Data Privacy Enforcement Tracker

Data has become one of an organization’s most valuable resources, a fact which has become recently intensified with the continued rise of artificial intelligence. As such, the data management lifecycle is a critical framework for organizations to handle data in compliance with legal requirements and industry best practices. This article examines the four key stages of the data lifecycle: client engagement, data collection, data use, and data retention.

Client Engagement

The foundation of legally sound data management begins with proper client engagement, which is substantially different in business-to-business (B2B) and business-to-consumer (B2C) contexts.

In a B2B context, the signed agreement between the two organizations should contemplate, at a minimum, the following issues: what data will be collected, how and where the data will be stored, how will the data be used, data breach obligations, data retention policies, and representations specifically relating to data.

Conversely, in a B2C context, organizations must establish clear terms of service and privacy policies that explicitly outline how data will be collected, used, and retained. Further, in certain situations, this stage may require obtaining consent from the consumer, particularly in jurisdictions governed by comprehensive privacy regulations like Texas or California.

Data Collection

During the data collection phase, organizations face significant legal obligations to ensure data is gathered in accordance with the terms set forth in the client engagement phase. As such, the collection must match the agreement (in the B2B context) and/or the terms of service / the privacy policy (in the B2C context), while ensuring compliance with any updates. Further, organizations must implement appropriate technical and organizational measures to: protect data during collection, including encryption and secure transmission protocols, track consents, and track data lineage. Failure to implement these safeguards can cause an entire dataset to become unusable if a small subset becomes tainted or otherwise not legally usable.

Data Use

The data use phase presents complex legal considerations regarding how organizations process and share collected information. Organizations must ensure that data usage aligns with the originally stated purposes communicated during client engagement. Access controls and data processing agreements become crucial when sharing data with third-party service providers. To that end, organizations must maintain detailed records of data processing activities, such as sharing the data or using the data to for other purposes (e.g., training an AI model). Further, maintaining accuracy in marketing materials relating to data and AI has recently emerged as a new area of focus for privacy regulators.

Data Retention

The final phase, data retention, demands careful attention to legal requirements regarding storage duration and disposal methods. Organizations must establish and follow retention schedules that balance business needs with legal obligations. Many privacy laws require organizations to delete or anonymize personal data once it is no longer necessary for the original purpose of collection. Further, agreements often set forth requirements for data retention and deletion standards. As such, implementing secure deletion protocols and maintaining documentation of destruction activities are essential components of compliance. However, organizations should also consider legal hold requirements that may supersede standard retention periods during litigation or regulatory investigations.

Final Thoughts

Proper management of these four phases requires organizations to maintain comprehensive data governance policies and regularly update their practices to align with evolving legal and contractual requirements. Success in navigating the data management lifecycle depends on close collaboration between legal, IT, and business teams to ensure compliance while meeting operational objectives.  If implemented correctly, the proposed data management during the four aforementioned phases will result in substantially lower legal and operational risk.