AI Data Security: Protecting Sensitive Customer Data in Modern Contact Centers with Thunai

Worried about your data?

Every AI-powered customer interaction processes sensitive information names, financial records, health data, and private conversations. As contact centers shift to autonomous AI agents, the exposure risk grows. 

One weak API token or unverified integration can open the door to massive data leaks across connected systems. The real threat isn’t just hackers, it's invisible gaps in how AI accesses and uses data. 

The solution is built in AI data security. verified access, real-time redaction, compliance monitoring, and controlled intelligence layers like Thunai working alongside enterprise platforms such as Genesys to protect every interaction by design.

AI and Private Data

The link between artificial intelligence and sensitive customer data is the most complex frontier in the history of the modern contact center. Traditionally, service teams have been targets for bad actors because they hold high value data.

In fact, during 2025, deepfake-based attacks increased by 1,500%, moving from simple scams to CEO Doppelgänger attacks where real-time video/audio clones are used to authorize fraudulent transfers.

A digital worker often has access to data that includes personal identifiers, bank records, and health info. However, the shift to AI led interactions has changed the access patterns these systems need.

This wider access pattern means a single point of failure can expose much more data than an old tool. In mid 2025, a breach at one AI bot provider led to a cascading attack that hit over 700 firms, including major tech firms. 

The actors did not have to break into 700 firewalls, they just used a stolen token to gain access to the cloud system, taking data from connected databases across the whole user base. 

This shows a harsh reality, maintaining sturdy AI data security is not just about blocking access, but about verifying the intent of the system.

Old Security Limits

Safety frameworks we built for old tech are not enough for the world of AI. For decades, safety was based on predictable logic: we knew that if a user clicked a button, the system would run a specific line of code. 

Our firewalls and access tools were built to watch these paths. However, AI models do not work on fixed logic, they work on patterns. A bot might give a good answer today, but produce a risky one tomorrow if the prompt is slightly different. This unpredictability makes it difficult for AI data security methods from the past.

Old network tools watch traffic volume and paths. They are blind to the meaning of the talk. A firewall can see a packet moving to an API, but it cannot read that the packet has a bad instruction designed to leak data. 

This lack of semantic insight means that many AI attacks look normal to legacy tools. In fact, prompt injection is now the top threat in the enterprise, yet old defenses still fail to catch them.

In fact now, for enterprise security the AI-BOM (AI Bill of Materials) has become a major requirement. This lack of insight is a major hurdle for any firm trying to grow their tech while monitoring AI data security.

Enterprise Grade CX

As we move toward a world of industrial AI, we are moving toward secure setups that put enterprise safety first. For CX leaders, this means moving away from AI for the sake of AI. We must make sure every project has clear goals and follows strict rules. The days of patching holes with small tools are over. 

We are now in the age of systems safety. This involves a shift left path, where safety is not a final step but is part of every stage, from the data used for training to the agents used in the field. This change is fundamental to maintaining AI data security.

A main part of this shift is safety as code. In 2026, we do not write rules in PDFs, we write them in code that machines can follow. AI Data Security verifies that as our teams grow, the same rules are used everywhere. This automation is needed because manual work cannot handle the volume of data in modern AI. 

By treating safety as part of the system's base, we reduce the drag that often slows down change. This allows our teams to ship new tools faster and with more confidence while keeping a focus on AI data security.

Thunai and Genesys

In the Genesys ecosystem, the platform for many of the world's best contact centers, the need for safety is high. Genesys Cloud is a sturdy system that uses strong encryption. It gives a full set of tools for bots and routing. 

However, as we move into the era of autonomous workers, firms need an extra layer of logic that can link scattered data and act as a brain. This is where Thunai fits. Thunai acts as an intelligence layer that unifies data from transcripts, CRM records, and internal wikis into a single truth called the Thunai Brain. This link is a requirement for AI data security.

The value of Thunai is deep by fixing clashes in data before a bot acts, it reduces hallucinations by 95 percent. This verifies that when a Genesys run agent talks to a customer, it is not just guessing. It is giving answers based on a verified system of intelligence. 

This level of precision is required for firms that handle regulated data. Thunai also helps with data sovereignty by giving on premises setup options. This is a main benefit for sectors like health or government, where data cannot leave the internal network.

Privacy through Redaction

At the heart of any AI Data Security plan is the protection of customer privacy. The best AI is useless if it leaks the data of the people it serves. This is why PII redaction is not just a feature, it is a foundation for trust. Modern tools must find and remove personal data in all forms, including voice, emails, and PDFs. 

Contact center safety must follow the rule to redact early. By removing PII at the point the data comes in, we verify that it is never spilled into the firm or used to train models. This proactive path is a key part of AI data security.

We must also see the difference between masking data and true redaction. Redaction means the data is gone forever. For a leader, this means using platforms that give audit ready logs to prove every piece of data was handled correctly. 

GDPR and SOC 2

Handling the global rules of 2026 requires a plan as dynamic as the AI it governs. As leaders, we must meet the strict rules of GDPR and SOC 2: the standards for digital trust. For a CX team, reaching compliant AI Data Security goals without slowing down is a major challenge. 

Thunai simplifies this path by giving a hub that is both GDPR compliant and SOC 2 Type II certified. The Type II mark is key: while Type I only looks at a point in time, Type II proves that safety rules were effective over a long period. This is essential for AI data security.

Also, the EU AI Act has added a new layer: the need for explainability. Regulators now want proof of how AI works and what steps stop bias. Thunai meets these needs by giving full audit trails. It tracks the user's intent and the agent's actions to find any drift from the goal. 

This helps prove that our bots act fairly and follow the law. By automating the busywork of compliance: using AI Data Security to hunt for evidence and watch rules, we allow our teams to return to building the business while maintaining AI data security.

Innovation with Thunai

Innovation should never come at the cost of control. With Thunai, innovation is structured, measurable, and secure. Instead of adding disconnected AI tools that create new risks, Thunai builds a unified intelligence layer that connects transcripts, CRM records, knowledge bases, and workflows into one trusted source of truth.

This means teams can launch autonomous agents, automate after call work, and enable real-time decision support without fearing data drift or hallucinated responses. Every action is grounded in verified knowledge. Every interaction is monitored. Every insight is traceable.

For CX leaders using platforms like Genesys, this creates a powerful balance, faster innovation, lower operational drag, and enterprise grade AI data security built directly into the foundation.

Ready to secure your AI the right way? Book a demo with Thunai today.

FAQs on AI Data Security

Why is data security vital for AI in contact centers?

Every AI Data Security chat handles private details, and a single vulnerability can leak thousands of customer records instantly. Thunai prevents this by baking security directly into the workflow instead of tacking it on as a late stage patch.

How does Thunai stop AI hallucinations from happening?

We force the AI to pull from a verified knowledge layer, meaning it only uses your actual enterprise facts. This kills the guessing game and ensures every customer gets a response rooted in reality rather than digital fiction.

Can Thunai handle GDPR and SOC 2 compliance?

Absolutely, as we’ve automated the messy parts like audit trails and PII redaction to keep you legally shielded. It simplifies the entire compliance headache so you can focus on scale without worrying about regulatory fines.