Chess, Not Checkers: Future Trends in Litigation and eDiscovery Technology

In our last post, we discussed the use of ESI protocols in complex litigation and the information needed to negotiate from a position of power.

We used the analogy of chess vs. checkers in the first post in this series to illustrate the difference between typical litigation cases and complex litigation scenarios, like class-action lawsuits and multi-district litigations (MDLs). How do you make complex litigation less complex? By continually finding new ways to leverage ever-changing technology tools to streamline litigation and eDiscovery workflows  in order to address emerging challenges. In our last post in this series, we will discuss potential future trends in technology that could impact complex litigation.

Potential Future Technology Trends for Complex Litigation

Several looming technological developments are poised to significantly impact the management of litigation and discovery. These emerging technologies have the potential to enhance efficiency and reduce costs but also introduce new challenges in legal practice. Here are key developments to watch:

Agentic AI

The emergence of agentic AI – AI systems capable of autonomous decision-making, task execution, and iterative learning – could dramatically reshape litigation and discovery management. Unlike traditional AI tools that assist with specific tasks, agentic AI can orchestrate workflows, adapt dynamically, and interact intelligently with legal professionals and data systems. Below are key areas where agentic AI could have a profound impact:

• Autonomous Litigation Project Management: AI agents could orchestrate workflows, track deadlines, assign tasks, and provide real-time risk monitoring.
• Dynamic Discovery Optimization: AI could autonomously refine ESI searches, privilege reviews, and compliance checks, adapting as new evidence emerges.
• Continuous Compliance & Ethical Safeguards: AI could continuously check for privilege risks, regulatory changes, and bias in legal decision-making to ensure ethical discovery.
• Litigation Cost & Resource Optimization: AI can predict case costs, suggest alternative fee arrangements, and optimizes workload allocation for efficiency.
• AI-Driven Settlement & Strategy Insights: AI can analyze case trajectories, predict optimal settlement points, and adjust strategies in real time.

Advanced Deepfake Detection and AI-Generated Evidence

As deepfake technology and AI-generated evidence become increasingly sophisticated, litigation teams will need to develop new strategies to authenticate digital content, assess the reliability of AI-created materials, and navigate evolving discovery obligations:

• Authenticating Digital Evidence: As deepfake technology improves, courts will need AI-powered forensic tools to verify video, audio, and document authenticity.
• New Discovery Obligations: Lawyers may soon be required to account for AI-generated evidence and deepfake manipulations, adding complexity to eDiscovery.
• Synthetic Witnesses & AI Depositions: AI-generated personas could be used for predicting witness testimony outcomes and even simulating depositions!

Blockchain and Smart Contracts in Legal Evidence

As blockchain technology and smart contracts gain traction in legal and business transactions, they present new opportunities for securing digital evidence, ensuring the integrity of discovery materials, and automating aspects of dispute resolution.

As evidence changes, ensuring the integrity of that evidence will continue to be more important. The use of blockchain and smart contracts to help ensure integrity of the evidence is likely to become more important:

• Tamper-Proof Discovery Data: Blockchain can be used to track chain-of-custody for electronically stored information (ESI), ensuring document integrity and preventing spoliation claims.
• Automated Compliance & Discovery Logs: Blockchain-based logs could provide immutable records of data access, reducing litigation risks related to improper handling of evidence.
• Smart Contracts in Dispute Resolution: Self-executing contracts could automate enforcement and dispute resolution, shifting some legal conflicts away from litigation.

AI-Driven Real-Time Legal Translation

As cross-border litigation and multinational regulatory matters become more common, AI-driven real-time legal translation is poised to break down language barriers, accelerating discovery, improving courtroom communication, and reshaping how legal teams handle multilingual evidence. Of course, there are bias and accuracy risks: translation errors in legal AI could introduce misinterpretations with serious legal consequences.

• Multilingual Discovery at Scale: AI-enhanced legal translation tools could instantly translate international discovery materials, reducing delays in cross-border litigation.
• Real-Time Court Interpretation: AI could replace human interpreters in depositions, hearings, and arbitrations, making global litigation more efficient.

Autonomous Legal Reasoning & AI-Led Arbitration

As AI systems become increasingly capable of legal reasoning, the prospect of autonomous arbitration and AI-assisted decision-making raises fundamental questions about the role of human judgment, fairness, and the future of dispute resolution in litigation. Could AI replace or complement human judges and arbitrators? Hint: It already has been used by judges to help in decision making!

• AI as an Independent Legal Arbitrator: Advanced AI models may be granted limited authority to mediate and resolve legal disputes outside of court.
• AI-Generated Case Law Citations: Future AI tools might autonomously generate legal arguments and identify supporting case law, redefining traditional litigation research.

Swarm Intelligence & Decentralized AI Decision-Making

As AI systems evolve beyond single models into decentralized, collaborative networks, swarm intelligence has the potential to revolutionize litigation strategy, discovery management, and legal decision-making. But it could also raise new questions about accountability, coordination, and ethical oversight: Who is responsible if a swarm-based AI system makes an erroneous legal decision?

• Collective AI for Case Strategy: Swarm intelligence – AI networks that mimic group decision-making – could allow legal teams to crowdsource optimal litigation strategies from AI collectives.
• Distributed AI for eDiscovery: AI agents operating in multiple jurisdictions could collaborate in real-time, autonomously handling cross-border discovery in international litigation.

Extended Reality (XR) in Litigation

As extended reality (XR) technologies – encompassing virtual, augmented, and mixed reality – become more sophisticated, they offer transformative applications for litigation, from immersive trial presentations to AI-enhanced document review and remote witness testimony.

• Virtual Reality (VR) for Courtroom Simulations: Lawyers could use VR environments to recreate crime scenes, accident reconstructions, or contract disputes for juror analysis.
• Augmented Reality (AR) for eDiscovery Review: AR-enabled AI could overlay insights on documents, showing real-time annotations, case law references, and litigation strategy suggestions.
• Holographic Depositions & Witness Testimony: XR technology could enable remote 3D holographic depositions, allowing courts to assess nonverbal cues better than traditional video.

Want more? As quantum computing advances, it could revolutionize eDiscovery by rapidly processing vast datasets and breaking traditional encryption methods, necessitating new security protocols for privileged legal communications. Meanwhile, neuromorphic computing and brain-machine interfaces (BMIs) may introduce novel forms of digital evidence, raising complex questions about the admissibility and ethical implications of neurodata in litigation. Who knows what other potential technological developments could impact complex litigation in the future?

Conclusion

Do some of these technological advances seem far-fetched (or at least well down the road)? Perhaps – or perhaps not. Three years ago, did you anticipate the rapid evolution of generative AI that we’ve seen today? Many of you would probably answer “no” to that question – yet many of us are already recognizing the benefits that GenAI can provide in complex litigation scenarios.

Complex litigation is a game of chess, not checkers. There are key elements needed to manage it effectively, including strategic planning and early case assessment, data collection strategies, effective leveraging of generative AI and application of human oversight. Complex scenarios including factually similar cases, class-action lawsuits, and multi-district litigations (MDLs) require unique strategies to optimize discovery and the use of ESI protocols in a way where you can negotiate from a position of power. All while keeping an eye on emerging technology.

As complex litigation challenges become more complex, they require increasingly complex solutions to reduce the complexity. It’s important to work with a partner that is looking ahead at emerging technologies to determine how they can be applied to Cimplifi, er, simplify complex litigation!

For more regarding Cimplifi eDiscovery, litigation, and investigations services, click here.

Chess, Not Checkers: Strategic Approaches to Complex Litigation

• Key Elements of Effective Litigation Management
• Early Case Assessment and Strategic Planning
• Data Collection Strategies in Complex Litigation
• Navigating eDiscovery with AI and Tech Solutions
• The Human Element
•  Multi-Case Strategies for eDiscovery
• Negotiating from a Position of Power
• Future Trends in Litigation Technology