Key Takeaway: When it comes to adopting AI for dispute resolution, the real risk lies in unchallenged use. AI already plays a role in dispute resolution, but credibility depends on how it is governed, questioned, and reviewed. Practitioners who adopt AI incrementally, apply human judgment, and ask the right questions reduce risk while gaining accuracy, efficiency, and confidence.

For dispute resolution, the question is no longer if AI will play a role, but how practitioners can use it responsibly and without risking credibility or client trust.

Much of the hesitation around AI stems from high-profile cases in which AI produced non-existent legal sources, otherwise known as “hallucinations.” These incidents, while concerning, are also widely misunderstood. The problem stems from unquestioning reliance on AI by those who use it, not the technology itself. Proper use of AI requires training, awareness of the limitations of AI tools, and diligence in verifying AI outputs. 

The Real Risk Is Not the Technology

Every dispute professional knows to carefully review work from a junior associate to ensure it is free of errors. AI is no different. Its outputs require the same careful review, and responsibility for its accuracy lies with the practitioner who delivers the final product. Human review is essential to maintain accuracy, defensibility, and ethical compliance.

Courts and regulators are not prohibiting the use of AI. Rather, they are allowing it with close attention to long-standing duties of competence, candor, diligence, and supervision. In practice, this allows AI to assist with analysis, research, and review, but it cannot replace professional judgment. Treating AI as a shortcut rather than a regulated and fallible tool is where problems arise.

Confidence Matters More Than Speed

Most practitioners have exposure to AI, even if they hesitate to rely on it. The challenge to adoption is confidence. Though aware of the benefits of AI, many lawyers remain unsure where to begin, such as which use cases to test first or how to validate an output. 

A practical starting point is low-risk use cases. Early case assessment, chronology building, legal research support, and document review offer safe opportunities to test out the benefits of AI. While arguably low-value use cases, they still require validation and clear workflows. This allows for secure adoption without blind trust in the technology.

The seemingly exponential adoption of AI should not prompt a practitioner to feel pressured to dive headfirst into it. The goal is to harness the benefits of automation while remaining confident in the quality and reliablity of your work.

Asking Better Questions Reduces Risk

Responsible AI adoption must begin with asking the right questions, both of the technology and of the suppliers who provide it. Practitioners should expect clear answers on data security, confidentiality, model training, auditability, and validation processes. If those answers are vague or incomplete, that is a signal to look elsewhere.

The same principle applies to prompting. AI responses depend on how you ask questions.

Requests that invite agreement tend to produce reassuring but unreliable answers. For example, asking AI “Does this analysis look correct and compliant?” The result would likely confirm the analysis, reinforce assumptions, and is unlikely to surface errors or missing context. This wording encourages the model to agree rather than challenge, potentially creating false confidence or incorrect assumptions.

Prompts that ask for errors, weaknesses, or alternative views produce more useful results, such as “Identify any errors, unsupported assumptions, or compliance risks in this analysis.” AI will then flag missing citations, unclear reasoning, and areas where legal or regulatory interpretation may be incomplete. This forces the model to stress-test its own output, surfacing risk early.

Prompting is becoming a professional skill, and those who develop it will reduce risk while increasing value.

Smaller Firms May Have the Advantage

Small- and mid-sized firms often assume they are behind larger firms in technology adoption. In reality, they may be better positioned to adopt AI effectively. Smaller firms have fewer layers of approval, a narrower practice focus, and a close proximity to client needs, allowing for faster learning and more targeted use.

AI levels the playing field by reducing reliance on large teams and manual processes. When used well, it supports specialization rather than diluting it. For dispute practices built on expertise and judgment, AI becomes an instrument that amplifies skill, rather than a system that replaces it.

Move Forward Without Losing Control

Responsible, effective AI adoption requires an incremental approach grounded in governance, transparency, and accountability. Practitioners who take the time to understand how AI works, where it fits, and where it does not, will continue to meet client expectations and ethical obligations while exploring the benefits of automated workflows.

The future of dispute resolution will be defined by those who learn to use it carefully, confidently, and responsibly, without fear or shortcuts.

Learn more about Epiq Court Reporting Services.



Lorraine Medcraft, Vice President, Court Reporting
Lorraine enables law firms to maximize efficiency and respond to client demands while staying true to their core values, principles, and commitment to their staff. With over 20 years’ experience providing solutions to law firms, she and her team have worked on a range of projects from information governance and records management, outsourced staffing solutions, to trial technologies and transcription.