Artificial intelligence is increasingly shaping dispute resolution, with growing relevance for mediation. Bruce Edwards in his article, "Artificial Intelligence in Mediation and What the Future Holds for Mediators”, notes that while AI tools are not yet widely adopted, they are steadily being integrated to support mediators in structuring processes, analysing information, and facilitating communication.

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Mediation relies on effective information management, communication, and neutral facilitation to reach mutually acceptable outcomes, often placing heavy cognitive and administrative demands on mediators in complex cases. Edwards notes that AI can reduce this burden by streamlining processes and strengthening analytical capacity.

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Katie Shonk, in her article "AI Mediation: Using AI to Help Mediate Disputes”, notes that AI in mediation is gaining growing scholarly and practical attention. She explains that although not yet widely adopted, AI tools are being developed to support mediators through efficiency, communication management, and data-driven insights.

One of the most important contributions of AI in mediation lies in its ability to process and organize vast amounts of data quickly. Disputes often involve extensive documentary evidence, communications, and contextual information that can be difficult to synthesize in real time. AI systems, particularly those based on natural language processing and machine learning, can rapidly search, categorize, summarize, and extract relevant insights from this data. This allows mediators to focus more on substantive negotiation and less on administrative processing.

AI tools can enhance mediation by providing data-driven insights that support decision-making and negotiation strategies. They identify patterns and areas of agreement in disputes, helping mediators understand interests and settlement options while complementing rather than replacing human judgment.

Another emerging function of AI in mediation is communication management. In multi-party disputes, especially those conducted online or across different jurisdictions, AI systems can help organize communication flows, track negotiation progress, and ensure that key information is not lost or overlooked. This contributes to a more structured and transparent mediation process, potentially increasing efficiency and reducing misunderstandings between parties.

Despite these advantages, Edwards also emphasizes that the integration of artificial intelligence into mediation practice presents both opportunities and challenges. On the positive side, AI has the potential to make mediation more accessible, efficient, and cost-effective. It can reduce time delays, support mediators in managing complex cases, and enhance the overall quality of dispute resolution services.

However, the use of AI also raises important concerns. These include the risk of over-reliance on automated systems, the possibility of errors in AI-generated outputs, and questions regarding transparency and accountability in algorithm-driven processes. Since mediation relies heavily on trust, neutrality, and human judgment, any technological intervention must be carefully designed to support—not undermine—these core principles.

However, the successful adoption of such systems is conditioned by structural constraints, UNDP in its policy brief; Assessing Rwanda’s Potential in Artificial Intelligence and Innovation, highlights structural constraints to Rwanda’s AI development, including limited advanced AI talent, fragmented data systems, high compute costs, and financing gaps for deep-tech innovation. It also warns that without inclusive strategies, AI risks widening existing digital and socio-economic inequalities, particularly affecting women, youth, rural, and vulnerable groups. In ADR, these constraints may directly impact the fairness and inclusiveness of AI-enabled mediation systems.

Artificial intelligence is ready to play a transformative role in the future of mediation. As Edwards suggests, while it is not yet a dominant feature of dispute resolution systems, its increasing integration signals a shift toward more technologically supported mediation practices. The central challenge, moving forward, lies in balancing innovation with caution, ensuring that AI enhances rather than undermines the integrity of mediation as a human-cantered process.

The writer is a legal researcher and mediator.