Using AI in your customer support organization brings plenty of benefits, from helping support teams work more efficiently to delivering improved self-service. But implementing AI isn’t without its challenges, especially when it comes to managing data privacy and compliance. AI systems often handle high volumes of sensitive customer and company information, so the stakes are high. How can businesses get the most out of AI while keeping data secure and complying with data protection laws? In this article, we’ll answer this question, and highlight how you can adopt AI in customer support responsibly.
There are three major ways AI can transform your support operations:
1. Enhanced efficiency and productivity. AI is great at automating routine, repetitive tasks that can otherwise slow down your team. They can summarize conversations, suggest relevant responses or resources, and even convert internal documentation into customer-friendly articles, streamlining processes and saving valuable time and resources. For instance, Yotpo agents improved efficiency by 30% after implementing an AI assistant.
2. Improved customer experience. AI’s ability to personalize interactions and deliver instant responses can significantly boost customer satisfaction, while also dramatically improving ticket deflection. Since they’re able to dynamically summarize relevant articles for customers, AI-powered help centers are far more effective than static knowledge bases. articles. One of the biggest wins here is that AI-powered systems work 24/7 – no breaks or vacations – so your customers can get help whenever they need it. An AI chatbot, for instance, can handle late-night inquiries and simple FAQs, ensuring round-the-clock service and happy customers.
3. Data-driven insights. Advancements in natural language processing enable AI to analyze vast amounts of data in real-time, unlocking insights at a level you’ve never had access to before. This includes a wide spectrum of outcomes. AI is able to analyze 100% of your support conversations, uncovering knowledge gaps among your team so you can proactively coach your agents and develop informed training resources. AI is also better at identifying trends in customer sentiment, helping you create a more informed product roadmap and making it easier to connect the dots between customer feedback and the reasons customers churn off your product.
All these advantages make AI tools an attractive option for support teams across the globe.
AI is a powerful tool, but with great power comes great responsibility.
As AI technology evolves, so do the regulations around data privacy. Mishandling customer data can result in heavy penalties, not to mention a loss of trust and damage to your brand’s reputation.
There are a handful of critical regulations and standards to consider when planning how to add AI to your customer service tech stack:
By adhering to these regulations and choosing AI service providers with industry-recognized certifications, you not protect your business from legal penalties and build trust with your customers. If you’re serving enterprise customers, certifications like these are essential to even get on a prospect’s shortlist.
How a company handles customer data can make or break its reputation.
Research shows that 70% of customers would be less likely to engage with a brand if they knew AI was being used without proper human oversight. Trust is fragile, and mishandling of sensitive information, as well as AI-generated poisonous or “hallucinated” answers, can severely damage a company’s image.
As Melanie Mitchell, a professor at the Santa Fe Institute, wrote in the New York Times:
“The most dangerous aspect of AI systems is that we will trust them too much and give them too much autonomy while not being fully aware of their limitations.”
Over-reliance on AI — without understanding its boundaries — can lead to serious missteps.
Consider the case of Air Canada in February 2024.
The airline faced legal action after its AI bot gave a customer incorrect information about claiming bereavement fares. Following the bot’s guidance, the customer purchased a ticket, only to have the airline reject the refund claim later, saying the discount couldn’t be applied after purchase.
The court ruled in the customer’s favor, holding Air Canada responsible for the bot’s misleading advice as the company didn’t take “reasonable care to ensure its chatbot was accurate.”
And this isn’t an isolated incident with AI usage in customer support.
Chevrolet’s bot once mistakenly promised to sell a car for $1.
And DPD’s AI bot famously swore at a customer during an interaction.
While these latter examples may not have led to legal consequences, they certainly affected the brands’ reputations – and if trust is a difficult thing to earn, it’s even harder to rebuild once it’s been broken.
So, how can you leverage AI to improve your customer support without compromising security and privacy?
It all starts with selecting the right AI partner. While cost and ease of use are usually top of mind, don’t overlook security and compliance with data regulations — they should also be right up there on your list of priorities.
When evaluating potential AI providers, here are the key questions to ask from a security standpoint:
And here’s a final pro tip: loop your security team in early.
If you’re a customer support leader, looping in your security team too late can derail your entire AI initiative or, at the very least, significantly delay your timeline. It’s not because they’re being difficult—they’re just doing their job.
Whether they need audit logs to monitor employee access, single sign-on for added authentication, or consent mechanisms to meet GDPR requirements, involving them early will help ensure a smooth and successful rollout.
And if you’re a CISO (or any related security role), you already know it’s no fun coming in at the last moment and being the one who says no to an exciting new project.
For AI to function effectively in your organization, your team needs comprehensive training that covers both the tools and data privacy aspects.
For support team members, the focus should be on:
Beyond just technical skills, training programs should also include ethical considerations. This means addressing issues like mitigating algorithmic bias, ensuring responsible AI usage, and preventing overreliance on AI — especially in sensitive situations where human judgment is essential.
Customer-facing teams, in particular, need to be trained to recognize when AI-generated responses require human review, especially during emotionally charged or complex interactions with customers.
Including real-world examples from your company’s experiences and realistic scenarios showing what could happen if security or privacy policies are breached can help employees better retain this information.
Since AI is evolving, your security awareness program needs to evolve, too. Encourage feedback from your employees to gauge how effective the training is, and make ongoing adjustments as needed to help your team stay up-to-date with the latest knowledge and skills.
Introducing AI into your workflow means adjusting internal processes and closely monitoring its performance to ensure it delivers the desired outcomes. Here’s how to build an effective monitoring framework:
Begin by implementing AI in a select group of processes or a small team to keep things manageable and test AI without overwhelming the entire operation. Ideally, early adopters should be team members who are enthusiastic about AI and willing to experiment with new tools.
Let them pilot the system, track their successes and challenges, and use their feedback to refine the process. Starting small gives you the opportunity to adjust in real-time and optimize AI performance without disrupting core operations.
To limit risk, it’s also often a good idea to first implement internal-facing AI (like AI-powered workflows) before implementing customer-facing AI.
Once AI is in place, schedule weekly or bi-weekly check-ins to assess its impact on productivity and efficiency. Over time you’ll be able to reduce the frequency of these check-ins, but early on it’s essential to be proactive about training your AI model and catching issues early.
These meetings should include both internal stakeholders and your AI vendor to review the system’s performance. Regular check-ins help catch data quality and security issues early and fine-tune the system to ensure you’re getting the most value from your AI solution.
The people who interact with the AI daily will have valuable insights, so make it easy for them to share their experiences. Create simple channels for them to submit suggestions, flag difficulties, or highlight areas for improvement.
Their input will be essential for training your AI model over time, as well as keeping the system running smoothly and ensuring it evolves with your business needs.
Clear, accessible policies on protecting customer data are crucial for keeping privacy and security at the forefront of your organization. These guidelines give employees a practical framework to follow in their daily work.
However, having policies alone isn’t enough to build a privacy-first culture, so consistent action is key.
And it starts with leadership.
When leaders make data privacy and security a priority, it sets a strong example for the entire organization to follow.
Recognizing and rewarding good practices, fostering collaboration between customer support and security teams, and regularly reviewing policies all help reinforce the importance of data protection and ensure that everyone stays aligned on compliance.
By taking these steps, you show your employees that safeguarding customer data is not just a policy — it’s a shared responsibility and a team sport.
With the right approach, AI can be a powerful ally in delivering outstanding customer experiences. But the real challenge lies in finding the sweet spot between leveraging AI’s capabilities and maintaining the data privacy and security that customers expect.
Striking this balance is the key to the long-term success of your AI implementation.
Luckily, there are tools designed to do both – and Ask-AI is one of them.
Ask-AI’s team is on a mission to build the most secure AI platform on the market. Today, their product meets all industry-leading standards, and it’s designed from the ground up to exceed modern security, privacy, and compliance requirements.
Ask-AI’s enterprise-grade AI includes all standard certifications, including SOC 2 Type II, ISO 27001, and full GDPR compliance. And when you’re working with Ask-AI, you stay in control, choosing what data the system can access and what’s available to your teams. No customer data is ever shared with third parties or used to train language models.
Book a demo today to empower your team with responsible AI that delivers incredible customer experiences through your reps, help center, and product.
