AI is precipitating a paradigmatic shift in the architecture of complex litigation. The hype around AI, compounded by the sharp divergence in quality of AI tools and their outputs, makes the extent of the transformation difficult to perceive. But litigation is definitely changing—more than it has in decades, and the scale of change is likely to rapidly accelerate, at least for some tools and AI systems.
The AI-driven shift is likely to upend the complex litigation process. The workflows and structures are likely to evolve, but the central role played by the litigator and the case team will not change because litigation’s essence is irreducibly human; experience required to traverse adversarial nuances with human presence and ethical bearing remains beyond the reach of any AI tool.
Discernment and Nuance in Complex Litigation
Litigation is among society’s most complex systems, encompassing interlocking procedural layers and structural frameworks that govern every stage of a case. But the complexity of litigation is now more manageable than ever through a combination of process, expertise, and sufficiently well architected AI systems. Even as this transformation occurs, attorney expertise will continue to be at the center.
In litigation, every action and reaction can trigger a cascade of consequences. Decisions made at the pleading stage, for example, impact potential discoverability of evidence. Managing deposition witnesses while simultaneously anticipating how a judge (or later, appellate court) may read the record adds yet another layer of sophistication. At every overlapping inflection point, where a contemporaneous determination forecloses or opens future probabilities, the lawyer’s ability to reason with the case’s full trajectory in mind is integral.
Challenges are compounded by the adversarial nature of litigation, in which the opposition seeks not only to break any previously identified patterns, but also to disrupt emerging patterns triggered by shifting data points. It is here that seasoned judgment is most decisive, with the recognition, for example, that a late-produced document may reframe the narrative or that a broader case strategy needs to be reassessed based on results of an unrelated case.
Complex litigation demands layered and discerning judgments by lawyers who absorb nuances and make impactful decisions based on experience that algorithms cannot replicate.
Human presence
Litigation experience is also essential and particularly so because of the extent to which litigation requires human presence. The litigator—not an AI tool—addresses client concerns, hopes, and fears, interacts with opposing counsel, deposes witnesses, and stands up in court. A lawyer physically embodies the litigant interests at stake and executes the narrative. After AI delivers mastery of the facts, the lawyer leverages those facts, telling the story to a human judge, jury, and counterparty.
When tools take on the algorithmic labor of document review and other data analyses, they free litigators to immediately dive into deep case strategy and planning. Those tools allow movement away from work that is primarily computational to focus on weightier issues. How do the documents interact with each other and with the case arc? How does opposing counsel appear to be neutralizing them? What stories can the documents tell, which story will most effectively benefit the client, and how can I best tell that story?
Whatever the answers, lawyers are mentally “there” throughout. With emotional intelligence, they exercise relational judgment and participate rather than simply observe. An emotionally attuned lawyer reads the deponent who may not be lying but is not telling the whole truth. That lawyer sees the case-changing hesitation a witness won’t voice and hears the question opposing counsel tellingly does not ask. AI’s organizing the evidentiary landscape and preparing documentary inventory, does not diminish the litigator’s role as an advocate. It enhances it, as the litigator’s full attention turns to assessing witnesses and building strategic records.
Litigators’ perceptions are not tasks to be delegated because they are not tasks at all. Presence cannot be trained into a model; it reaches beyond processing to interpretation, serving as the foundation upon which, applied to lived experience, litigation’s essential decisions are made.
Ethical responsibilities
Lawyers do not make decisions in a vacuum. The profession is bound by self-regulating rules of professional responsibility. The framework demands a lawyer capable of self-regulation not only as a matter of compliance, but also as a cornerstone of professional and procedural integrity. Lawyers are expected to internalize ethical standards independently, without court supervision or adversarial oversight, even when monetary constraints and client pressures conspire to engender moral compromise.
Beyond ethical responsibilities, each lawyer occupies a role that is, at its most fundamental level, a risk transfer mechanism. Simply put, when a client retains a lawyer, risks shift and attach to a specific person as the resulting professional relationship becomes the core unit of accountability. That accountability cannot be delegated to a tool bearing no professional obligations or consequences.
Accountability in its most basic form requires the existence of a party with something at stake—reputational, financial, professional, or personal. A tool has no such stake. It cannot be sanctioned, disbarred, sued for malpractice, or held in contempt. It is structurally indifferent to consequences.
Tools do not exercise moral responsibility through challenges or navigate conflicts of interest. When a client’s instructions blur ethical lines or rules of professional responsibility require disclosing evidence adverse to a client’s position, accountability is essential. A lawyer with professional obligations cannot disclaim them, and courts will not allow abdication of professional responsibility based on AI use.
What this moment reveals
What it means to litigate at an elite level is changing, the threshold assumptions that underlie the procedural rules are being upended, and the compositions of case teams in complex litigation are evolving swiftly. The ramifications of these advancements are likely to be far reaching. One thing that is unlikely to change, however, is the role of the (human) litigator, who will remain at the center of the litigation arena. It will be the litigator’s job to read the room, see into the eyes of the jury, hear unasked questions, and know when an algorithm’s suggestion is not right in a particular moment. AI cannot take on those roles; it can make litigators better equipped to do what they have always done.
One way to think about litigation is as an extraordinarily complicated game. It involves cascading rulesets that vary with each matter and are themselves subject to ongoing reinterpretation. It involves distinct but interrelated mechanisms for resolving legal, factual, procedural, and evidentiary disputes. By any measure of linguistic and logical complexity, it may be the most complicated game society has devised.
