Can patent teams trust agentic AI? Why reliable data matters
Speakers
Using a novelty search workflow as a real-world example, our panel will examine how agentic AI can help patent professionals move from invention disclosure to informed decision-making more efficiently. We will discuss how AI can assist in understanding technical concepts, gathering relevant information, identifying potentially similar inventions and organizing findings for review, while ensuring final judgment remains firmly in the hands of patent experts.
In the session, we will answer:
- How can patent teams determine where agentic AI delivers meaningful value?
- What role does connected patent data play in producing useful outputs?
- When does a workflow benefit from an AI agent versus direct access to data through an MCP?
- How should organizations validate AI-assisted novelty and prior art findings?
- Which stages of the patent process still require expert review and decision-making?
- What practical safeguards help maintain quality, consistency and confidence in AI-supported workflows?
The session will also explore why flexibility matters. Patent workflows vary significantly between organizations, technologies, industries and jurisdictions. As a result, successful AI adoption depends on solutions that can adapt to existing processes rather than forcing teams into new ways of working. We will discuss how platforms such as IPOne are being developed to support this reality by bringing together patent intelligence, workflow context, AI capabilities and expert oversight in a more connected environment.
