What is AI in customer communication? Definition and best practices for 2025

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Your customer support agents are handling dozens (maybe hundreds) of customer interactions every day. And with each channel you add to your communications strategy, the cracks can start to show: slow response times, frustrated customers, and support agents stretched to the limit.

Artificial intelligence features, from real-time call transcription and sentiment analysis to automated routing and response generation, are helping customer-facing teams do more, and do it better. 

In this article, we define what AI in customer communication management (CCM) actually looks like in 2025. We also share eight practical ways to use it to improve your team’s workflows and deliver an exceptional customer service experience without burning out your agents.

What AI in customer communications means and why it matters

Customer expectations are higher than ever. They want replies in seconds, answers that immediately resolve their issue, and customer service that feels tailored to them. AI in customer communication makes this possible.

But implementing AI isn’t about robots replacing human customer service agents. It’s about smarter tools that help customer-facing teams do their job better and more efficiently. AI tools help manage calls, chats, and messages by automating the mundane, recommending helpful actions, and giving every customer the attention they deserve.

Think hyper-personalised support, real-time call transcriptions, smart routing, natural language processing (NLP) insights, and AI agents that don’t sound like bots. And when you add an AI-powered customer communications tool like Aircall to your tech stack, you get access to customer sentiment insights, instant call summaries and action items, and conversation trends.

According to Aircall’s Voice of SMBs report, 82% of small businesses that use customer service chatbots say they use it to enhance customer engagement. That’s a good sign. But more importantly, it shows that AI is becoming part of the everyday customer experience and a standardized approach for offering more efficient customer support.

8 best practices for leveraging AI in customer communications

You don’t need a full AI strategy to start seeing value. Sometimes, small changes like summarizing calls or nudging agents in real time can make a big difference. Here are 10 CCM best practices to help you start implementing AI, experimenting with different approaches, and making the technology a natural part of how your team communicates.

1. Identify clear use cases for AI that make sense for your business

Customer service AI works best when you know exactly what you want it to do. So start by looking at the parts of your customer communications that are high-volume and repetitive. This can include routine customer service tasks like tagging tickets, routing calls, or answering basic customer inquiries. These are solid entry points for automation.

If you’re not sure where to start, ask your support team. They’ll know where the time sinks are and which customer requests currently eat up the most time. Plus, involving your agents in the decisions-making process will help you get their buy-in come time to implement the tool.

Keep your use cases narrow at first, and focus on improving one workflow at a time rather than reinventing all your workflows at once. You’ll likely see early wins in faster response times and less pressure on your agents. That’s valuable in itself, but you’ll really see the payoff when it starts improving the customer experience.

2. Choose communication tools with built-in AI features

Instead of stitching together disconnected communications platforms, look for tools with built-in AI features. When everything lives in one place, setup is simpler, training is faster, and you’re less likely to end up with data silos and manual errors. 

Aircall, for example, comes with a number of built-in AI features: 

• AI Voice Agent handles routine tasks and customers queries and ensures you never miss a call again. 

• AI Assist detects customer sentiment and mood, highlights action items, and scores your agents’ calls for better training. 

• AI-Generated Call Summaries, a part of AI Assist, reduce admin after customer interactions with key topic recognition and talk-to-listen rations. 

Take pressure off your agents and empower them to hold better conversations with Aircall’s advanced AI features. Learn more. 

3. Start small, then scale

The smartest way to bring AI into your customer communications is to start small instead of trying to overhaul everything at once. Will Yang, Head of Growth and Marketing at Instrumentl, recommends “taking an iterative approach. Start with a limited use case; gather feedback from customers, employees, and other stakeholders; refine based on that feedback; and gradually expand from there.” 

To get started, try something simple and high-impact, like Aircall’s AI Voice Agent that handles frequent customer questions. It’s incredibly easy to implement, as you can set it up in minutes, and it helps boost agent productivity and frees up their time to address more complex customer inquiries. 

From there, look at what’s working and what’s not. You might find opportunities to add AI solutions that predict customer behavior and analyze customer sentiment. Eventually, you can scale up to a more integrated approach where you implement AI across your channels to create a smoother, more personalized omnichannel customer experience.

The key is to treat it like a learning process, not a launch. 

4. Connect your entire communications tech stack

Using AI in customer service interactions works best when the technology has the full picture. That means connecting all your communication channels, from voice and email to chat and SMS, so your tools can follow customer conversations wherever they happen.

A scattered tech stack makes it harder for the technology to analyze customer conversations and get the context it needs for quality support. But when your systems are unified, AI tools can step in to orchestrate the flow of conversations. It knows when to escalate, who to route to, and what context to keep front and center.

Consider this scenario: a customer starts their query in email, follows up via WhatsApp, and finishes on a call. When your communications tech stack is connected, they don’t lose momentum or have to repeat their issue. This kind of continuity will help you achieve seamless handoffs, faster responses, and less back-and-forth.

5. Combine human and AI efforts for maximum impact

​​AI in customer service doesn’t need to replace human agents to be useful. In fact, it works best with them. The most effective teams use a “human-in-the-loop” setup: AI handles repetitive, low-effort tasks, while human agents step in for the interactions that actually need a human touch, like nuance, emotion, or complex decision-making.

“AI is incredible, but customers still want to talk to real people when things get complicated,” says Ernesto Pramasetya, Co-Founder of Giantfocal. “Always make sure there's an easy path to human support.”

Aircall’s AI Voice Agent, for example, jumps in to answer simple, routine queries like “What payment methods do you accept?” or “Can I modify or cancel my order?” That frees up your team to focus on trickier, more sensitive issues that require critical thinking or empathy.

This blend of machine speed and human connection creates space for faster responses and better conversations. Using AI in customer service helps you scale without sacrificing customer loyalty.

6. Train AI with contextual, business-specific data

AI is only as smart as the data you give it. If it doesn’t know your customers, it can’t help them properly. That’s why training AI with your actual business context (like purchase history, sentiment, and past customer interactions) is so important.

“Your product and your customers are always evolving, so make sure your AI reflects that by feeding it fresh data,” underlines Pieter Wellens, CTO and Co-Founder of Apicbase. When you operate with a connected customer communications tech stack, this can happen automatically.

7. Build an AI governance framework for responsible use

AI in customer service is powerful, but with power comes responsibility. Data privacy and AI laws are constantly evolving, and businesses must have a plan to use AI ethically and stay compliant.

An AI governance framework helps you track data use, ensure transparency, and protect customer privacy. And be sure to let customers know when AI is part of the conversation, or if their data is used to train AI. This builds trust and helps you achieve compliance with these regulations. 

Remember, compliance affects your reputation and your bottom line, and responsible AI use means thinking beyond technology. It’s about ethics, transparency, and respect. And that’s how you maintain trust with your customers. 

8. Monitor AI performance and adjust continuously

AI needs constant tuning to stay sharp, and it isn’t a “set it and forget it” tool. To measure success, keep an eye on KPIs like deflection rates (how many queries AI handles without human help), customer satisfaction scores, average handling time (AHT), and sentiment analysis to understand how customers feel about their experience with AI agents and chatbots.

But don’t stop there; listen to feedback from both your agents and customers. They’ll be able to spot issues or opportunities that numbers don’t show.

Collect feedback through quick surveys, agent check-ins, call transcripts, and conversation trends. Use those insights to retrain your AI models and fine-tune responses.

Discover advanced AI for voice-first customer communications

The best practices we’ve covered are essential in helping you create smoother, faster, and more personalized AI-powered experiences that have a positive impact on the customer experience, improve service quality, and take pressure off your agents. 

As a voice-first, omnichannel platform, Aircall leverages AI to make your team’s life easier and your customer experience smoother. 

AI Voice Agent from Aircall is designed to handle routine requests so your customer service agents are free to focus on the more complex or sensitive conversations that really need a human touch. And AI Assist, gives you access to valuable call insights like key topics, conversation trends, and customer mood. 

“I was sold on AI Assist and championed it to our CEO. It’s been a game changer. With call summaries, we’re saving about an hour per agent per month on call reviews,” says Stephen Monarch, Director of Operations at Puls.

If you need smart, simple ways to bring AI into your customer communication strategy and take pressure off your team, turn to Aircall. 

Discover a voice-first, AI-powered customer communications platform that helps you hold better conversations. Get started with Aircall for free. 

Frequently asked questions about AI in customer communications

How do you set up CCM workflows?

To set up customer communications management (CCM) workflows, start by mapping out your customer communication touchpoints. Next, define the steps each interaction should follow, including who handles what and when. Then, look for opportunities to automate repetitive tasks with AI or software tools, like routing queries or sending follow-ups. Finally, test your communication workflows, gather customer feedback, talk to your team about their experience, and tweak as needed to keep things smooth and efficient.

Which channels should CCM include? 

The best CCM strategy covers all the communication platforms your customers engage with, such as email, live chat, social media, SMS, and WhatsApp. Having all these channels connected means your customers can reach you however they prefer and you get a complete view of their journey without information siloes or context gaps.

How is AI used in customer service?

AI is used in customer service to handle routine customer queries with chatbots or voice assistants, so your team isn’t bogged down by simple tasks. It can analyze sentiment to spot unhappy customers early, suggest the best responses to agents in real time, and summarize calls automatically. 

All this speeds up support, adds a personal touch, and frees up your agents to focus on higher impact tasks.

What is AI in CRM?

AI in CRM means using smart tech to analyze customer data and turn it into useful insights and actions. It can predict what a customer might need next, personalize messages based on past interactions, and automate tasks like lead scoring or follow-ups to help build stronger, more meaningful customer relationships and drive loyalty and revenue.

What is the meaning of AI communication?

AI communication is all about using artificial intelligence to manage and enhance the way businesses talk with their customers. AI-powered customer service involves tools like automated chatbots and Aircall’s AI Voice Agent that can understand and respond to customer needs quickly and accurately. 

The goal is to make conversations smoother, faster, and more personalized without losing the human touch.

Published on July 17, 2025.