According to a study by the Federal Reserve Bank of St. Louis, employees who use AI become on average 33% more productive for each hour of work than those who do not use it. The effect is especially noticeable in areas where speed of communication is important, such as customer service.
In this article, we will tell you what AI in customer service will become by 2025, what real benefits it will bring to companies, and why it is being used not only by technology giants but also by small businesses.
What is AI in Customer Service?
Have you ever written to support and waited hours for a response — or never received one at all? Now imagine your customer getting help in seconds, right in messenger, with no calls, no forms, and no annoyance.
That’s how artificial intelligence works in customer service. A smart chatbot understands the essence of the issue, immediately offers a solution, and knows exactly when to connect with a live service agent.
Benefits of Using AI for Customer Service
Support that works without fatigue, responds instantly, and remembers what the customer contacted last time — sounds like the ideal? That’s exactly how AI solutions can help in customer service.
First, AI is always on call. While employees are resting, the AI continues to take requests, prompt solutions, and engage in dialog — quickly, clearly, and uncluttered. It can understand context and even conversational AI elements like tone and urgency.
Second, it removes the routine from the team. The bot can solve simple customer queries by itself and pass more complex ones to a human but already with the necessary information, without unnecessary correspondence. This empowers the customer service team to focus on meaningful interactions and enhances the overall support experience.
The third thing is speed. No waiting in queues, automatic sorting of requests, instant answers. The client does not wait but gets help while they are still in the mood to solve the issue.
And what is especially pleasant is that the AI is able to adapt to the client. It can take into account the history of communication, interests, tone, and style so that the answers are not just accurate, but appropriate and humane.
It also helps to improve customer relationships and service quality and even enables teams to support customers more effectively through data-driven insights. And of course, if your company is growing, AI is easily scalable. One bot can handle what used to take an entire team to do. No offices, no vacations, no overtime.
Key AI Technologies for Customer Support Service
AI in customer support is not just one tool but a whole set of technologies, each of which solves a different problem. Together, they make service faster, more accurate, and more convenient for both the customer and the team.
Chatbots that Understand What You Mean
This is not about buttons “1 — check balance, 2 — contact an operator”. Modern bots can understand live speech — with emotions, mistakes, and incomplete phrases. Write “My payment is not working”, and the bot will clarify what is wrong and try to resolve customer problems without putting them into templates.
Generative AI That Responds Like a Human
Models such as ChatGPT generate a response not from a pre-defined list but right at the moment of the request, taking into account the context, the client’s communication style, and even their mood. Support becomes not just functional but truly human.
Intelligent Routing
The customer doesn’t have to choose from 10 menu items. AI itself understands what is being discussed and directs the request to where it will be resolved fastest. This saves time for both the customer and your customer support team.
Mood Analysis
AI can also detect when a customer is annoyed, frustrated, or satisfied — and helps them react in time. This approach reduces conflicts and increases loyalty.
Voice Technologies
When a customer calls, the AI recognizes speech, translates it into text, and can even help the operator: by prompting answers, searching for relevant information, and recording the conversation. All of this happens in real-time.
Recommendation Systems
While the customer is still formulating their question, the AI already comes with a ready-made solution. It analyzes how people in similar situations have solved the problem and suggests what will work.
AI can provide real-time answers and support across channels, ensuring customers feel heard and helped immediately — even before talking to a human. If needed, AI help can guide agents with knowledge-based suggestions.
AI-Powered Customer Service in 2025
In 2025, artificial intelligence (AI) is fundamentally changing the face of customer service, transforming it from a traditional support channel to a strategic tool for improving productivity and better customer satisfaction.
According to Stanford University’s AI Index Report 2024, investment in generative AI has literally exploded — it has grown almost eightfold over the year to reach $25.2 billion. At the same time, several major studies confirm that AI helps people to work faster and better, and also helps to narrow the gap between experienced and novice specialists.
This data shows that AI is becoming an integral part of customer service, enabling companies to handle customer inquiries faster and more efficiently, reduce operational costs by automating routine tasks, and increase customer satisfaction through personalized and timely service.
How to Implement AI in Customer Service: A Step-by-Step Guide
AI is a powerful tool, but for it to start delivering value, it’s important to implement it wisely. Below is a clear plan of action that will help you integrate artificial intelligence into your support team without chaos or waste.
Identify the Tasks Worth Automating
Start by analyzing: which support requests are the most frequent? Where do operators waste time? These can be standard questions about shipping, returns, registration, order status, etc. It makes sense to automate them in the first place.
Choose the Right AI Customer Service Solutions
There are many options: from simple chatbots to advanced generative models like ChatGPT. The choice depends on your goals. Need fast filtering of requests? Smart routing is the right choice. Want to replace some of the operators? Look at NLP bots that understand the client’s language.
Prepare Data for Training
The more accurately the AI understands your customers, the better it works. Use an archive of correspondence, frequent questions, and typical scenarios — all this will help “train” the system to give relevant answers and help AI better understand customer needs.
Integrate AI with Your Support Channels
Connect AI to those channels where you already have traffic: website, Telegram, WhatsApp, mobile app, e-mail. It’s important for the customer to be able to go wherever he or she feels comfortable, and the AI will handle everything internally.
Test and Monitor the Performance
Launch a pilot version and monitor: how many requests are processed without human intervention, how much load is reduced, and how customers react. Collect feedback and adjust scenarios.
Increase the Use of AI Gradually
When AI copes with basic tasks, you can move on to more complicated ones: analyzing customer sentiment, automatic generation of reports, forecasting bounce rates, etc. The main thing is to scale the solution step by step, without overloading the system.
Challenges and Risks of Implementing AI in Customer Service Operations
Implementing AI in customer service is a step with serious expectations: automation, savings, and efficiency gains. But in practice, companies face a number of challenges that cannot be ignored.
First, a lot depends on the quality of the trained model. Without good data — history of requests, typical customer requests, information about customer issues — even the most advanced AI systems will not give the desired result.
Without good data, AI solutions do not recognize customer interaction correctly, give formal answers, and create a feeling that the customer is facing not intelligence but an answering machine. This directly affects the customer experience.
Secondly, the role of human agents cannot be completely ruled out. Humans are still needed, especially in complex, emotional, or non-standard situations. AI chatbots should be assistants, not replacements. The ideal scenario is when AI supports agents by providing them with the necessary information and reducing routine.
Technical risks also exist. To be able to leverage AI, one must be aware of how AI aligns with current customer service activities. Legacy platforms or a lack of APIs can slow down the integration process. This way, teams must carefully select the right AI tool and implement it properly.
We should not forget about security. AI processes sensitive customer data and a breach of privacy can damage reputations. Everything must work by the book, from security to transparency about how AI is used in customer service.
Conclusion: Implementing AI-powered Customer Service
AI can help transform customer service — making it faster, smarter, and scalable. But only if the business approaches implementation not as installing a “magic button,” but as a project with a clear strategy.
It is important to define goals in advance, train the system on actual data, test, and make sure that customer service experience does not deteriorate but improves.
At SCAND, we help companies use AI in a smart and practical way. Instead of just adding new tools, we make sure AI fits the company’s goals and works well with what’s already in place. We focus on improving customer service without losing the human touch. With our help, AI becomes a real benefit — not just a buzzword, but a way to make support faster and better.
