Artificial intelligence (AI) is rapidly embedding itself into the core machinery of the criminal justice system, powering everyday decisions from police analysis of digital evidence and pattern detection in crime data to prosecutorial discovery management, charging recommendations, algorithmic risk assessments in courts, and large language models for summarizing records and drafting documents. These tools promise efficiency gains—processing vast data volumes, reducing backlogs, and optimizing scarce resources in an overburdened system—but they also carry profound risks: embedding bias, producing opaque or unreliable outputs, shifting unmonitored power to vendors, and influencing high-stakes liberty decisions like arrests, detention, sentencing, and release. The central problem is that AI capabilities are deploying without sufficient understanding of their mechanics, failure modes, or implications for constitutional rights, democratic accountability, and system legitimacy. Criminal-justice entities who encounter AI tools—thousands of under-resourced police departments, prosecutors’ offices, courts, and probation units—lack the technical expertise to evaluate these tools rigorously, while vendors market directly to practitioners. This creates a governance gap: even well-intentioned actors cannot reliably apply emerging standards amid rapid technological changes, risking uneven, superficial oversight that undermines public trust.