What Is AI and Copyright?
AI and copyright encompasses three intersecting legal questions: can AI systems legally train on copyrighted works, who owns the outputs that AI generates, and what obligations do organisations have when employees use AI to create content. In March 2026, the US Supreme Court denied certiorari in Thaler v. Perlmutter, confirming that AI-generated works without human authorship cannot be copyrighted under US law. Courts are drawing increasingly clear lines on training data legality — in Bartz v. Anthropic (June 2025), training on legally acquired copyrighted works was found to be transformative fair use, while using pirated copies was not.
AI Copyright — the body of law and contract concerning rights in AI training data, AI-generated outputs, and the use of copyrighted material by AI systems.
AI copyright is contested across three distinct questions. First, whether AI training on copyrighted material is fair use — Bartz v Anthropic (2026) found legal training data could be transformative fair use. Second, whether AI outputs that compete commercially with their training sources are fair use — Thomson Reuters v Ross (2026) said no. Third, whether AI-generated work is copyrightable at all — the US Supreme Court denied certiorari in Thaler v Perlmutter (March 2026), settling that purely AI-generated work is not.
Source: Bartz v Anthropic; Thomson Reuters v Ross; Thaler v Perlmutter; EU AI Act Article 53
Why it matters for governance
For organisations, AI copyright governance requires policies covering three areas: training data due diligence (ensuring AI vendors' training data was legally sourced), output ownership documentation (maintaining records of human creative contribution to support copyrightability of AI-assisted work), and employee guidelines on AI content creation (clarifying ownership expectations, disclosure requirements, and quality review). The EU AI Act requires GPAI providers to publish training data summaries and comply with copyright opt-out mechanisms from August 2025.