The implementation of artificial intelligence in customer support systems is increasingly becoming a key element in improving the efficiency of service companies. Automated AI systems that handle text requests, offer automatic recommendations, and potentially replace part of the call center operators are revolutionizing the service approach. These technologies not only accelerate the process of handling requests but also significantly reduce costs, enhancing customer satisfaction with faster and more accurate responses. To explore how AI impacts response speed, service quality, and economic efficiency, we decided to talk with expert Vladislav Kislov.
We also asked Vladislav to share real business statistics demonstrating the results before and after the implementation of such solutions.
Vladislav Kislov is a result-oriented entrepreneur with extensive experience in business, finance, and service management. He is the founder and owner of a successful home services company in the U.S., generating an annual income of $2.5 million and paying out over $1 million in salaries. Vladislav has rich experience in managing large service operations, leading a team that services over 3,500 homes per month, and developing business strategies aimed at improving efficiency and driving growth.
In 2025, Vladislav was honored with the Cases&Faces Award. He was honored with a nomination for “Manager of the Year” in the “Consumer Services” category. The purpose of the Cases&Faces Award is to recognize and promote exceptional individuals, ideas, and projects that contribute innovations across various spheres such as entrepreneurship, management, social practices, science, culture, education, and digital technologies. It aims to ensure that the creators of these innovative achievements receive both expert and public recognition. Each submission is evaluated by an independent panel of judges, all of whom are experienced professionals with notable careers.
Are AI systems used in your business to handle customer voice and text requests, and if so, how do they help replace or support call center operators?
Yes, our business uses an AI system to handle text customer requests. This allows us to respond instantly, significantly reducing wait times. We also tested AI for voice calls, but the quality was insufficient, so currently, live operators handle phone calls. We continue to monitor the development of the technology, and if voice AI improves, we may consider re-implementing it.
What changes in customer satisfaction levels, response speed, and cost reduction have you observed (if any) after implementing automated support systems?
The introduction of AI for text messages significantly reduced the average response time from 15 minutes to 30 seconds. This increased customer satisfaction as they receive the needed information much faster. Additionally, automation helped reduce the workload on operators, which lowered costs for recruitment and training.
What are the main benefits of AI-based automated systems for handling text requests in the context of customer service?
The main advantages of AI in text support are immediate responses, the ability to operate 24/7 without breaks, and the absence of human factors that may cause delays or errors. AI also standardizes communication, ensuring consistency in responses and reducing the risk of misunderstandings.
How do automated customer support systems adapt to various requests and situations, and how often do these systems require the intervention of live operators?
If AI is unable to process a request, a live operator steps in. However, the system continuously learns from such cases, reducing the likelihood of recurring issues in the future. Over time, AI becomes more accurate and requires less intervention from operators.
What challenges or issues arose when implementing AI systems in customer service, and how were they addressed?
One of the main challenges was the quality of recognition of complex or non-standard requests. Initially, AI did not always understand the essence of the inquiries correctly, requiring manual adjustments. We solved this problem by continuously training the system on real dialogues. It was also important to integrate AI smoothly into the workflow, allowing operators to join the conversation when needed easily.
How do you see the future of automation in customer service? What do you think is important to consider when implementing AI solutions to maintain or improve service quality?
In the future, AI will become even more accurate, and we may be able to revisit testing voice solutions. It’s important to keep in mind that AI should not only respond quickly but also be user-friendly and understandable to customers. We also believe that completely excluding live operators is not yet feasible – human involvement remains crucial in complex situations. Therefore, the key point is finding the right balance between automation and human interaction.
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