early case assessment, not only during review.
4. Establish governance. Document how automation and AI are deployed and validated. Defensibility is as important as efficiency.
5. Train and align teams. Make Legal, IT, and Compliance partners in process and outcome.
6. Measure relentlessly. Track performance metrics and communicate success to stakeholders.
7. Iterate and scale. Treat intelligence as a journey, not a project. As data evolves, so must your approach.

Why It Matters

Proactive eDiscovery isn’t a luxury; it’s a necessity in the modern data environment. The volume, velocity, and variety of information are outpacing traditional models. The only sustainable path forward is intelligence: systems that learn, adapt, and anticipate.

For organizations that embrace it, the benefits go beyond cost reduction. Proactive intelligence drives better decision-making, faster response times, and stronger defensibility. It positions Legal as a strategic partner in enterprise risk management.

At A&M, we believe this evolution marks a turning point for the industry. The firms and departments that embed intelligence into their discovery programs will not only handle today’s data challenges—they’ll be ready for tomorrow’s.

The Road Ahead

For those of us who’ve led or advised on this transformation, the lesson is clear: When intelligence becomes part of the process, you don’t just change the tools; you change the trajectory of the entire legal function.

eDiscovery’s future is not about faster reaction; it’s about smarter prevention. It’s about turning data into foresight, and foresight into strategy.

And that shift—from reaction to readiness—is what will define the next generation of legal operations and discovery professionals.