The focus on data privacy has begun to move rapidly beyond compliance in recent years, and is expected to move even faster in the near future. Unsurprisingly, the Thomson Reuters Risk and Compliance Research Report found that 82% of respondents cited data and cybersecurity concerns as their organization’s top risk. However, most organizations have noticed a recent shift in which organizations are moving from compliance as a “tick the box” task to a strategic function.
With this evolution in data privacy, many organizations are realizing that they need to proactively change their approach for the future. Here are five important considerations to prepare for the future of data privacy.
1. Create a process to stay up to date with new and evolving regulations
Data privacy is more than just compliance, but organizations must first and foremost comply with all regulations. Failure to comply may result in fines and reputational damage. However, regulations are passed and changed all the time, making it very difficult to stay up to date. As of September 2024, 20 states have enacted consumer data privacy laws, and many others have bills pending. Currently, the United States does not have a federal data privacy law, but the U.S. Privacy Rights Act is in its first stages of legislation.
As the data privacy regulatory landscape continues to change, organizations must create processes to manage all relevant regulations, which can be challenging for global enterprises. Global companies are often bound by many different regulations, as organizations need to comply with regulations where their customers are located, not where the company is located. Organizations are increasingly leveraging artificial intelligence (AI) with tools to monitor and ensure compliance with all relevant regulations, saving time and reducing fines.
2. Focus on balancing data privacy with analytics and AI goals
An AI study from the Wharton School of the University of Pennsylvania found that the percentage of employees using AI weekly increased from 37% in 2023 to 73% in 2024. However, this significant and rapid increase in AI adoption has raised significant data privacy concerns. Top concerns include lack of data transparency, new endpoints for vulnerabilities, third-party vendors, and potential regulatory gaps. At the same time, companies that don’t use AI can quickly fall behind their competitors in terms of productivity and personalization.
Not using AI is rarely the right business decision, so organizations must take a strategic approach to balancing business value and data security. Technology is part of the solution, but platforms and systems cannot solve challenges without a balanced approach. By creating processes and frameworks that help organizations evaluate risks and benefits, companies can make smart business decisions regarding data privacy. For example, companies may use AI to implement automation throughout their organization, except for use cases that involve sensitive customer or employee data.
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3. Consider Privacy Preserving Machine Learning (PPML)
By using certain AI and analytics techniques, organizations can reduce data privacy risks. Many organizations are turning to PPML. PPML is an initiative initiated by Microsoft to protect data privacy when training high-volume language models. The three components of PPML defined by Microsoft are:
Understand: Organizations must conduct threat modeling and attack research, identifying characteristics and assurances. Additionally, leaders need to understand regulatory requirements. What to do: To determine the current state of data privacy, leaders need a quantitative understanding of vulnerabilities. Next, the team must develop and apply a framework for monitoring risk and mitigation success. Mitigation: After understanding the data privacy picture, teams must develop and apply techniques to reduce privacy risks. Finally, leaders must meet all legal and compliance regulations.
4. Focus on data minimization
In the past, many companies retained all, or at least most, data by default for long periods of time. However, all stored and stored data must comply with compliance regulations, which is why many organizations employ a strategy called data minimization.
Deloitte defines data minimization as taking steps to determine what information is needed, how it will be protected and used, and how long it will be stored. By taking this careful approach and deciding what data to keep, organizations can reduce costs, make it easier to find the right data, and improve compliance. Additionally, protecting smaller amounts of data is easier and requires fewer resources.
5. Build a culture of data privacy
Like cybersecurity, data privacy is not just the job of certain employees. Instead, organizations need to instill a mindset in which all employees are responsible for data privacy. Building a data privacy culture doesn’t happen overnight or in one meeting. Instead, leaders must take the time to instill values and focus. The first step is for leaders to become champions, commit to a shift in responsibility, and “walk the walk” in terms of data privacy.
Data privacy relies on team members following specified processes and requirements, so organizations need to go beyond just dictating the rules to explaining the importance of data privacy. If employees understand the risks of not following a process and the impact on the organization and its consumers, they are more likely to do so.
Additionally, leaders must measure process adherence to determine current status and then goals. By offering incentives, organizations can then encourage compliance and emphasize the overall importance of compliance.
Start building your data privacy approach today
As your team focuses on planning for 2025 and beyond, now is the time to pause to ensure your approach and goals are aligned with the direction of your industry. Organizations that understand where data privacy is headed and take the necessary steps to align their goals with the future of data privacy will be able to more effectively transform their data into business while ensuring compliance. You can set yourself up to get value.
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