There is a seductive narrative gaining momentum in legal technology circles: artificial intelligence will soon handle routine judicial tasks, predict case outcomes with scientific precision, and free human judges to focus on "higher-value" work. It is presented as technological destiny, a wave we cannot stop and probably should not try to.
This framing deserves serious pushback.
The premise rests on a fundamental misreading of what judging actually is. Proponents of AI-assisted adjudication typically focus on efficiency metrics: faster case processing, reduced backlogs, standardized decision-making. These are real problems in many court systems. The error is assuming that adding computational power solves them without eroding something essential about the judicial function itself.
Consider the implicit assumptions. An AI system predicting outcomes based on historical case data is, by definition, predicting what past judges have done. It is not discovering objective legal truth. It is encoding the decisions, biases, and blind spots of previous judicial decision-makers into an algorithmic form. If those historical decisions reflected systemic inequities in how certain communities were treated, the model does not cure that problem. It potentially amplifies it at scale and obscures its origin behind the appearance of mathematical neutrality.
The legal technology industry has begun to treat this scenario as inevitable in a way that should concern anyone paying attention to how major institutional changes actually happen. They are not being forced upon us by physics or mathematics. They are being actively promoted by vendors with commercial interest in adoption, adopted by court administrators under budget pressure, and normalized by thought leaders who benefit from being perceived as forward-thinking.
This is not to say AI has no role in legal systems. Predictive analytics can help courts allocate resources. Natural language processing can assist with document review. These are tools, not replacements for human judgment.
But there is a crucial difference between using technology to support judicial work and automating the decision-making itself. The first enhances human judgment. The second outsources it.
A judge deciding a case involving questions of fairness, credibility, or the application of broad legal principles to novel circumstances is performing something that cannot be meaningfully reduced to pattern matching. That judgment requires accountability. If a judge makes a decision that seems unfair, we can appeal, we can scrutinize the reasoning, we can hold that judge accountable at election time or through other mechanisms. If an AI system produces an outcome, the explanation is often opaque even to its creators. "The model said so" is not a sufficient legal justification, yet it increasingly functions as one.
We should also be skeptical of the efficiency argument itself. Faster case processing sounds universally good until you ask faster for whom. If AI systems make it cheaper and easier to process certain types of cases, courts may have less incentive to address underlying system failures. Why fix broken discovery rules if you can just automate around them?
The legal technology industry is not wrong that many courts are struggling. Backlogs are real. Resources are thin. But the solution to institutional stress is not always technological. Sometimes it is political and budgetary. Sometimes it requires asking hard questions about how many cases we are actually trying to process and whether that is even the right goal.
We can acknowledge the genuine problems without accepting the proposed solution as inevitable. Courts are not software. Judging is not a service to be optimized. And inevitability is a rhetorical device, not a destiny.
The conversation we should be having is not whether AI in courts is coming. It is whether we actually want it, what we lose if we implement it carelessly, and whether there are better ways to address the real pressures our legal system faces. That discussion deserves more skepticism and more humility than it is currently receiving.