AI Best Practices In Customer Service

September 24, 2026 in Ai
AI Best Practices In Customer Service

Using AI in customer service fails consistently. Here is what to plan upfront to make AI a success in your customer service this time;

AI Should Not Be An Obstacle

Customer service exists because we need to manage customer sentiment in situations where product or service fails to deliver. Talking to a human is the best way to manage sentiment; so we should focus on how we can use AI to make this more accessible.

Instead of using AI as a replacement to human interactions, we should focus on how to make talking to a human more accessible.

If we try to replace call center reps with AI Voice Bots, customers see that as an obstable to the better option and get frustrated. By using AI as an assitant to your call center reps, we can achieve better results.

Obviously, there are use cases where AI Voice Assistant is a better option and we will cover that as well.

Use AI to Eliminate Friction

One of the biggest friction points in customer service is the call center IVR menus and self service options. Main reason for using IVR is that agents are trained for certain skills, not all of them. By using AI as an assistant to your call center reps. you can let your agents to handle calls from any skill. So that you will not need an IVR; you can connect your customer to a representative who can handle all the questions without transferring the call.

AI Agent Assist uses the real-time call transcripts to create knowledge base flashcards so that agents can handle calls from the skills that they were not even fully trained for.

In order to support your agents, there is also Real-Time Sentiment Analysis for supervisors. It helps them to support your reps when the customer's sentiment is consistently negative on an active call.

AI Must Be The Better Option

Customers know that AI has shortcomings; speech recognition may not work in all cases and AI answers may not be correct all the time. Customers can tolerate those when AI is better than the other options;

One use case is the product support, product orientation, and new user help. Imagine that your dishwasher's top shelf is not cleaning well recently, despite you tried several things to fix it. You have three options as a user;

  • book a service technician: Usually it is not immediate and has a cost
  • check lots of YouTube videos about similar situations: Time consuming and may not be available for new products
  • talking to AI Voice Assistant for troubleshooting

By calling the helpline number, your customers can talk to AI Voice Assistant to get some help, even send photos and videos of the issue by mobile text and get a reply. In this case, AI is better than calling.a technician or spending hours on Youtube for dishwasher videos. In this case, customers do tolerate AI's shortcomings and they don't mind repeating the question or asking it in a different way.

Other use cases include, out of hours support and an option while waiting in the queue for talking to a real person.

AI Needs Fine Tuning for Each Use Case

AI is not plug and play; it needs fine tuning. As you roll out AI use cases, each AI response will be a success or a failure. By running iterations, you need to retrain your AI to increase its success rate. Your AI partner should be able to help with that.

Run Your AI Offline and Locally

In the age of AI, value of your business is the same as the value of your customer service data. Running your AI applications, speech to text and text to speech locally and offline is very important for data privacy and safety of your business. Using a shared cloud service or a "data lake" may expose your valuable data to the outside world and you will lose control of your data.

Top Five AI Use Cases in Customer Service

Here are top five AI solutions, you should consider for customer service;

Conclusion

AI is capable of delivernig amazing results. We just need to be aware of the hype created and focus on the interest of your company, not the service providers. Click here to schedule a call to discuss your AI use cases.

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