On June 29, 2026, McKool Smith published its latest AI Litigation Tracker, a running review of generative AI copyright suits in media and entertainment prepared by principal Avery Williams (McKool Smith). Read together with entries from April through June, the tracker shows courts edging away from quick exits and toward fact-heavy fights that will shape how models train on creative works.
What McKool Smith’s AI Litigation Tracker shows
The pattern is procedural but telling. According to McKool Smith’s AI Litigation Tracker entry dated June 18, 2026, plaintiffs in Richard Kadrey, et al. v. Meta moved to certify summary judgment issues for interlocutory appeal, citing prior rulings by Judge Chhabria (McKool Smith). On April 7, 2026, that same tracker noted the court had “reluctantly” allowed an amended complaint in the case. Plaintiffs are reframing claims and trying to tee up legal questions early, a sign they want appellate guidance before a full trial record locks in.
The May 18, 2026 entry points to continuing discovery fights in Sarah Andersen et al. v. Stability AI, et al., including the court granting requests for letters rogatory—formal help to obtain evidence across borders (U.S. Department of State). That detail underscores the cross-border nature of training-data questions and the logistical cost of proving who scraped what, where, and when.
Another thread runs through the May 5, 2026 entry on the Southern District of New York multi-district litigation: even with discovery supposedly closed, filings linger. According to the AI Litigation Tracker, “straggler issues” remain, which suggests judges are still sorting out what material belongs in the record for any coming dispositive motions (McKool Smith).
What the McKool Smith tracker says about early motions
Two April entries show how courts are treating threshold attacks. On April 20, 2026, McKool Smith reported that in Sony v. Uncharted Labs (d/b/a Udio), the defendants’ motion to dismiss was denied—at least for now—after briefing that touched the YouTube “rolling cypher” (cipher) issue. That keeps anti-circumvention and access questions alive into later stages (McKool Smith). On April 13, 2026, the tracker noted that in Disney et al. v. MiniMax & Hailuo AI, the defendants filed motions to dismiss, setting up another early test of how specific rights-holders must plead training, outputs, and market harm (McKool Smith).
The throughline: judges are less willing to end disputes at the pleading stage when the facts about training datasets, technical measures, and model behavior are contested. That matches the technology itself. Generative AI systems learn from large corpora, often including media content—facts that affect both copying and fair use analyses (Wikipedia). Courts are asking for a fuller record before writing broad rules.
Why these lawsuits matter for media and model makers
These procedural beats carry practical stakes. Plaintiffs are shifting from sweeping narratives to targeted claims that survive to discovery, and, in some cases, toward certified legal questions that could clarify the law faster than a full trial. The bid for interlocutory appeal in the Kadrey case highlights that strategy. An interlocutory appeal is a request to take up specific legal issues before final judgment, typically only when a court certifies that immediate review may materially advance the litigation (Cornell LII). If appellate courts accept such issues, the resulting opinions could set the contours for what counts as permissible training or actionable copying.
Discovery-framing matters just as much. Letters rogatory, noted in the Andersen suit, suggest key evidence sits abroad, with service providers or data hosts outside the United States. That can slow cases and raise costs, which can pressure settlements or, inversely, deepen parties’ resolve to seek precedent.
The “rolling cypher” reference in the Udio dispute shows why access and anti-circumvention theories keep resurfacing. If a court treats a platform’s dynamic signature or similar mechanism as a technological protection measure, it can pull the Digital Millennium Copyright Act’s anti-circumvention provisions into play. That would widen the risk for model builders who gather training inputs by bypassing such controls, even if outputs are later argued to be transformative. The line between training and scraping defenses is narrowing because access questions can precede fair use.
Policy backdrops also loom. The U.S. Copyright Office has reminded creators and companies that authorship claims turn on human creative input, and it has flagged the unsettled status of training uses and output liability (U.S. Copyright Office). While that guidance doesn’t decide the disputes tracked by McKool Smith, it informs what evidence plaintiffs collect and how defendants frame their compliance programs.
How the AI Litigation Tracker reframes 2026’s fights
By collating short, dated entries across multiple dockets, the AI Litigation Tracker surfaces what individual filings don’t: 2026 is a grind. Early motions are thinning out. Discovery is sprawling. Plaintiffs are amending to survive. Defendants are pushing courts to isolate dispositive legal issues for possible early review. This is the phase where facts about data provenance, technical guardrails, and model behavior meet doctrine.
For studios and publishers, the lesson is straightforward. Document the works at issue, their market paths, and the ways model outputs might act as substitutes. For AI companies, the risks are procedural as much as doctrinal. Once a motion to dismiss fails, the record expands, and with it, the odds that a court finds at least one viable theory to send to a jury.
What to watch next in the AI Litigation Tracker
Expect more bids to certify narrow questions for interlocutory appeal, as in the Kadrey matter described by McKool Smith. Watch whether courts in the SDNY multi-district proceedings shut the door on lingering discovery, or allow more targeted requests to clean up the record. Track whether the Udio court converts the “rolling cypher” debate into a full DMCA fight, or treats it as a contract or access skirmish and moves on.
McKool Smith’s AI Litigation Tracker is useful because it connects these dots across courts and industries. It captures the shift from fast exits to evidence-heavy showdowns, and it flags where appeals may jump the line. For anyone building, licensing, or investing in media-facing models, that’s the map to keep open as the next round of rulings lands. For more on this, see nytimes.com.