In 2026, the conversation around AI in IP and R&D shifted from “can we trust it” to “can we connect it.” The Model Context Protocol (MCP) is the open standard making that connection possible, letting AI assistants and agents work directly with authoritative patent, scientific, and market data instead of guessing from training data. Every major model provider now supports it, and IP and R&D organizations are moving quickly from experimentation to adoption.

On Thursday, October 29, at 12 PM ET, this panel brings together IP, R&D, and AI practitioners for a practical briefing on what MCPs are, why they matter, and what to consider before connecting AI systems to your organization’s research and IP workflows. Attendees will leave with a clear understanding of the technology, real integration scenarios, and the questions to ask before deployment.

What we will cover:

• MCP in plain terms: what the protocol does, how it differs from APIs and built-in AI features, and why it has become the standard for connecting AI to external data
• Why it matters for IP and R&D: the shift from AI that generates plausible answers to AI grounded in verifiable patent, literature, and market data
• Integration in practice: how teams are using MCPs today, from prior art and FTO analysis to target discovery, competitive monitoring, and portfolio decisions
• What flows through the pipe: why data quality, provenance, and coverage determine the value of any MCP connection
• What to know before you connect: security, confidentiality, and governance considerations; managing hallucination risk; where human review still belongs in privileged and high-stakes work
• Where this is headed: agents, custom builds, and what data access looks like over the next 12 to 24 months