#USA #New York #J.S. Held #AI Litigation #Technology Risk

The Evolution of AI Litigation: Insights from J.S. Held

In a significant update, J.S. Held, a global consulting firm, has released its third-quarter report for 2026 on AI-related litigation. This report highlights a transformative trend in which the focus of legal disputes has shifted from the design aspects of AI systems to their behaviors and outcomes once deployed in the real world. As AI technology continues to permeate various sectors, it brings forth unique legal challenges that necessitate a comprehensive understanding of both technical and legal implications.

Key Findings of the Report

The latest findings indicate that the total number of cases monitored has reached 468, with 42 new cases introduced in the third quarter alone, up until September 30, 2026. Historically, AI litigation was predominantly concerned with copyright issues and the utilization of training data. However, the report notes a noticeable shift towards examining how these systems operate post-deployment. This involves an increased scrutiny of AI outputs, automated decision-making processes, and the ethical ramifications tied to their transparency and accountability.

Expansion of Litigation Landscape

While copyright and training data disputes remain prevalent, the recent influx of cases reveals a broader canvas of issues being addressed by courts. Disputes now encompass not just the datasets used to create AI systems but also the consequences that arise from the integration of AI into consumer products and business operations. James E. Malackowski, the Chief Intellectual Property Officer at J.S. Held, emphasized that the required evidence for litigation will likely have to detail both the origin of training data and the resulting behaviors exhibited by AI systems.

The shift in focus represents an evolution from merely asking whether developers had permission to utilize certain data to probing deeper into the operational outcomes - essentially questioning how well these systems function and the safeguards put in place to mitigate risks.

Understanding System Behavior and Legal Risks

The report outlines the importance of examining various facets of AI deployment when assessing litigation risks. This encompasses everything from the specific version of the AI model used in a case to the logs of activities and decisions made throughout its operation. Legal evaluations will require a robust understanding of not just the technology but also the metrics of governance and the potential economic impacts resulting from the AI’s behavior.

It's crucial for organizations to comprehend these evolving legal landscapes to effectively manage risks associated with their AI deployments. Companies must ensure that their governance frameworks adequately address these challenges, providing clear insights into how their systems operate, the safeguards they have implemented, and any potential consequences that may arise from their use.

Two Forms of Disclosure Risks

The introduction of two distinct types of disclosure risks surrounding the use of AI has been highlighted in the report. The first relates to potential misrepresentation of the capabilities of AI systems, a practice often referred to as