Mason Clutter is a Partner and Privacy Lead at Frost Brown Todd Attorneys, previously serving as Chief Privacy Officer for the US Department of Homeland Security. Mason’s practice is at the intersection of privacy, security, and technology. She works with clients to operationalize privacy and security, helping them achieve their goals and build and maintain trust with their clients.

In this episode…

Companies are facing new challenges trying to build privacy programs that keep up with evolving privacy laws and new AI tools. Laws, like Maryland’s new privacy law, are adding pressure with strict data minimization requirements and expanded protections for sensitive and children’s data. These shifts are driving companies to reconsider how and when privacy is built into operations. So, how can companies effectively design privacy programs that address regulatory, operational, and AI-driven risks? 

Companies can start by embedding privacy and security measures into their products and services from the start. AI adds another layer of complexity. While organizations are trying to use AI for efficiency, confidential or personal information is often entered into AI tools without knowing how it will be used or where it will go. Vague third-party vendor contract terms and downstream data sharing compound the risk. Staying compliant means understanding each AI use case, reviewing vendor contracts closely, and choosing AI tools that reflect a company’s risk tolerance and privacy and security practices.

In this episode of She Said Privacy/He Said Security, Jodi and Justin Daniels chat with Mason Clutter, Partner and Privacy Lead at Frost Brown Todd Attorneys, about how companies can navigate complex privacy, security, and AI challenges. Mason shares practical insights on navigating Maryland’s new privacy law, managing vendor contracts, and downstream AI risks. She explores common privacy misconceptions, including why privacy should not be one-size-fits-all or checkbox compliance exercise. Mason also addresses growing concerns around AI deepfakes and why regulation alone is not enough without broader public education.