Privacy Unplugged: Tackling the Challenges of Agentic AI in Business

At SXSW this year, Signal President Meredith Whittaker warned that agentic AI’s need for vast amounts of personal data poses severe privacy and security risks. As global AI regulations intensify, businesses are facing increasing pressure to ensure their use of the technology is both ethical and compliant with legal requirements.

Agentic AI is a leap beyond generative AI, which relies on human instructions to perform specific tasks. Instead, agentic AI operates autonomously, making decisions on behalf of users or businesses. For example, a company might use agentic AI to analyze a customer’s interactions across multiple touchpoints — such as social media, website visits, and support queries — and automatically personalize the experience, offering discounts or adjusting shipping without requiring human intervention.

While generative AI responds to user input, Agentic AI understands the context and goals, enabling it to act independently and achieve outcomes. This autonomy makes agentic AI more efficient and effective, but it also raises concerns about privacy and security, particularly regarding the use of data and decision-making processes.

So, how can businesses responsibly navigate these challenges? Let’s explore.

The Privacy Risks

At the heart of the privacy concerns surrounding agentic AI is the issue of trust. For AI to be trusted, especially when it makes autonomous decisions, it must operate transparently, ethically, and in full compliance with privacy laws. Yet, as agentic AI evolves, its decision-making process is often opaque, with minimal human oversight, complicating efforts to meet privacy obligations.

Agentic AI systems require vast amounts of personal data to function effectively. The more data these systems have, the more accurate their decisions become. However, the data collection process becomes murkier when AI operates autonomously. Often, consent from individuals whose data is used is not clearly obtained, leaving consumers unaware of how their personal information is being utilized or, in some cases, whether it’s being used without their consent. This lack of transparency creates significant privacy concerns.

Additionally, the training data used by agentic AI can introduce biases. If the data sets are flawed or unrepresentative, AI systems can perpetuate or even amplify existing biases, leading to unfair or discriminatory decisions. This could result in privacy violations, particularly if an AI system makes decisions such as denying a loan or issuing a medical recommendation based on biased data.

Data storage and retention further complicate privacy risks. Because agentic AI relies on historical data—much of it sensitive or personally identifiable—businesses must ensure compliance with data protection laws. However, many organizations struggle to track vast data sets, particularly when the data is repurposed for uses beyond the original consent. This increases the risk of non-compliance and potential data breaches.

One of the most significant privacy risks associated with agentic AI is its ability to make automated decisions with substantial real-world consequences. For example, an AI system might independently decide to reject a loan application or deny a refund without any human review. The lack of oversight in such decisions can lead to errors, accountability issues, and potential breaches of consumer rights. Privacy laws, such as the GDPR, limit automated decision-making, especially when it has legal or significant effects on individuals, requiring businesses to provide mechanisms for consumers to contest or appeal these decisions.

Navigating Legal Compliance

As businesses adopt agentic AI, understanding the regulatory landscape is crucial. While AI-specific laws are still developing, existing frameworks such as the EU’s GDPR and various U.S. state laws provide essential guidelines.

Under the GDPR, for instance, businesses must ensure that they have a valid legal basis for using personal data in automated decision-making processes. Article 22 of the GDPR prohibits decisions based solely on automated processing unless there is explicit consent or a clearly defined legal basis. Businesses using agentic AI must be able to justify their data usage under one of the following legal grounds: consent, legitimate interest, or contractual necessity.

Additionally, the GDPR requires companies to conduct a Data Protection Impact Assessment (DPIA) when deploying technologies that could impact privacy rights, particularly when those systems make autonomous decisions. A DPIA helps businesses identify risks and outline measures to mitigate potential harm, such as anonymizing data, minimizing data collection, and ensuring transparency in AI decision-making.

Transparency is a core element of data protection laws globally. Consumers must be informed about how their data is collected, processed, and used, particularly when AI systems are involved. Businesses must ensure they provide clear, timely notifications to customers when interacting with AI systems, helping them understand the role AI plays in their experience. This transparency not only fosters consumer trust but also ensures compliance with legal requirements for disclosure, particularly regarding the logic behind automated decisions.

Moving Forward with Trust and Compliance

To manage the privacy risks associated with agentic AI, businesses must take proactive steps to ensure legal compliance and build customer trust. Human oversight remains essential, especially for decisions with significant consequences. While agentic AI can operate autonomously, businesses should establish review processes to monitor AI decisions and intervene when necessary, ensuring that the system’s actions align with ethical and legal standards.

Businesses should continuously evaluate their data management practices. The data used to train AI must be relevant, accurate, and unbiased. Additionally, companies must implement robust systems for obtaining and tracking explicit consent from individuals whose data is being used by AI. These systems should be transparent, user-friendly, and capable of handling requests for the withdrawal of consent.

They must also provide consumers with the ability to opt out of automated decision-making processes. In line with GDPR and other data protection laws, companies should offer individuals the option to challenge AI-driven decisions, particularly when those decisions have significant personal or legal consequences. Providing an alternative human-driven process for resolution helps businesses comply with regulations while maintaining a positive customer experience.

Best Practices for Managing Consent with AI

Despite the risks, agentic AI offers immense benefits. It can improve customer experience, streamline business processes, and drive innovation. However, businesses must take the following practical steps to ensure responsible and ethical use of agentic AI, particularly when it comes to managing data consent:

 ● Establish Clear Consent Processes: Develop a streamlined system for obtaining, managing, and tracking consent effectively. This ensures that data collection is transparent and compliant, mainly when AI is used for decision-making.

●  Limit Data Collection: Adhere to the principle of data minimization by gathering only what is necessary for specific tasks. Reducing excess data helps mitigate the risk of breaches and improves compliance, while anonymizing data offers an additional layer of protection.

●  Provide Opt-Out Options and Alternatives: Allow individuals to opt out of automated decision-making, particularly for decisions with significant consequences. Offering an alternative human-driven process for appeals or queries fosters transparency and protects consumer rights.

● Implement Oversight on AI Decisions: While AI can act autonomously, human oversight is crucial for ensuring that high-impact decisions align with ethical guidelines. Regular reviews and a structured process for addressing disputes are vital for maintaining accountability.

Agentic AI is poised to reshape the future of customer interactions, decision-making, and business operations. But with this power comes the responsibility to navigate complex privacy risks. As regulation continues to evolve, businesses must remain vigilant and proactive in adapting to new laws and best practices. With these privacy-centric strategies, companies can go beyond compliance to fostering trust with customers, a key strategic advantage in the global business landscape.