There’s no doubt. AI is changing the way businesses deliver customer service. From chatbots that handle FAQs in seconds to smart tools that help agents reply faster, AI can make support operations more efficient and scalable.
But as more companies jump on the AI bandwagon, recent headlines are highlighting a crucial reality: AI doesn’t always get it right.
Major tech players have seen their AI tools provide inaccurate, misleading, or even made-up responses. This has become a phenomenon now widely known as “AI hallucinations.” And while these glitches can be harmless in some contexts, in customer service, they can quickly damage your brand’s reputation.
What does this mean? It’s time for a reality check. AI is powerful, but it’s not perfect. And it’s certainly not a replacement for the human touch that customer experience is built on.
AI glitches and AI hallucinations: what’s really going on?
Check out these real-life scenarios and AI hallucination examples:
- A lawyer used a conversational chatbot for legal research assistance. The judge saw that six of the precedents quoted in the brief were bogus. The chatbot not only made them up, it even specified that the precedents were available in major databases.
- Microsoft’s Bing Chat gave the wrong figures about Gap’s recent earnings and Luluemon’s finances.
- Microsoft’s Tay chatbot generated racist and offensive tweets after it was launched, due to what it had learned from interacting with Twitter users.
- Air Canada’s chatbot gave a customer false information on bereavement discounts. Following the chatbot’s advice, the customer booked a flight and was denied the discount.
- DPD’s chatbot insulted the company itself by calling it the “worst delivery firm in the world” and told the customer not to call them.
Yes, AI hallucinations are very much real. So real that even Google has an AI hallucination definition:
AI hallucinations are incorrect or misleading results that AI models generate. These errors can be caused by a variety of factors, including insufficient training data, incorrect assumptions made by the model, or biases in the data used to train the model. AI hallucinations can be a problem for AI systems that are used to make important decisions, such as medical diagnoses or financial trading. – Google Cloud
So why does AI get things wrong? The short answer: it’s only as good as the data it’s trained on.
When engineers build AI systems (especially large language models (LLMs) which is the tech behind AI chatbots), they feed them massive amounts of information from books, websites, and other sources.
The AI studies this data, learns patterns, and uses those patterns to figure out how to respond to questions or complete tasks.
Issues arise when:
- There is not enough data. If the AI hasn’t “seen” a particular type of question or situation in its training, it may just make an educated guess. That’s why sometimes, you’ll notice polished and well-written sentences that don’t really make sense.
- The data is flawed or biased. If the information it learned from is incomplete, outdated, or inaccurate, the AI will absorb those same flaws.
- The AI attempts to fill in the gaps. When the AI doesn’t know the answer, it sometimes creates one based on similar examples from its training. The result can be something totally believable… but also totally wrong.
That’s why a chatbot might give you a convincing “fact” that never happened, cite a research paper that doesn’t exist, or misidentify something entirely.
For customer service, these mistakes can cause big problems. Wrong pricing details, made-up refund policies, or product info that doesn’t match reality. And because AI can deliver these answers so confidently, customers might not realize they’ve been misled until it’s too late.
The key takeaway? AI isn’t thinking like a human—it’s predicting what to say based on patterns. And while it’s incredibly good at that, it’s not immune to making things up.
The risks that AI hallucinations bring to the customer service industry
AI can be an incredible asset for customer service. After all, it speeds up response times, reduces repetitive work, and provides 24/7 availability. But its tendency to “hallucinate” poses real risks that businesses can’t afford to ignore.
In fact, studies show that chatbots can hallucinate up to 27% of the time. In customer service, where accuracy and trust are everything, even a small mistake can cause some huge damage to your brand. If AI provides the wrong answer, it doesn’t just create confusion. It can damage your brand’s reputation and cost you sales.
Here’s an example:
Customer asks: I received an email announcing these gadgets are 50% off for Black Friday. Is that true?
AI chatbot answers: Yes, our entire gadget collection is on sale for 50% off. Add the items to your cart and the discount will automatically be applied.
Flawless, right? Except maybe, the actual promo requires customers to type in a special code. Or maybe only selected gadgets are on sale. These little but crucial details are where AI can slip up.
Here are some of the biggest risks AI hallucinations pose:
- Incorrect or misleading answers. AI may confirm details that are wrong, and these errors can frustrate customers and result in lost sales.
- Invented policies or procedures. AI can fabricate return policies, warranty terms, or service rules. This happened when an AI-powered chatbot told users that account logouts were “expected behavior” under a policy that didn’t exist.
- Erosion of customer trust. Customers rely on support teams for accurate information. When they realize they’ve been misinformed, they may lose confidence in the brand, and this can result in churn.
- Escalated conflict and increased workload. Wrong answers can create confusion that requires human intervention. So instead of AI helping human agents resolve issues quickly, human agents may need to spend extra time repairing customer relationships.
- Reputational damage. One AI blunder can go viral and harm your brand image. Public mistakes are much harder to undo than they are to prevent.
Why AI should complement, not replace, human support teams
AI is a powerful tool, but it’s still just a tool. Yes, it can handle a variety of tasks at scale, but it doesn’t possess the empathy, intuition, or contextual understanding that human agents bring. The best customer experiences happen when AI and humans work together, each playing to their strengths. This hybrid approach ensures speed and efficiency without sacrificing trust and personal connection.
The human element in customer experience
No matter how advanced AI becomes, it can’t truly feel empathy or understand the emotional weight behind a customer’s words. Humans excel at:
- Understanding when a customer is frustrated, worried, or upset, and responding in a way that makes them feel heard.
- Recognizing when a question isn’t just about the product, but about a bigger problem the customer is facing.
- Making decisions in situations where policies might need to be bent, exceptions granted, or creative problem-solving applied.
Example: A chatbot can answer a late-delivery query with an estimated shipping time and end the conversation. A human agent, on the other hand, can detect urgency in the customer’s tone and apologize sincerely before arranging a follow-up.
When AI works best: support, not takeover
AI shines when it’s used to make human agents more effective—not replace them entirely. For example:
- Automating repetitive tasks: AI can handle routine inquiries like order tracking, password resets, or store hours which frees up human agents to focus on complex issues that need a personal touch.
- Helping agents respond faster (AI as co-pilot): AI can suggest responses, summarize long conversations, or surface relevant help articles so agents can provide answers more quickly.
- Managing large data sets and routing tickets efficiently: AI can analyze incoming requests and automatically reroute them to the right department or agent, reducing wait times and improving first-contact resolution rates.
- 24/7 initial response coverage: AI-powered chatbots can greet customers at any hour, and ensure urgent issues are queued for immediate human review.
- Customer sentiment analysis: AI can flag conversations where the customer seems upset or dissatisfied, allowing agents to step in proactively before issues escalate.
How to integrate AI into your customer service operations
Remember that AI in customer service isn’t about replacing your human team. It’s about making them faster, more efficient, and more effective. The most successful companies treat AI as a strategic partner. Here’s a step-by-step approach to integrating AI the right way:
Step 1: Identify what to automate
Not every part of customer service is suited for AI. Start by mapping your most repetitive, time-consuming tasks and automate those first. These will reduce agent workload without risking the customer experience on complex interactions.
Examples:
- Answering FAQs
- Tracking orders
- Handling basic account updates
- Providing store hours
Step 2: Keep a human-in-the-loop system
Define clear escalation rules so that when an AI encounters a question it can’t answer with high confidence, it hands it off to a live agent instead of inventing an answer. This ensures customers never get stuck in a frustrating loop with an AI that doesn’t understand their problem.
Step 3: Regularly audit and train your AI tools
An AI is as smart and effective as the data it’s trained on. They need ongoing supervision, such as:
- Review chatbot transcripts regularly to catch inaccuracies or outdated information.
- Update the AI’s knowledge base to reflect new products, promotions, or policy changes.
- Watch for signs of bias or irrelevant responses to prevent drift from your brand’s tone and standards.
Step 4: Equip your agents with AI co-pilot tools
AI can empower human agents behind the scenes just as much as it can assist customers directly. Consider adding these capabilities to your tech stack:
- Suggested responses help agents reply faster without starting from scratch.
- AI-powered summarization can condense long tickets so agents instantly understand the issue after it’s handed off.
- Sentiment analysis can flag emotionally charged conversations so agents know where to tread carefully.
Step 5: Measure and optimize continuously
Use metrics to track whether AI is helping or hurting the customer experience:
- Monitor resolution times, customer satisfaction (CSAT) scores, and escalation rates.
- Gather agent feedback to understand how AI is affecting their workflow.
- Refine your approach based on both data and human insights.
How LTVplus uses AI to power customer support
At LTVplus, our AI strategy is built around enhancing our human agents’ capabilities, not replacing the human touch that customers value most.
Our approach to AI-enhanced support
- AI supports agents, never replaces them. We use AI as a powerful assistant to speed up processes, reduce repetitive work, and surface the right information quickly. Meanwhile, our agents handle complex and sensitive conversations.
- Human-first policies and quality assurance layers. Every AI interaction is supported by a human safety net. We monitor AI outputs, review accuracy, and step in whenever context or empathy is needed. This ensures customers always get the right information and a personal connection.
Results we’ve seen
- Faster ticket resolutions. AI-powered triage and suggested responses reduce handling time so customers get their answers faster.
- Improved CSAT scores. Since agents are freed from repetitive queries, they can focus on high-value interactions.
- Better performance than AI-only setups. Our hybrid approach combines the speed of AI with the empathy and adaptability of human agents. This strategy delivers a consistently better customer experience.
More LTVplus resources for integrating AI tools and human agents
Blogs
- 24/7 Customer Support Isn’t Optional in 2025: Here’s How to Build a Global Support Team Without Burning Out Your People. This guide goes over the importance of offering 24/7 customer support. We also go over the tools and the systems that will help you achieve this.
- Harnessing AI Customer Support: Enhancing Human Connection Through Automation. Uncovers how businesses can turn their AI customer support into something that nurtures both efficiency and genuine engagement.
- Live Chat vs Chatbots: Optimizing Customer Conversations. Live chat or chatbots? Which one is better? The answer might surprise you. So we provided this guide to walk you through both customer service strategies, where they excel, and how to maximize them.
- 10 Tips for Customer Service Automation That Will Change the Way You Deliver Support. These are ten quick but meaty actionables that will help you get the most out of customer service automation.
- Hybrid Customer Service Can Wow and Delight Your Customers: Here’s How. This blog starts off with five reasons why you should consider hybrid customer service. Then, we provide tips and best practices for implementing it.
Guides and ebooks
- When AI Meets CX: The Future of Customer Service is an in-depth discussion on what customer service will be like in the future. This guide was created with the help of various LTVplus partners in the AI and CX space.
- Humanizing Customer Support in the Digital Transformation Era compiles insights from a couple of industry experts. This guide aims to provide clarity on the concept of humanization of customer support in a digital world.
Final thoughts: Nothing beats the human touch
In a nutshell, AI is truly transforming customer service. But as powerful as it is, going all-in on AI too quickly can create more problems than it solves.
Without the right oversight, AI hallucinations can happen—which can then erode the very thing customers value most: trust.
Complex customer experiences often require a human touch. While AI can assist in these interactions, it can’t replace the warmth, understanding, and flexibility of a human conversation.
At LTVplus, we help businesses get the best of both worlds. Our approach to AI is strategic and human-centered. We use technology to make support more efficient, but we keep people at the heart of every interaction.
LTVplus is the best partner for scaling customer support without sacrificing quality. Reach out to us today to see how we can help you maximize AI tools to provide great customer experiences.
