AI's actual capability in litigation remains narrower than headlines suggest. The technology excels at high-volume document processing—extracting data, comparing materials, and drafting summaries faster than paralegals or associates can manage. But it cannot accelerate case timelines. Lawyers must still interpret AI-generated materials and craft arguments for court. Every output requires human approval before filing. The practical effect is that AI functions as a workflow accelerator for discrete tasks, not a replacement for legal judgment. The copyright landscape is also settling: recent rulings involving Anthropic establish that training data must be obtained legally through permission-based models, barring the use of pirated content for large language model development.
Attorneys should monitor two regulatory deadlines converging this summer. Colorado's AI Act (SB 24-205) takes effect June 30, 2026, requiring impact assessments for high-risk AI systems. The EU AI Act follows in August. These rules will force firms to formalize ethical policies and document AI decision-making in discovery and litigation. Simultaneously, corporate clients increasingly expect outside counsel to demonstrate AI capabilities in pretrial work. Firms that cannot articulate their AI workflows face structural disadvantage as in-house legal teams reduce reliance on outside counsel. The DOJ's Task Force signals that federal agencies are actively managing both AI risks and efficiency gains—a benchmark for how the profession should operate through 2026 and beyond.