Published Articles
AI, IP, governance, and enterprise-risk signals translated into practical review questions for technology counsel.
Published articles
Coverage lanes
Signals reviewed
Source items screened before articles are drafted.Two recent patent signals point to a practical filing control: document the human conception story separately from the technical implementation story. AI use alone should not be allowed to answer either question.
The European Commission’s GPAI training-content template gives AI procurement and counsel teams a concrete document to request from vendors. Treat it as a transparency artifact—not proof of non-infringement—and build review gates around what it says, omits, and updates.
CourtListener metadata shows a new S.D.N.Y. copyright class complaint against Meta, while the OpenAI copyright docket continues to reflect amended-complaint activity. The operating takeaway is preservation readiness, not outcome prediction.
OpenSSF’s agentic-AI security discussion makes the practical risk visible: agents connect models, tools, data, and open-source dependencies. Counsel should turn that into review gates before agent workflows become embedded in developer and business operations.
Recent metadata from Bartz, Kadrey, and UMG dockets shows AI copyright litigation moving through class-certification, expert, discovery, and Copyright Office-report arguments. Counsel should treat training-data records as litigation-readiness infrastructure now, not a cleanup project after a merits ruling.
A nonprecedential Federal Circuit § 101 affirmance against mobile-notification claims is a practical reminder for AI/software patent intake: do not stop at the workflow. Capture the concrete technical improvement, implementation details, and fallback positions before filing.
Enterprise AI access is expanding while production conversion, agent governance and vendor-market stability remain uneven. Counsel should use that gap to tighten AI contract review before pilots become dependencies.
Court metadata reflects that Dow Jones and NYP’s second amended complaint against Perplexity was entered on Jan. 28, 2025, with listed appendices. Treat it as a prompt to tighten evidence trails for AI search, summarization, and retrieval products—not as a merits signal.
The Federal Circuit’s NantWorks opinion is a practical prompt to re-test AI-adjacent software claims that depend on selecting, filtering, or rendering information. The drafting question is whether the claim shows a technical improvement, not just a useful data workflow on conventional components.
Recent CourtListener docket activity shows AI copyright disputes continuing across major defendants and procedural tracks. Counsel should use the signal to test data provenance, vendor allocation, product claims, and preservation readiness before discovery or diligence pressure arrives.
A pending DTSA preliminary-injunction fight in X.AI Corp. v. Li is a practical prompt to test whether employee-departure controls can generate usable evidence quickly. The immediate lesson is procedural: access records, confidentiality designations, and exit documentation need to be ready before suspected misuse occurs.
Docket materials surfaced in Concord v. Anthropic, Getty v. Stability AI, and the Google generative-AI copyright litigation point to a practical shift: counsel should be ready to prove data provenance, prompt/output testing, internal decisions, and customer or vendor representations before the merits are settled.