Practical Considerations and Barriers to PET Adoption

Adopting privacy-enhancing technologies (PETs) presents several challenges, including technical complexity, usability issues, and regulatory gaps. These barriers can slow the widespread implementation of PETs and complicate their integration into organizations’ data privacy practices.

Technical complexity is a key barrier to PET adoption. Many PETs, especially those involving advanced cryptographic techniques such as homomorphic encryption or secure multi-party computation, require specialized knowledge and are computationally intensive.¹ For example, differential privacy—used by the U.S. Census Bureau in the 2020 Census—adds noise to data to protect individual privacy.² However, this approach can reduce accuracy, particularly in small communities with limited data.³ The challenge lies in balancing privacy protection with data utility, as introducing too much noise can lead to inaccurate or unrepresentative insights.

Usability issues in PETs are another obstacle. Many PETs are complex to configure and manage, making them less accessible to non-technical users.⁴ Poorly designed interfaces can hinder adoption, as organizations may struggle to implement these technologies correctly.⁵ To overcome this, user-friendly interfaces that abstract the technical complexity of PETs could help organizations deploy these tools more effectively, making privacy protections easier to use without sacrificing security.

Regulatory and standardization gaps also hinder PET adoption. For example, the European Union’s General Data Protection Regulation (GDPR) requires “appropriate technical and organisational measures” to protect personal data but does not specify which PETs ensure compliance.⁶ This lack of clarity can create confusion about which technologies are legally acceptable, especially when jurisdictions interpret privacy laws differently. Developing standardized guidelines for PET usage would provide clearer compliance paths, helping organizations confidently choose the right technologies for their needs while adhering to legal requirements.⁷

Cost constraints are a major hurdle in PET adoption. High implementation costs, ongoing maintenance expenses, and integration complexities make it difficult for organizations to justify investment, particularly when privacy protections do not directly contribute to revenue generation.⁸ Many PETs require specialized infrastructure or technical expertise. Advanced techniques such as homomorphic encryption or secure multi-party computation demand substantial computing resources, driving up costs.⁹ If the return on investment isn’t clear, organizations may deprioritize PET adoption and the data sharing allowed in favor of other pressing technological needs. Having a clear understanding of the value of PET-enabled data sharing can help, as can implementing them in phases.

Operational challenges further complicate PET implementation. Many organizations or government agencies lack the in-house expertise required to deploy and maintain these technologies effectively.¹⁰ Government agencies may struggle with the technical demands of PETs, from configuring privacy-preserving algorithms to ensuring ongoing compliance with evolving regulations and best practices. Without dedicated resources, PETs may become underutilized or misconfigured, reducing their effectiveness. Streamlining PET integration through managed services, a dedicated support staff or team, and a phased approach can help address these operational challenges.

Awareness and expertise gaps—a lack of awareness and understanding of PETs among key stakeholders—present another significant barrier. Many decision makers are unfamiliar with PETs’ functionality, potential integration with existing systems and data lifecycles, and benefits to improving data use and sharing efforts, leading to hesitation around investing.¹¹ Moreover, PETs are often perceived as more complex or resource-intensive than they are, which makes it difficult to appropriately build a strong case for their implementation. In areas where privacy risks or data-sharing efforts are not immediately pressing, organizations and agencies may prioritize more familiar measures, or just default to not sharing the data generally.¹² Adopting PETs also requires cross-functional collaboration, yet expertise is typically confined to specific departments or data-sharing initiatives, such as the census. This can result in fragmented efforts that reduce the overall utility of PETs. Overcoming these gaps with targeted training and knowledge sharing can help integrate PETs more effectively into data-governance strategies.