To stay compliant and maintain trust, CIOs and CISOs need to track the innovations in their data-rich environments. They must also monitor the volume of data these innovations are collecting, processing, and storing.
The evolving regulatory landscape demands an proactive approach to data privacy. Organizations are increasingly aware of the need for strong safeguards, which has increased the pressure on security leaders to stay ahead of regulations that may evolve further.
Beyond non-compliance, data privacy is a significant reputational matter. A survey shows that 86% of Americans consider data privacy a growing concern, highlighting consumers’ heightened awareness of and reliance on their personal data.
In a global context, companies are increasingly dependents on third-party vendors for services, which could introduce additional risks. Even those that traditionally favored in-house solutions are embracing this trend for innovation. This risk of data breaches from third-party vendors, with a 98% of 98% of organizations reporting such incidents, underscores the need for secure oversight.
Choosing the right solutions is crucial, especially with the rise of generative AI. Organizations must balance innovation with data management priorities to stay compliant. This means securing a middle ground in data governance that prevents the administrative burden of compliance while maintaining strong security measures.
Consumer awareness has further compounded the need for better data practices. With AI technologies increasing, consumers are even more highly concerned about data privacy posed by their own information. Addressing these needs requires a focus on data lifecycle management, emphasizing the importance of minimizing data exposure to avoid liability issues.
