IP Insights webinar series 2026: Commercial/IP - Key considerations in IP licensing

The Licensing Reckoning

The surge in generative AI has collided with traditional intellectual property protections, creating urgent pressure on licensing practices. Courts in the United States are adjudicating whether training large language models on copyrighted books, images, and other works without permission constitutes infringement. Several district courts have allowed claims to proceed, while some summary judgment decisions in 2025 found fair use in certain cases lacking evidence of infringing outputs. Appellate decisions expected in 2026 could set binding precedents, determining if AI firms face widespread liability and thus compelled to negotiate bulk licensing deals with publishers, artists, and other rights holders.

In Europe, the EU AI Act and related frameworks emphasize compliance with copyright opt-outs for text and data mining, prompting consultations on practical implementation of rights reservations. The UK government's AI and copyright consultation, with outcomes anticipated by March 2026, has drawn over 11,000 responses, highlighting tensions between creative industries demanding transparency and licensing revenue and tech firms preferring lighter regulation. These developments could normalize direct licensing markets for training data, shifting power toward content owners.

Beyond AI, broader IP licensing faces turbulence from policy shifts. The USPTO's evolving guidance on patent eligibility, pro-patent leanings at the PTAB, and a new Standard-Essential Patent Working Group signal stronger enforcement of patent rights, including in standards like 5G. This environment encourages more litigation by patent owners seeking injunctions and higher damages, complicating global licensing negotiations where jurisdictions diverge on fair, reasonable, and non-discriminatory terms.

Non-obvious tensions persist: while rights holders push for compensation, high transaction costs in licensing vast datasets could stifle smaller AI innovators and raise consumer prices for AI tools. In life sciences, additional pressures from data transfer restrictions under rules like the US Bulk Data Rule add layers of compliance to licensing deals involving sensitive information.