In recent years, the emphasis on data privacy has rapidly transitioned beyond mere adherence to rules and is projected to accelerate even more in the imminent future. Unsurprisingly, the Thomson Reuters Risk & Compliance Survey Report identified that 82% of survey participants identified data and cybersecurity concerns as the most significant risk for their organizations. Nonetheless, a recent trend observed by most organizations is a shift from viewing compliance as a box-ticking exercise to a strategic operation.
As data privacy evolves, numerous organizations recognize the necessity to proactively modify their strategies to prepare themselves adequately for the future. Below are five crucial aspects to prepare for the forthcoming advancements in data privacy.
1. Establish a mechanism for staying abreast of new and evolving regulations
While data privacy transcends basic compliance requirements, ensuring adherence to regulations remains paramount to mitigate the risks of fines and reputational harm. The constant evolution and introduction of regulations pose a significant challenge in staying informed. By September 2024, 20 states had enacted consumer data privacy laws with more legislation awaiting approval in several states. Despite the absence of a federal data privacy law in the U.S., the American Privacy Rights Act is currently in the initial legislative phase.
Given the dynamic regulatory landscape, organizations must devise a structured process to monitor all relevant regulations, a task especially arduous for multinational corporations. Considering that compliance applies to the locations of customers, not the company, global enterprises often face compliance across multiple jurisdictions. Increasingly, organizations are embracing artificial intelligence (AI) tools to track regulations efficiently and ensure compliance, thereby saving time and reducing penalties.
2. Emphasize striking a balance between data privacy, analytics, and AI objectives
Research conducted by AI experts at the University of Pennsylvania’s Wharton School revealed a surge in weekly AI usage among employees, rising from 37% in 2023 to 73% in 2024. However, this swift growth in AI adoption has introduced notable data privacy challenges. Key concerns include data transparency gaps, increased vulnerability points, involvement of third-party vendors, and potential regulatory loopholes. Simultaneously, businesses abstaining from AI integration risk falling behind competitors in productivity and customization.
Given that eschewing AI usage is seldom a prudent choice for businesses, a strategic approach is imperative to strike a harmonious synergy between business value and data security. While technology plays a pivotal role, without a balanced strategy, platforms and systems alone cannot surmount the challenges. By establishing processes and a framework to assess risks and benefits, organizations can make informed decisions concerning data privacy. For instance, an enterprise may opt for automation with AI across its operations but refrain from using AI in scenarios involving sensitive employee or customer data.
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3. Explore privacy-preserving machine learning (PPML)
By deploying specific AI and analytics techniques, organizations can mitigate data privacy risks. Many organizations are increasingly adopting PPML, an initiative spearheaded by Microsoft to safeguard data privacy during the training of extensive language models. Microsoft defines the three components of PPML as follows:
- Comprehend: Organizations should engage in threat modeling and attack scrutiny while determining critical properties and assurances. Additionally, leaders must comprehend regulatory requisites.
- Evaluate: To gauge the current state of data privacy, leaders need to quantify vulnerabilities. Subsequently, teams should devise and apply frameworks to assess risks and monitor mitigation success effectively.
- Alleviate: After acquiring a comprehensive understanding of data privacy, teams must develop and implement methodologies to minimize privacy risks. Finally, leaders must ensure full compliance with legal and regulatory standards.
4. Prioritize data minimization
In the past, many businesses tended to retain all, or most, of their data for prolonged periods by default. However, as all stored data must align with compliance standards, numerous organizations have embraced a practice known as data minimization.
Deloitte defines data minimization as the process of assessing necessary information, ensuring its protection and usage, and determining appropriate retention periods. By adopting this careful approach and identifying essential data, organizations can reduce expenses, enhance data accessibility, and bolster compliance. Moreover, securing a smaller dataset demands fewer resources and is less complex.
5. Foster a culture committed to data privacy
Similar to cybersecurity, upholding data privacy should not be the sole responsibility of specific personnel. Instead, organizations must cultivate a culture where every employee acknowledges their accountability for data privacy. Instilling a data privacy culture is a gradual process that necessitates consistent effort from leaders. Initially, leaders must champion the cause, communicate the shift in responsibility, and exemplify a commitment to data privacy.
Given that data privacy hinges on team members adhering to stipulated processes and requirements, organizations must elucidate the significance of data privacy rather than just imposing rules. When employees comprehend the ramifications of non-compliance and the repercussions for both the organization and its stakeholders, they are more likely to comply voluntarily.
Additionally, leaders should gauge adherence to procedures to determine current adherence levels and set benchmarks. By offering incentives, organizations can motivate compliance and underscore its overall significance.
Commence formulating your data privacy strategy
As your team gears up for the future and beyond 2025, it is imperative to pause and align your strategy and aspirations with the industry’s trajectory. Enterprises that anticipate the direction of data privacy trends and take requisite steps to synchronize their objectives with the foreseeable data privacy landscape stand better positioned to derive enhanced business value from data while ensuring compliance.