(Updated on 26th May 2025)

The US and Europe have increased scrutiny of AI development. For as many regulations and laws as there are that encourage innovation, there are those that monitor privacy risks, such as the GDPR. These developments are part of a broader trend towards more stringent AI regulations globally, aiming to balance technological advancements with ethical considerations and privacy protection.

In-house legal practices looking to take advantage of AI’s promising legal technology must be aware of these regulations and their responsibilities when operating AI. Likewise, a chief legal officer and other leadership need an awareness of potential privacy issues and how to look for secure, compliant AI technology. 

So, let’s learn how you can ensure secure usage of AI in your organization while staying compliant with global regulations. 

Why artificial intelligence raises privacy concerns

As artificial intelligence continues to evolve, so too do the questions about how it handles personal data. The technology's growing influence has raised alarm bells about how much of our private lives it sees—and what’s being done with that information. Below are five key reasons why AI raises serious privacy concerns.

#1 Data misuse and lack of consent

The 2023 Pew Research Center survey found that 72% of Americans are concerned about how companies collect and use their personal data. Another study found that 70% of Europeans are also concerned about how their data is used. 

The core of AI privacy issues often begins with data misuse. AI systems need vast amounts of data to learn and improve. However, the way AI companies collect this data is sometimes dubious. Many times, companies gather personal information without clear consent or proper understanding from the users.

It's like someone is secretly taking notes about your life—where you shop, what you like, your online searches—and using it to make a profile about you. This is not just a breach of trust but a significant privacy invasion. People should have the right to know and choose what information about them is being collected.

#2 Enhanced surveillance capabilities

By 2025, the global facial recognition market is projected to reach $9.8 billion. This AI recognition software is used to mark and track in ways a human security officer never could. 

Technologies like facial recognition and gait analysis make it easy to constantly monitor individuals, and this isn't limited to high-security areas. It’s also happening in everyday spaces like shopping malls and streets.

Governments or corporations can easily misuse this level of surveillance to track and control individuals, posing a stark threat to personal freedom and privacy.

#3 Profiling and discrimination

Here's a bitter truth—AI can be biased. When AI systems are fed data that reflects societal biases, they can inadvertently perpetuate discrimination. This could manifest in various ways, like job recruitment AI favoring a particular gender or race, or credit scoring algorithms unfairly biasing against certain socioeconomic groups.

AI models may use individual data to make biased assessments, which can have real-life negative consequences.

#4 Opacity and lack of control

AI systems can be like black boxes—complex and opaque. The lack of transparency in how these systems work and make decisions is a significant privacy concern.

People are often in the dark about what data about them is being used and how. This lack of understanding and control over personal data is unsettling. Imagine not knowing why you were denied a loan or flagged at an airport, but it all happened because of an AI system’s hidden workings.

#5 Data breaches and security risks

AI systems are not impervious to cybersecurity threats. The more data an AI system holds, the more tantalizing a target it becomes for cyberattacks. Personal data stored in these systems can include sensitive information such as social security numbers, financial records, or health history.

A breach in AI data security could lead to massive privacy violations and identity theft. The risk of such breaches adds an extra layer of concern regarding how data is stored, protected, and used in AI systems.

Key laws and frameworks regulating AI privacy in 2025

These regulations aim to protect individuals' privacy, ensure transparency, and prevent misuse of AI, particularly in high-risk scenarios. Understanding the evolving legal landscape is essential for any organization working with AI tools. 

In the European Union

Firms operating in the European Union or with EU citizens should be aware of both the General Data Protection Regulation (GDPR) and the EU AI Act. 

• The EU AI Act: This is the world's first comprehensive AI regulation. It aims to ensure trustworthy AI by classifying software by risk level. The act enforces strict compliance for high-risk applications and bans some applications for use in the EU. 
• General Data Protection Regulation (GDPR): This regulation governs the collection, processing, and storage of personal data in the EU. It imposes strict requirements on how legal firms and their tools manage sensitive information, and there are penalties for non-compliance. 

In the United States

There are no federal regulations or laws in the United States as of early 2025. Individual states have passed regulations that apply to companies operating within their state lines. For example, in mid-2024, Colorado passed the Colorado AI Act, which aims to protect individual privacy and limit bias and discrimination in high-risk AI systems.

So far, policymakers generally seek to provide reasonable protection for sensitive data. AI algorithms that deal especially with delicate data or emerging technologies, such as biometric readings, are held to higher standards. 

Other laws, like the California Consumer Privacy Act (CCPA), are being amended to specifically govern what AI systems can disclose. Legal teams can expect a changing regulatory landscape in the coming years. 

This is going to be a bumpy ride, but it is one that most organizations will navigate together. The guidelines below will help you remain compliant in an AI-powered future. 

Best practices to mitigate privacy risks associated with AI

We know regulations like GDPR in Europe and laws like CCPA in California are a big deal for privacy, but we can do more to keep personal data safe in the world of AI.

Let’s look at some good ways to do this.

Also read: How In-House Legal Teams Can Safeguard Company Data and Mitigate Security Risks

#1 Develop a comprehensive AI use policy

The first step is to draft a clear policy that governs the use of AI within the organization. This policy should outline what is permitted and what is not, focusing on ethical use, data protection, and privacy. It should serve as a guideline for all employees to understand the boundaries and expectations when working with AI. This policy should address:

• Data governance: Establishing how data is collected, stored, accessed, and secured for AI purposes
• Model explainability: Ensuring transparency and understandability of how AI models arrive at decisions
• User consent: Obtaining informed and meaningful consent for data collection and use in AI systems
• Risk management: Identifying and mitigating potential privacy risks associated with specific AI projects

Also read: Crafting Effective Generative AI Policies: A Step-by-Step Guide

Also read: ‍Alternative Legal Careers for Lawyers: 20 Realistic Ideas

#2 Conduct privacy impact assessments (PIAs)

PIAs are your best friend here, and they are a critical tool for identifying potential privacy risks associated with AI projects. A PIA involves a detailed legal analysis of how data is collected, processed, stored, and deleted, identifying risks to privacy at each stage. It also requires evaluating the necessity and proportionality of data processing, ensuring that only the minimum amount of data necessary for the project's objectives is used.

By regularly conducting PIAs, you can identify potential privacy issues before they become real problems. Conduct these assessments during the planning stage of any project involving personal data and revisit them regularly as the project evolves.

#3 Ensure transparency and consent

Transparency is key. You must ensure that clear, concise information is provided to users about the AI systems in use, the nature of the data those systems collect, and how they will use the data. Present this information in a user-friendly manner, and avoid technical jargon that obscures understanding. Securing informed consent is equally critical; your customers should have a clear choice regarding their data, including the ability to opt in or opt out of data collection practices.

• Invest in explainable AI (XAI). Leverage XAI techniques to understand how AI models arrive at decisions, increasing transparency and accountability for potential algorithmic bias.
• Communicate openly. Communicate transparently about the use of AI systems, their potential impact, and limitations, while balancing transparency with legitimate business interests.

#4 Implement robust data security measures

Protecting the data that AI systems use is non-negotiable. You must work closely with IT and cybersecurity professionals to ensure that personal data is protected against unauthorized access, disclosure, alteration, and destruction. This includes employing encryption, implementing strong access controls, and regularly updating security protocols to address emerging threats.

Additional considerations:

• Regular security assessments: Engage third-party security experts to conduct penetration testing and vulnerability assessments to identify and address potential weaknesses in your defenses.
• Stay vigilant: Continuously monitor evolving cyber threats and vulnerabilities. Subscribe to security advisories and updates to stay informed and adapt your security measures accordingly.
• Compliance is key: Ensure your data security measures align with relevant data privacy. regulations. Compliance not only minimizes legal risks but also demonstrates your commitment to responsible data handling.

#5 Stay updated on regulations and standards

The regulatory landscape for privacy and AI is constantly changing, with new laws and guidelines emerging as technology evolves. You must remain vigilant and stay informed about current and upcoming privacy laws and regulations at both the international and local levels. Continuous education and adaptability are key, as is the ability to interpret how these regulations apply to your organization's specific use of AI.

Some tips:

• Track legal changes. Monitor global privacy laws and AI regulations.
• Assess impact. Evaluate any new regulations’ effects on AI use.
• Adopt standards. Follow international AI development standards.
• Influence policy. Participate in regulatory discussions.
• Join Legal groups. Engage with Legal networks for insights.
• Use RegTech. Apply technology for compliance tracking.
• Update your programs. Regularly refresh your compliance strategies.
• Promote a compliance culture. Foster organizational awareness and adherence.

#6 Foster a culture of privacy

Promoting a culture that values and respects privacy is perhaps one of the most effective strategies for mitigating privacy risks.

Consider how you can:

• Develop AI literacy programs. Train all the different teams in the organization on responsible AI practices and data privacy regulations, and their roles in upholding data protection principles.
• Promote continuous learning. Encourage ongoing learning and awareness campaigns to keep pace with evolving AI technologies and the legal landscape.
• Foster a privacy-conscious culture. Cultivate a culture where privacy is a shared responsibility and everyone involved in AI projects understands their privacy obligations.

New AI developments and privacy challenges

As AI gets smarter and does more, it's going to handle a lot more personal information. But this could mean more chances for privacy problems. The more AI knows, the more we need to be careful about keeping information safe. From leadership to legal interns, all AI users are responsible for maintaining privacy. 

Enhanced predictive analytics

• Privacy risk: Increasingly accurate AI predictions may infer sensitive personal information without explicit consent, exposing users to privacy breaches.

• Mitigating the risk: Prioritize AI model development that emphasizes data minimization and anonymization. Regularly review and update data protection policies to address the handling of inferred data.

Expansion of AI in decision-making

• Privacy risk: Growing use of AI in decisions affecting individual rights—such as hiring or credit scoring—raises concerns about transparency and accountability.

• Mitigating the risk: Design AI systems to be auditable and compliant with fairness regulations. Establish clear guidelines for AI's role in decision-making, with a strong emphasis on human oversight.

Proliferation of IoT devices

• Privacy risk: The spread of Internet of Things (IoT) devices means more personal data collection at an unprecedented scale and granularity, heightening the risk of unauthorized access and data breaches.

• Mitigating the risk: You should push for robust security standards and privacy-by-design principles in IoT development. Implementing strict access controls and data encryption is crucial to protect the information collected by these devices.

Advances in Natural Language Processing (NLP)

• Privacy risk: Improvements in NLP enable AI to understand and generate human-like text, potentially leading to the misuse of sensitive information or the creation of convincing phishing attempts.

• Mitigating the risk: Developing comprehensive policies on the use of NLP technologies, including guidelines for data handling and user consent, is essential. Regularly train your staff to be able to recognize and protect against AI-generated phishing threats.

Keep AI risks at bay with SpotDraft’s AI Policy Playbook

Understanding laws like GDPR and CCPA and using smart strategies is key to managing privacy risks in AI. As technology keeps advancing, we need to keep up and stay proactive. One big help? Creating an AI for lawyers use policy.

And if you're wondering how to start, SpotDraft’s AI Use Policy Playbook is just what you need. It gives you a head start to create a tailored policy for your organization, ensuring you're well-equipped to tackle privacy risks head-on.

SpotDraft is a compliance ally for legal teams using AI tools. The VerifAI feature can help automate contract reviews for risky clauses, including those related to privacy, ensuring teams don’t miss key obligations or red flags.

See how SpotDraft helps you flag and fix risk-prone clauses before they become legal issues. Request a demo today.