Artificial Intelligence as a means to manage data on the one hand and privacy protection on the other seem to be diametrically opposed notions. One is used by governments and companies to gather as much information about people as possible, while the other tries to ensure only the required data are being shared and the rest is protected.

Collecting data is now easier than ever because technology is able to link everything together and form a scarily accurate picture of who we are. Then, as one data breach follows another, we see how much both private and public entities actually know about us. It’s only natural that people are at least skeptic about AI when it comes to their data.

Anonymity guaranteed?

Too often, the stream seems to only go one way: your data is being taken, turned over, and used in some obscure way because we don’t have the time to go through user agreements and terms of service. AI helps make that data legible, usable, but mostly also personal.

We may think we’re anonymous on the internet, but more and more, that’s not the case. On the flip-side, companies and public institutions are more responsible than ever to protect their customers’ personal data.

The GDPR was Europe’s answer to this pressing issue and sought to give users more agency over their own information. When it comes to AI, data protection regulations need to enforce transparency of AI systems, the right authorizations, an easy way to opt-out and remove information when requested, and the purpose must be well-defined and limited in scope. GDPR is a big step in the right direction, as companies are already facing consequences for failing to comply. It’s a surefire way to lose your customer’s trust, and it’s near impossible to regain it. Each reported data breach sets a company back, gets stock prices to plummet, so it’s time for companies to look for the best way forward that doesn’t rely on external regulations and compliance to them.

Integrate AI in your data protection strategy

The role of AI in a company’s data management strategy can go beyond collecting and analyzing data. Data management should include privacy and protective strategies in its core rather than having it be a problem of simple compliance. So why not use the tools at your disposal to create a unified strategy that encompasses data management in all its aspects, and ensures you won’t lose customers’ trust, won’t run into compliance issues, and won’t risk serious data breaches? The right system will create a balance between finding new business opportunities and safeguarding data.

There are a few questions you need to ask when considering optimizing your use of AI for a balanced data management strategy. Mainly, who will be affected by it, and in what way? What’s the right level of security, and how can you minimize risk from the earliest point in the process? Are there any biases at risk of sneaking into the way the data is being analyzed?

But mainly, when dealing with AI, the key thing is to be transparent about it. Trust between a company and its customers is a fragile and valuable thing, and transparency is how to maintain it.

If you are interested to learn more, check out the first AI-driven data privacy scanner.