What every business leader should know about AI data privacy

By: Jhoni Jackson, Edited by: Gabriela Pérez Jordán

Published: March 19, 2025

Artificial intelligence (AI) is dramatically changing the business landscape in several beneficial ways — but AI has disadvantages too. For business leaders integrating these new technologies, AI privacy concerns should be a top priority.

Explore what business leaders should know about the security risks inherent to AI systems and how to best avoid them.

What is AI data privacy?

AI data privacy refers to safeguarding personal data, proprietary information, and other sensitive material when using AI systems.

Data collection is integral to artificial intelligence. For example, generative AI systems like ChatGPT function by learning from information that's publicly available on the internet or supplied by third parties, such as Reddit. These data arsenals are also bolstered by input from system trainers and researchers.

Additionally, generative AI systems learn from data supplied by everyday users. And therein lies the privacy concern: Is the data users supply to AI safe? If not properly secured, third parties — including cybercriminals — can access this data without consent.

Businesses have an obligation to protect company and client information, so leaders must understand how AI works and the risks involved. Employees should also learn the fundamentals of AI and be vigilant about security threats. The more business leaders and their teams know about AI privacy concerns, the better they can protect their data and maintain ethical use of AI.

What business leaders need to know about AI privacy concerns

Data security varies across AI platforms. However, there are several widely applicable AI privacy concerns every business leader should know.

1. Data leaks

An AI data leak occurs when sensitive information is exposed to outside parties. This can result from system issues, human error, or cyberattacks.

2. Cyberattacks

A cyberattack is any intentional and malicious attempt to disrupt software, hardware, or other computer infrastructure. Artificial intelligence systems are susceptible to cyberattacks, as are individual users, their computers, and the networks their computers are connected to.

For example, phishing is a cyberattack involving fraudulent virtual communication, such as email or social media scams. It can result in issues such as identity theft or the infection of a computer or an entire network of computers with malware. Bad actors can use personal data obtained from AI systems to enable these attacks.

Data poisoning, another type of cyberattack, involves intentionally corrupting data within an AI system to cause inaccurate or inappropriate outputs.

Note that there are many more kinds of cyberattacks; these are only two examples. Additionally, cyberattacks evolve alongside technology, and new varieties may surface in the future.

3. Unauthorized third-party access to data

Artificial intelligence systems may share data with third parties. You can find third-party access information for any AI platform through its privacy policy. However, some of these privacy policies aren't explicit about the identity of third parties and how they may use your data.

How can leaders balance success with AI security?

The potential for AI to enhance and optimize businesses is profound: It can help optimize processes, enhance your leadership, and evaluate data for more informed decision-making.

However, these advantages come with risks. Below you'll find measures your company can take to minimize common AI privacy issues.

Evaluate the AI platform's privacy policy

When choosing which AI systems are safe for company purposes, read the system's privacy policy. If the policy isn't clear on how data is used, the system may not be appropriate for business use.

Never input sensitive information

Regardless of the perceived strength of an AI system's data security, users should never input sensitive information, such as client data, proprietary company information, and financial details, into any AI system.

Opt out of AI training

Machine-learning systems are trained by data, including user data. However, many systems allow users to exclude their data from use for AI training purposes. The location of an opt-out feature varies by system, but most are in the profile or settings sections.

Use strong passwords and change them regularly

Current best practices for a strong password include combining numbers, symbols, and uppercase and lowercase letters. You should never use personally identifiable information in your password (e.g., your birthday or spouse's name). Passwords should be changed every few months. However, if a breach is suspected, change all passwords immediately.

Adjust your browser settings

You can change your browser settings to stop third-party tracking by switching to a "do not track" setting. Note that this does not prevent an AI system or website from collecting information.

Consider using a VPN

A virtual private network (VPN) provides security through encrypted, private internet use. This can be a helpful barrier in protecting data from security risks when using AI on an internet browser.

Keep AI software and hardware up to date

Updates to AI software and any other programs your company uses could include privacy upgrades. Keep your systems up to date at all times. After these updates, check your settings (e.g., opting out of third-party tracking) to ensure no changes were made.

Consider hiring a specialist or an AI team

If you are unsure about AI security, consider hiring a specialist to evaluate company use. An AI expert can check for vulnerabilities in your security measures and suggest further action. Should your company implement AI on a larger scale, including developing its own AI systems, consider assembling an in-house AI team.

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