This chapter establishes the conceptual foundations of AI, exploring both its technical aspects and philosophical underpinnings to understand what it is and is not, and how these perspectives shape expectations in legal settings. This is followed by a critical look at significant normative concerns surrounding AI deployment, such as privacy, transparency, and bias, discussing how AI tools can potentially amplify systemic inequalities and identifying necessary safeguards. The discussion then transitions to the practical applications of AI within ADR, detailing current tools used for legal prediction, document automation, contract analysis, and case management, and evaluating their integration and effectiveness through examples like CoCounsel and the BC Civil Resolution Tribunal. The exploration is further enhanced with case studies and hypothetical scenarios to illustrate AI’s potential role in mediation or arbitration and the resulting ethical, practical, and legal challenges presented by non-human involvement in decisions. Looking ahead, the material addresses future developments and challenges, considering anticipated AI trajectories, regulatory issues, algorithmic accountability, access to justice, and the design of ADR systems that balance efficiency with human considerations. Finally, it concludes by revisiting core principles like relational justice, epistemic repair, and transformative practice, emphasizing their importance in guiding decisions about the adoption of AI, including the underlying motivations. By the end of this chapter, readers will have a critical framework for understanding AI’s transformative—and potentially disruptive—role in ADR.
