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Are You Ready for AI in Adjudication?

When a decision-maker leans on a model, the questions counsel has to ask change shape.

Are we ready for AI judges? It sounds like science fiction. But as iDS CEO & Founder Dan Regard makes clear in the eighth installment of the Regarding Evidence column in Today’s Managing Partner, it isn’t a hypothetical — it’s already happening.

It’s Already Here

Automated Dispute Resolution is not a future concept. It is a present reality in Canada, Australia, China, and Mexico, among others.

In British Columbia, the Civil Resolution Tribunal has been resolving small claims and motor vehicle injury disputes with appealable automated decisions for years. In Australia, state tribunals use algorithmic triage and structured decision pathways to handle tenancy, consumer, and small-value claims — with algorithms determining how disputes are categorised and processed before a human adjudicator ever gets involved.

In the private sector, the scale is staggering. By 2010, eBay was resolving approximately 60 million disputes per year, with around 90% handled entirely by software. The fact that eBay no longer publishes these figures, Regard notes, reflects just how normalised large-scale algorithmic adjudication has already become.

Where AI Adjudication Makes Sense

Not all cases are created equal, and Regard is careful to define where algorithmic adjudication is genuinely well suited: high-frequency, low-complexity matters where efficiency is the primary goal and outcomes don’t involve significant human rights or liberty concerns.

Debt collection, eviction filings, traffic violations, unemployment eligibility, standardised contract disputes — these categories represent an enormous volume of cases that currently strain court systems globally. The World Justice Project found that in at least 62% of countries, a majority of people with legal problems who needed a resolution mechanism simply couldn’t find one. AI adjudication, applied thoughtfully, offers a path to closing that gap.

The Hallucination Problem — and the Solutions Emerging

Regard doesn’t sidestep the risks. As of early 2026, there have been at least 733 documented cases worldwide where AI hallucinations featured in court submissions. That track record demands caution.

But he also points to the solutions beginning to emerge. Tools designed to limit the universe of documents an AI considers, enforce proper citation practices, and establish verified standards for certain facts are already entering the market. The technology is evolving alongside its known failure modes — and the legal profession needs to evolve alongside it.

What It Means Either Way

Perhaps the most practical takeaway for legal professionals is this: even if your cases are never decided by AI, the foundations AI adjudication requires — clarity, consistency, and accountability in how disputes are documented, categorised, and filed — strengthen traditional decision-making too. Building processes that work for both humans and machines leads to better outcomes regardless of whether AI ever enters your courtroom.

As Regard puts it, drawing on William Gibson’s often-quoted observation: the future is already here. It’s just not evenly distributed.

At iDS, staying ahead of the technology reshaping evidence and dispute resolution is central to how we serve our clients. Our Digital Forensics, eDiscovery & Disclosure, and Structured Data & Analytics practices are built for a legal landscape that is evolving faster than most organizations can track.

To connect with an iDS expert, visit idsinc.com.

iDS provides consultative data solutions to corporations and law firms around the world, giving them a decisive advantage – both in and out of the courtroom. iDS’s subject matter experts and data strategists specialize in finding solutions to complex evidence challenges, ensuring data can be leveraged as an asset, not a liability. To learn more, visit idsinc.com.


Having trouble with a technical term used in this post? Check out our Data Investigators Glossary to crack the code. 

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