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The rise of generative AI has brought data privacy to the forefront of global conversations. These AI models, trained on vast amounts of internet-scraped data, have ignited concerns about consent and transparency. Questions are being asked about whether individuals and organizations should be informed if their data is being used in this way.

It’s clear our current privacy laws are struggling to keep pace with the evolution of technology. However, while generative AI adds complexity, it doesn’t eclipse existing data privacy concerns that we’re already grappling with. In fact, the most pressing challenges still stem from widespread data breaches and apps that exploit personal data for profit.

What GenAI has done though is introduce new dimensions to these existing challenges. For example, we’re seeing a rise in AI-driven SaaS tools that collect and process user data. Technology vendors are increasingly offering opt-out options for their AI features to safeguard user privacy, but this underscores a larger need for more clarity around how data is being used.

The path forward demands a balance of adaptability, transparency, and regulation. Organizations must take proactive steps to safeguard privacy, including clear communication around data practices and investment in privacy-preserving technologies. Regulators must also work closely with the technology industry to craft policies that protect individuals without hindering progress.