Generative AI for Your Privacy Office

Privacy teams are under pressure to review complex documentation, assess data-sharing proposals and support innovation without compromising rigor. This session will show how generative artificial intelligence can help privacy professionals work more effectively across key parts of that workflow, starting with building a clearer understanding of core privacy terminology, concepts, and the components of modern risk assessments. It will then explore how these tools can support the interpretation of complex artifacts such as risk assessment reports and de-identification documentation, helping users extract insights, clarify assumptions and better understand the implications of results. Building on this understanding, the session will demonstrate how generative AI can assist in reviewing and assessing data-sharing proposals and privacy documentation, and guide risk management decisions to ensure privacy-preserving data use. Drawing on practical experience and examples of purpose-built AI tools, the speakers will discuss where these tools can add real value, where human judgment still matters, and how companies can use generative AI to strengthen quality, consistency and efficiency in privacy work.

What you will learn:

• How generative AI can help build a working understanding of key privacy concepts, terminology and components of modern risk assessments.

• How to interpret and critically assess re-identification risk assessment reports and de-identification documentation using generative AI.

• How generative AI can support the review and improvement of privacy documents used in data access and data-sharing initiatives.

• What strong de-identification documentation and related privacy materials should include.

• Practical ways to use these tools to support responsible innovation while maintaining trust.