Every industry is in the midst of digital transformation—and artificial intelligence (AI) has become an integral component. From optimizing manufacturing supply chains to personalizing consumer user experiences, AI-powered capabilities are now a part of everyday business practices.
This AI revolution has brought about a data explosion: 70% of businesses report at least a 25% annual increase in data generation—making AI-powered data processing and analysis capabilities key to managing this burgeoning data.
Yet, generating and analyzing such extensive amounts of data raises user consent and privacy issues, and keeping up with rapidly evolving privacy laws makes the challenge even more complex.
Understanding the impact of AI on data privacy can help you stay ahead of changing consumer attitudes and legal landscapes. That way, you can harness technological advancements while safeguarding customer data and ensuring compliance.
The expanding role of AI
AI-powered technologies help businesses manage and analyze data, personalize customer experiences, and even stay abreast of evolving privacy regulations.
Systems utilizing AI algorithms can process vast amounts of data at speeds far beyond human ability. They can automatically organize data using predefined criteria or learned patterns, accelerating data management and reducing human error. AI can carry out sophisticated analysis, identify patterns, and forecast future trends—helping you make better strategic decisions.
With AI, you can tailor content and services to different users by analyzing customer behaviors. As consumers, we’ve all grown accustomed to AI-powered personalization via content and product recommendations on streaming services and ecommerce platforms, and these practices are extending across all industries and user experiences.
There are also AI tools to help you manage compliance with privacy regulations. For instance:
- Checking regulations as they evolve and notifying stakeholders of updates.
- Monitoring data usage and access across your organization and detecting any anomalies that indicate a breach or misuse.
- Identifying potential risk factors and predicting where compliance issues might occur.
But there are two sides to every coin. Though AI can further your compliance efforts, it can also create new challenges around privacy and security.
Global data privacy legislation in the AI age
Though AI-powered automation and analysis can help you monitor regulations and compliance, how AI-powered systems use data also complicates compliance.
The last decade has seen a global effort to strengthen data privacy laws. 71% of countries have data privacy legislation—but businesses are struggling with data security challenges. For example, only 34% of organizations have conducted comprehensive data mapping and truly understand data practices.
Data legislation passed in recent years affects how you’re required to handle customer data, which has implications for any AI initiatives you introduce.
Many view the EU’s General Data Protection Regulation (GDPR) law as the most stringent data privacy regulation. Several aspects are particularly relevant to AI and, in some ways, make using AI more challenging:
- Transparency: Businesses must communicate to customers what personal data they collect, why, and how it’s processed.
- Purpose limitation: Personal data should only be collected for specified, explicit, and legitimate purposes and not used for another, incompatible purpose.
- Data minimization: Businesses should only gather data necessary for the stated purpose.
- Storage limitation: Data should not be stored longer than necessary for its stated purpose.
Many states have implemented—or plan to pass—customer data privacy legislation in the US. For example, the California Consumer Privacy Rights Act (CCPA) gives people the right to know what data companies collect about them and enables them to object to data sales. Operating internationally or across different states requires businesses to comply with various regulations—adding another layer of complexity.
In addition, regions are racing to protect consumers from the threats and challenges that AI presents. The EU is leading the effort, already securing approval from the European Parliament around a specific AI regulatory framework that imposes specific obligations on providers of high-risk AI systems and could ban certain AI-powered applications.
At an international level, the United Nations has formed an advisory body on AI that proposes regulations for dealing with AI. And the US issued an Executive Order that advances a coordinated approach toward the safe and responsible development of AI.
As regulations inch closer, recommendations—like urging developers to create models that minimize data usage and respect user privacy—still provide best practices for developing and using AI systems.
AI data privacy compliance challenges
AI-powered technology's actual and potential benefits are immense, but they don’t come without complex challenges to data privacy compliance.
First, privacy regulations compel you to protect personally identifiable information (PII)—like someone’s name, address, phone number, or ID number.
The second challenge relates to purpose limitation, specifically the disclosure provided to consumers regarding the purpose(s) for data processing and the consent obtained. Adopting AI-powered systems might create uses of data for new purposes, e.g., additional analyses or applications not covered in the original disclosure and consent agreement. Maintaining visibility into AI systems is essential to ensure your disclosures are accurate and appropriate to your data uses.
Additionally, the data minimization principle dictates that only the data needed for the stated purpose be collected and processed. This means that businesses must train and configure AI systems to use only what they need for the stated purpose, and controls should be put in place to adhere to such requirements.
Another consideration is potential AI bias. AI bias occurs because the data sets upon which the algorithms are built and trained are influenced by humans—who are invariably biased. As such, biased AI systems might make unfair decisions to particular groups of people—for example, in mortgage approval or college admissions processes. Regulatory and technology organizations are proactively working to see how these potential biases can be mitigated and eliminated.
Several well-known companies have been reprimanded for failing to comply with privacy regulations. For example, Cambridge Analytica used personal data from millions of Meta users with AI algorithms for political purposes. They were fined for breaching data protection law because they used data for political advertising without consent. Meta was also fined in 2023 under the GDPR law related to transferring EU users’ data to the US.
That’s why it’s increasingly critical that businesses pay attention and respond to new AI regulations as they evolve.
AI, consumer rights, and privacy concerns
Today’s consumers are becoming more concerned about how their data is used—especially when the mainstream news coverage is sprinkled with high-profile data privacy cases. According to Salesforce data, most consumers feel like they’ve lost control of how their personal information is used, and they want more transparency about how companies process data.
On the other hand, many consumers favor personalization over privacy. They’re happy to share data in exchange for a better experience. Leading businesses strike a balance between using AI for business objectives, developing better customer experiences, and protecting customers’ privacy rights.
To find that balance, it’s essential to be transparent about how AI systems use customer data, get informed consent from customers, and give customers control.
- Transparency: Keeping consumers informed about how their data is processed, stored, and potentially shared means presenting information in a way that is accessible to the average user.
- Informed consent: As stated, informed consent can be challenging because AI applications can evolve, potentially using data in ways not initially anticipated. Avoid treating consent as a one-time checkbox—it’s an ongoing engagement process between the AI system and the consumer.
- Customer control: Giving consumers control over their data means empowering them to opt in or out of data collection and processing. Control also involves a consumer’s ability to access their data, correct it, and request its deletion—particularly important in AI systems, where inaccurate data can lead to erroneous outcomes. Making control granular enables consumers to make choices about different types of data and the various purposes for which it's used.
Untangling customer data privacy
Protecting customer data privacy is complex—but it’s also essential. Not complying with privacy laws can lead to fines, a breakdown in customer trust, and business disruption.
But don’t let these complexities and challenges dissuade you from pursuing your AI initiatives. Instead, let us help you fuel your digital transformation while adhering to customer data privacy requirements.
To help you better understand how to comply with international privacy regulations, check out our “Guide to Global Customer Data Privacy.”
Packed with in-depth insights and actionable guidance, it’s a powerful resource for anyone eager to enhance their understanding of the ever-evolving data privacy landscape.
Dig deeper into the intricacies of AI and data privacy. Get your guide.
