How AI chatbots can handle privacy, security, and data concerns

Generative AI models have drastically changed the way people communicate and consume information. This development poses a challenge to many traditional business processes, and we can see businesses trying to adopt this technology in ways that lead to a better customer experience without putting users' personal or business data at risk.

Catapulted by the launch of OpenAI's ChatGPT and other generative models, AI chatbots have moved from the good-to-have checklist to a must-have conversational experience.

Historically, bots were often dismissed as unhelpful, but the intelligence added by generative AI models has completely changed people's perspective on these tools. AI bots can now attend to incoming requests with zero waiting time, mimic the conversational abilities of a human agent, understand complex queries, and provide accurate resolutions. AI chatbots are reshaping the way businesses approach customer interaction.

However, the generative models must be fed with data for an AI chatbot to work as intended. For a business, the models can take information from the company's website, knowledge base, FAQs, and other available resources. Privacy and security issues are minimal because all the information used to train the bot is already openly available.

Concerns begin to escalate when customers' private data is being shared via AI chatbots. This raises important questions about how the bot will collect, process, and store that data.

How AI chatbots work: Before and after GenAI

Before GenAI: Structured, supervised learning in a controlled environment

Before GenAI, rule-based chatbots were widely used. They didn't create any data concerns, as businesses fed structured information to those models under supervision. Website information, help guides, FAQ lists, and knowledge base resources were mapped with the bot to provide a limited ability to answer customers' most common questions. Because it was carried out in a controlled environment, the system provided comprehensive oversight over how data should be processed and shared with others.

After GenAI: Unstructured unsupervised learning

The stark difference in how GenAI models operate is how they learn and process data. A chatbot powered by GenAI will learn from every interaction it has with the customers, increasing the possibility of learning and exposing the proprietary data.

As we only have a handful of GenAI models, businesses hire those models to be the faces of their AI chatbots. Since they don't have control over how those GenAI models are trained, this leads to privacy, security, and data concerns about whether the providers are using collected customer data to refine their models.

Privacy, security, and data concerns around GenAI

The potential and usage of AI chatbots have expanded—they are no longer mere tools for conversations but can schedule payments, medical inquiries, purchase orders, transactions, and more.

When the generative models analyze all these conversations, it creates concerns, as customers might be sharing sensitive information with bots. Businesses need to have secure processes for collecting, storing, processing, and sharing that data.

What are the possible threats businesses face using GenAI chatbots?

The risk of privacy breaches is present during two stages: 1) When training GenAI models with data and 2) Accessing the trained data.

Only moderated and reviewed data should be used to train the models to prevent breaches. Any personal or proprietary information that cannot be shared in a public forum should be removed.

Likewise, when interacting with GenAI, there should be a gatekeeping mechanism to prevent sensitive information from being shared with those who doesn't have the approval to see the sensitive data. Authenticating interactions before sharing information can help businesses avoid breaches of privacy.

Best practices for ensuring data privacy in AI chatbots

Businesses have to be mindful of data privacy concerns and consistently apply best practices to protect their customers. What can they do? Let's see:

Be transparent and get consent

It's crucial to be transparent about what data you'll be collecting and how it will be used. As GDPR mandates opt-in for collecting data, you need to be upfront with your customers about what happens to their data and get their consent. This will also help increase their confidence in interacting with your business.

Implement secure collection, storage, processing, and sharing processes

Have a strict framework for securing data collection, storage, processing, and sharing. Conduct regular audits to check if the system is working as planned and resolve any issues. Companies may also want to arrange external audits to help improve the existing data privacy and security practices.

As we discussed above, it is crucial to feed only publicly available data while processing the data to train models, as this reduces the chances of privacy and data threats.

Role-based access control (RBAC): Authenticate and authorize

Role-based access control gives people access to data necessary for their role. Streamlining access settings enhances overall security, as no unnecessary information will be shared mistakenly with anyone who doesn't need access for their role.

Access can be shared by authenticating and authorizing the users. This creates an access trail and ensures that any people who have access to sensitive data remain accountable. Ultimately, it reduces the human error we could make in accessing, processing, and sharing the data.

Does it seem like a lot? Well, the simple solution would be to select an AI chatbot provider who is committed to handling your data, privacy, and security concerns so you can focus on your business.

Zoho SalesIQ's AI chatbots for secured conversations

As discussed earlier, SalesIQ's AI chatbot is powered by Zia, Zoho's proprietary natural language processing (NLP) solution. We don't use customers' data to train the AI model or sell ads. As we have for more than 25 years, Zoho promises we will never monetize our customers' data.

We adhere to the crown jewel of privacy regulations, GDPR (General Data Protection Regulation). Moreover, we extend GDPR's protections to non-European nations as part of our commitment to provide the highest levels of privacy and security to our users. We're also HIPAA compliant to ensure that healthcare organizations can also benefit from AI chatbots while adhering to regulations that govern how they collect, store, process, and share medical data.

When it comes to training GenAI models, we use only publicly available information. Since we run our own servers, customers' data is securely stored and complies with industry-standard audits. Any third-party packages are thoroughly checked for legal and security vulnerabilities to ensure the highest level of protection.

SalesIQ also integrates with OpenAI's ChatGPT

SalesIQ can be integrated with ChatGPT in two ways:

ChatGPT with Answer Bot: Users can integrate ChatGPT with our Answer Bot. Based on the visitor's query, Answer Bot, powered by Zoho's AI assistant, Zia, will find the appropriate resource. ChatGPT will only parse those selected resources and share a concise answer. It won't gain access to any other resources beyond that scope, and all these resources are publicly available.

ChatGPT card in our codeless bot builder:

This approach allows SalesIQ to extend its robust internal privacy, security, and data protection processes to third-party applications like OpenAI.

Want to see our chatbots in action? Sign up and start build secure AI chatbots for your business.