Artificial intelligence is creating new opportunities for corporate IP teams and outside counsel to automate research, analyze portfolios, identify risks, and collaborate more efficiently. But even the most sophisticated AI cannot reliably compensate for incomplete, inconsistent, or outdated information. When general-purpose large language models are used for IP analysis without a curated data foundation, the result can be missed relationships, unreliable conclusions, and confident-sounding hallucinations.

This webinar on Tuesday, September 15, at 12 PM ET, will examine how corporate IP teams, law firms, and data providers can work together to build more reliable and scalable AI-powered workflows. Drawing upon corporate, outside counsel, and data-infrastructure perspectives, panelists will discuss:

• How curated and normalized datasets can improve the accuracy and consistency of AI-assisted work;
• How organizations can connect general-purpose models such as ChatGPT and Claude with purpose-built IP data;
• Which tools and workflows corporate IP teams may choose to build internally—and how outside counsel can support and integrate with those systems; and
• The governance, quality-control, and human-review practices necessary to reduce hallucinations and maintain confidence in the resulting analysis.

Attendees will gain a clearer understanding of the data infrastructure required to move from generic AI experimentation to dependable IP workflows built on specifically curated industry data. They will also receive practical guidance for using AI and curated data to reduce duplicative work, improve in-house and outside counsel collaboration, and support faster, better-informed decisions without surrendering experienced professional judgment.