Data privacy risks in the age of AI: What tech companies need to know

AI has quickly become a part of our everyday lives. You can actively seek it out by asking ChatGPT to craft a convincing sick note for your boss, or you may passively encounter it without even realizing your moves are being monitored — those targeted ads don’t just grow on trees you know. 

And no matter how many cookie pop-ups or privacy statement update emails you get, it can still be hard to fully understand how profoundly artificial intelligence is influencing our privacy. That’s why, in the age of AI, technology companies have a responsibility to protect user data from bots and beings alike. 

This practice of protecting personal or sensitive information collected, used, shared, or stored by AI is now referred to as AI Privacy. According to Cisco’s 2024 Consumer Privacy Survey, 78% of consumers recognize the value of AI and expect responsible treatment of their data.

Today’s tech businesses are therefore tasked with using AI in an ethical manner, and planning for and protecting against those who may have ill intent. 

Understanding the high stakes of AI data privacy

Before we delve into the most common AI data privacy risks for tech companies today, it’s important to understand the devastating impact they can have on your business.

Financial losses: Simply put, data breaches and privacy violations can be very costly. On top of regulatory fines, your tech company could face lawsuits, lost business, and expenses related to incident response and recovery.

Reputation damage: A data breach or privacy scandal can negatively impact your company’s reputation and erode customer trust. In today’s world, where consumers are increasingly savvy and concerned about data privacy, tech companies need to prioritize data protection to maintain a positive brand image.

Lawsuits and regulatory penalties: There are numerous laws and regulations governing AI data privacy. If your company fails to comply with these standards, it can result in hefty fines and legal action.

Fortunately, with the right knowledge and risk management strategies, you can begin to protect your company and your customers from the harmful effects of these and other serious threats. 

One of the easiest ways to get started is by using a Risk Profile — this free tool can help technology companies proactively assess risks and refine their security strategies before issues escalate. 

Data privacy risks in the age of AI

AI and privacy risk go hand-in-hand. That’s because AI machine learning systems rely heavily on data — including sensitive personal information — to learn, adapt, and improve previously written code and models. And while this can lead to innovative advancements, it also exposes businesses to significant AI data privacy risks.

Here are the top risks to be mindful of when working with AI as a part of your technology business. 

Unauthorized access 

Unauthorized access refers to a situation in which someone (or some entity) gains access to a company’s customer database by using stolen login credentials. Like back in 2020 when a hacker guessed Trump’s password to his Twitter account, and had access to his personal messages and profile information. Unauthorized access can also occur through phishing emails. These deceptive emails are designed to trick employees into revealing their passwords or exploiting a weakness in the company’s login system.

Data breaches

A data breach is a security incident in which an unauthorized person accesses confidential, sensitive, or protected information. AI tools can make data collection and analysis easier, but it also increases the risk that sensitive information can end up in the wrong hands — and the results can be devastating and costly. IBM’s 2024 Cost of a Data Breach Report, for instance, found that 46% of data breaches involved personally identifiable information (PII), with the average cost of a breach reaching $4.88 million.

See how data breach insurance is one thing that can help. 

Data leakage

Data leakage is the accidental exposure of sensitive data vs. a targeted attack — but it can be just as damaging. For example, in 2018 in Pennsylvania, an error made by a State Department of Education employee accidentally put the personal information of more than 350,000 teachers at risk. 

The incident temporarily enabled anyone logged into the system to access personal information belonging to other users, including teachers, school districts and department staff. This might not have been done with malicious intent, but it doesn’t negate the potential damage. And while those affected were offered free credit monitoring services for one year, it doesn’t mean future issues won’t arise for them. 

Collection of data without consent

Data is being collected all of the time and while the insights might help offer some tech solutions, it doesn’t take away the problem of potential infringement of a person’s privacy. Users are becoming more aware of this, and in turn, expect more autonomy over their own data as well as more transparency regarding data collection. Even so, according to a recent study done by Equancy, 38% of 551 websites analyzed were collecting data without consent. If your company does not comply with best practices, you could be in violation of regulations and become subject to fines or lawsuits. 

Misuse of data without permission

When someone consents to sharing their information, there could still be risk involved if that data is used for purposes beyond those initially disclosed. A 2021 Cisco survey found that many people (around 46%) felt unable to effectively protect their personal data — primarily because they don’t understand how companies will use it. Meanwhile, in a 2023 Pew Research Center survey, 80% of U.S. adults said they were concerned their personal information will be used in ways that were not originally intended.

Bias and discrimination

AI-powered decision-making is imperfect, which is why using it to solve crimes can become problematic when analyzing surveillance videos using facial recognition. But that’s not the only place bias and discrimination can show up. Bias in data can show in many different ways and lead to discrimination, in part because the algorithm draws on limited or outdated data sets around gender, race, color, and personality traits, and perpetuates — even amplifies — existing inequalities. In 2022 researchers from the USC Information Sciences Institute found examples of bias in nearly 40% of supposed “facts” generated by AI programs. 

Unchecked surveillance

Similarly, unchecked surveillance is the use of surveillance technology without adequate regulation or oversight, like with facial recognition. It can violate privacy, civil liberties, and democratic values. At the close of 2024, a report from the Government Accountability Office reviewed the Department of Homeland Security law enforcement agencies’ use of detection and monitoring technologies in public without warrants. It was found that over 20 types of detection, observation, and monitoring technologies were utilized the previous year.

What you should know about compliance

Not only is awareness of privacy law important in order to avoid fines, fees and penalties, it also correlates with consumer confidence. 

Regulations can be set by countries and states. For example, while the U.S. government has yet to implement nationwide AI and data privacy laws, there is the Colorado AI Act, California Consumer Privacy Act, the Texas Data Privacy and Security Act, and the Utah Artificial Intelligence and Policy Act. 

Canada’s PIPEDA (Personal Information Protection and Electronic Documents Act) requires organizations to obtain consent when collecting, using, or disclosing personal information. It also includes specific guidelines for automated decision-making systems and AI transparency.

Regarding AI and the GDPR, there is a “principle of purpose limitation.” This requires companies to have a specific, lawful purpose in mind for any data they collect. The purpose needs to be communicated to users and companies. Further, the data should be deleted once it is no longer needed. And The EU AI Act prohibits some AI uses including the untargeted scraping of facial images from the internet or CCTV for facial recognition databases.

The good news is that tech organizations are taking note — 58% of privacy leaders now rank keeping pace with a changing regulatory landscape as their top priority, according to a recent Gartner privacy-compliance guide.

Mitigating data privacy risks in AI 

Yes, AI is everywhere and you can’t ignore it — especially when you work in tech. But, you can devise AI privacy approaches to help comply with regulations and protect your clients. Here are five ways to get started: 

1. Check your company’s current privacy policies and make necessary adjustments. Once complete, be sure to communicate the changes to your clients. 
2. Conduct quarterly risk assessments — sometimes it can be worthwhile to call in a third party — and address identified vulnerabilities. 
3. Limit data collection by having a defined purpose or intent for the information you gather and delete the data once you are no longer utilizing it. 
4. Seek, confirm and reconfirm consent as often as needed to ensure clients are aware of the data they are sharing. 
5. Follow security best practices and provide more protection for data from sensitive domains. 
6. Ensure compliance with local regulatory requirements and monitor cross-border data transfers for potential privacy and compliance gaps.

The benefits of proactive risk management 

Proactive risk management keeps your tech business secure, compliant, and financially stable. With an effective risk management strategy, you can identify threats before they occur, prioritize risks, and put the right protections in place, helping you avoid downtime, security breaches, and costly fines.

Your tech company will need to commit to making data and privacy adjustments as AI advances. But understanding the risks in front of you now will help you know what to be on the lookout for in the future. 

Not sure what other risks are looming? Don’t wait for a crisis to occur. Start building a proactive risk strategy today with Embroker’s Risk Profile tool — identify your vulnerabilities and get recommended coverages to match in just a few minutes.