How can you use AI to make your customer service more efficient? Examples, tips and tools
Artificial intelligence both fascinates and frightens. We are fascinated by its prodigious achievements, but fearful when it comes to integrating it into our business. This fear is legitimate and even normal. You wouldn't let just anyone take on a role in your company, especially when it comes to looking after your customers. However, you should be aware that this revolution can be welcomed with equanimity. If AI is properly integrated, you will benefit from a much more responsive and agile customer service .
Just like the SaaS software we analyse and compare for you, artificial intelligence applications are particularly varied. So it's important to make the right choice if you want to see a transformative evolution that adds real value to your productivity and your brand image. Each example of the use of artificial intelligence in business that we present will help you to better visualise the different possibilities.
What is AI in customer service?
AI in customer service is not a robot that takes your place. Far from it! In fact, AI in customer service is a set of services that partially or fully automates certain tasks assigned to it.
Do you often feel overwhelmed when it comes to responding to customer requests, questions and complaints? Is your team struggling to cope with the flow of requests from different channels (website, social networks, email, etc.)? It's probably time to take advantage of the many benefits offered by AI. But before integrating these tools, it is essential to take the time to understand them.
A study carried out by Zendesk on the customer experience in 2024 found that 65% of CX managers believe that AI improves the customer experience.
✅ AI can enhance the quality of the relationship between your business and your customers. Paradoxically, despite its artificial nature, it brings a more human side to your interactions. This comes from the fact that over the course of exchanges, it learns and grows richer.
AI in customer service does not replace agents, whose empathy is a fundamental pillar. Artificial intelligence brings greater precision to exchanges and the processing of requests. This means better performance, but also an optimised workload for your employees.
How does AI differ from traditional automation tools?
Until the advent of artificial intelligence, the automatic responses and processing offered by businesses were based on traditional programming. More specifically, traditional automation works on the basis of predefined instructions. Each response responds to specific actions. This type of programme solves the problem of repetitive and time-consuming tasks, particularly in customer service.
Conventional automation quickly reaches its limits, particularly when the interaction becomes more complex. We all remember those chatbots and automatic responses that displayed inappropriate answers over and over again:
- " We were unable to identify your request ",
- " Can you rephrase it? "etc.
These requests were then systematically redirected to the agents, who could quickly find themselves overwhelmed.
With the arrival of AI, the processing of requests and queries has changed radically. Instead of rigid scripts, you now have tools that are capable of reasoning and taking into account a large number of parameters to produce personalised responses or treatments. AI can make completely autonomous decisions.
The other major advantage of artificial intelligence is its ability to process different types of data (text, images, audio, etc.) in a coordinated way. It can also link different tools, such as email, CRM and live messaging.
The main advantage of AI is its ability to adapt. Thanks to machine learning and deep learning, it can adapt to the context and analyse and enrich a database as it goes along. A question or request will thus give rise to a personalised response that is not scripted as in the case of traditional automation. The quality of AI's work is very close to that of a human.
How can AI improve customer service? 6 benefits
Reduction in response times
This is one of the first benefits of AI customer service. The speed with which information is processed means that your leads and customers don't have to wait for long. What's more, the quality of the responses offered is generally satisfactory, provided you choose the right AI for your company's specific needs.
As well as handling time-consuming tasks, AI can also take direct charge of a request and process it immediately. For example, if a customer asks for their invoice or quotation to be sent back in a new format, the digital assistant will do this without delay.
Today's tools also have the ability to interpret emotions through the tone of the text or audio call. The customer service AI can therefore quickly decide to adopt a particular tone to soothe, arouse curiosity, adopt a neutral tone, communicate in a cheerful way...
Optimised availability
Artificial intelligence is available 24/7. So you can count on this high-performance assistant to respond to your customers' requests at any time. Whether for :
- prospecting
- buying assistance
- after-sales service
- building customer loyalty.
What's more, AI can process several requests simultaneously. During busy periods such as the sales season for retailers, or the end of the year for accountants, for example, this availability is particularly useful for coping with work overload.
For companies with an international presence, AI makes it possible to ignore time zones.
Improved customer satisfaction
AI improves customer satisfaction in several ways. Firstly, thanks to its availability and responsiveness, it avoids the long waits that can irritate customers. AI considerably reduces, if not eliminates, the often frustrating long waits behind the keyboard waiting for a letter or on the phone trying to reach an advisor.
AI is capable of providing personalised responses down to the smallest detail. Depending on the role you assign it, it will be able to handle complex requests that respond precisely to customers' needs.
AI can also help customer services to reduce their error rate. From drafting an e-mail to tracking order numbers or providing technical support, it can be used as a framework or bulwark to ensure that interactions are as error-free as possible. It's important to bear in mind that these errors degrade the customer experience and ultimately affect customer satisfaction.
Optimising staff costs
As we said earlier, AI customer service will never replace agents, who are essential for guaranteeing a genuine, high-quality relationship between your company and your customers. On the other hand, this high-performance virtual assistance will help your team to better manage its workflow and redistribute tasks. This advantage is all the more appreciable when you have to manage multi-channel communications where information is pouring in.
First-level tasks that are particularly time-consuming and tiring for agents can be delegated to AI:
- message sorting
- initial responses
- handling complaints, etc.
The AI then routes the priorities to the agents concerned, with the possibility of a summary presentation of the various cases to make it easier for the support staff to get to grips with the situation.
Fully integrated AI improves quality of life at work. It also helps to improve organisation and management. The choice of tool must therefore be taken into account.
More personalised interactions
Artificial intelligence makes it easier to personalise automated exchanges. The system takes into account the customer's history and personal data to enrich the interaction, as well as adding to its knowledge base. This creates a closer relationship between your company and the customer. As a result, your sales will increase. The proof: according to a report published by McKinsey, 76% of consumers are more likely to make a purchase if the brand offers a personalised experience.
✅ A perfect example of this personalisation: the exchange of names lets your customers know that they are unique. AI can also suggest products and services likely to be of interest to your leads and customers.
The personalisation of automated customer service must be carried out with strict respect for the customer's privacy. You mustn't be too intrusive, or you risk driving them away.
Anticipating trends
Thanks to its predictive capacity and with the help of the customer database and the company's resources, AI can help the company to anticipate customers' future needs. This means, for example, that reminder letters can be sent automatically when a deadline approaches. By analysing customer habits, it is also possible to determine their needs, and so fine-tune commercial offers. This proactive approach represents a major gain for the company's development and improves the customer experience.
The course of a conversation also enables problems to be anticipated on the basis of the questions and responses provided by the customer. Anticipation means that problems can be solved before they arise!
What can AI do for customer service? 5 application examples
Example 1: Intelligent chatbots
In their appearance, intelligent chatbots have not undergone a revolution compared with their traditional counterparts. However, when chatting, customers benefit from a warmer interaction that takes precise account of their requests and queries. There are no longer any ready-made answers. Each reply is unique and benefits from the neural network that enables artificial intelligence to mobilise a large amount of data to compose its responses. The intelligent chatbot can be textual or vocal and is difficult to distinguish from a real agent for the tasks assigned to it.
Example 2: analysing tickets via NLP
Tickets are used to track individual problems. However, with the proliferation of customers, a company has to manage a large number of them, increasing the risk of forgetting and making mistakes.
Thanks to automatic natural language processing (NLP), tickets are analysed not by detecting keywords, as was previously the case, but by understanding the entire communication in depth. In this way, the AI can determine not only the context, but also the sentiment of the caller. Thanks to NLP, tickets are processed automatically, but more efficiently.
Example 3: intelligent routing of requests
The requests addressed to your company, whatever its size, are disparate. Some are even errors or unwanted messages that could quickly saturate your customer service department if they are not handled intelligently. Intelligence performs optimised routing of requests thanks to its deep learning capability. This will make it much easier for agents to deal with them, as well as classifying them in the CRM.
Example 4: automatic email processing
How many emails do you process a day? Up to a few dozen, it is still possible to devote resources to this. Beyond that, this time-consuming task is also costly if it involves one or more agents. Thanks to AI, messages can be sorted and filtered efficiently. It provides unique responses to requests that can be processed automatically.
The automatic processing of e-mails also enables you to qualify the entries in your database automatically, thanks to a reasoned extraction of useful information: name, address, profession, etc.
Example 5: voice assistants and self-service
Artificial intelligence considerably improves the quality of conversations with voice assistants. So forget robotic voices and pre-recorded answers. Your new voice assistants will respond to your customers in real time, really taking the time to listen. The language models that make up these responsive tools are in fact capable of understanding thanks to the performance of the servers and the considerable size of the databases that serve as their learning base.
For customers who decide to obtain self-service assistance, i.e. without the intervention of an agent, artificial intelligence is an available guide to help them through the process. Help them quickly find the right answer in your FAQ, direct them to a forum section where the solution is presented, or communicate the procedures directly to them using the chatbot.
How can it be integrated into customer service?
When we think of artificial intelligence, we think of the most famous, such as OpenAI's ChatGPT, Google's Gemini or Microsoft's Copilot. You can of course integrate them into your customer service, but not in the way they are presented to the general public. You also need to take into account the new tools, an increasing number of which are dedicated to customer service.
Here are the steps to help you integrate AI into your customer service:
Step 1: Conduct a needs audit
It's impossible to find the right solution without knowing exactly what your needs are. So it's important to carry out an audit. It's important to remember that artificial intelligence is not a miracle solution that can be implemented on its own. You need to adopt new processes to take full advantage of it. A preliminary analysis of your company in general and your customer service department in particular is essential!
Step 2: Choose the right tools or platforms
Once you've identified your needs, it will be easier to choose the right software, SaaS or CRM platform. Like the craftsman who chooses his tools, you need to opt for the right solution to improve your customer relations. As well as functionality, ergonomics and interface should also be taken into consideration.
Step 3: Favour a gradual roll-out
Forced implementation is always counter-productive, despite all the power of artificial intelligence. Integrate the chosen solution gradually. You need to identify any reluctance within your team. This will speed up the resolution of bottlenecks at the time of implementation. Don't hesitate to form an integration team and set up a pilot project.
Step 4: Measure the KPIs
Successful deployment requires monitoring to accurately assess the benefits brought about by AI and any reorientations and adjustments that need to be made. By selecting relevant KPIs (requests processed, customers satisfied, calls handled per hour, incidents resolved, etc.), you can fine-tune the performance of the artificial intelligence. The choice of these indicators will depend on your objectives.
Step 5: Optimise team training
Training is at the heart of the implementation of AI. Each agent is an integral part of the automation process, guaranteeing that any information not resolved by the tool is processed at the end of the chain. This stage will be an opportunity to reinforce the ethics within your company to reassure employees and communicate your CSR policy where appropriate.
7 software applications to automate your customer service
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 Freshdesk |  Zoho Desk |  Service Cloud |  easiware |  Service Hub |
|---|---|---|---|---|
| For companies with 2 to 5000 employees | For all companies | For companies with 2 to 250 employees | For companies with 2 to 5000 employees | For all companies |
| See software | See software | See software | See software | See software |
| Learn more about Freshdesk | Learn more about Zoho Desk | Learn more about Service Cloud | Learn more about easiware | Learn more about Service Hub |
Freshdesk
Freshdesk
Freshdesk is an AI customer service tool developed by Freshworks. It offers :
- simplified ticket management with automatic ticket closure,
- centralisation of requests from different channels in a single interface,
- agent collision detection: to avoid duplicate work.
Salesforce Starter
Salesforce's Starter suite is an extensible CRM that focuses on customer and lead management. It incorporates not only artificial intelligence, but also pre-refined data to improve the tool's ability to manage its tasks:
- e-mail management
- customer support
- lead analysis
- dispatching sales teams, etc.
Service Cloud
Service Cloud
Published by Salesforces, Service Cloud specialises in optimising tasks for agents. Your team members will benefit from :
- a unified interface for multi-channel communication,
- routing of requests
- the generation of high-quality automatic responses on the appropriate channels (SMS, Messenger, Whatsapp, etc.).
Zoho Desk
Zoho Desk
Zoho Desk is an integrated service that centralises a long list of functions such as:
- ticket management
- automated responses,
- interface customisation tools,
- an automated workflow that takes into account multiple communication channels (including routing calls to the available agent).
Mobile Service Cloud
Mobile Service Cloud is a SaaS offering with integrated AI that :
- optimises the conversion of multi-channel communications on a unified interface,
- integrates easily with popular frameworks such as Magento and Shopify
- integrates easily with CRM or ERP systems.
Easiware
easiware
Founded in 2008, Easiware is a SaaS company that has enhanced its customer relationship management tool with Mistral. The application offers
- a summary of exchanges with the customer (whatever the channel used)
- automated responses
- Real-time reporting and analysis
- interface customisation
- integration with CRM, ERP or telephony tools
Service Hub
Service Hub
Developed by the American company HubSpot, Service Hub connects information from multi-channel communications with sales and marketing data. This solution integrates :
- ticket management
- omnichannel messaging,
- Process automation,
- Conversation analysis with AI,
- Native integration with HubSpot CRM.
What are the challenges of using AI in customer service?
Some factors require human intervention
Customer service AI solutions considerably improve the workflow for processing data and communications. However, certain tasks will continue to be performed by agents, whose ability to analyse goes far beyond algorithms. Empathy, cultural heritage and experience are irreplaceable assets in your team. AI is a first-level tool that will optimise the workflow. The agent acts as a control element to handle the most complex cases.
Ensuring proper data protection
The law requires personal data to be respected. This also applies to customer service AI. Only consented information can be used to enrich and serve artificial intelligence. The software solution selected must guarantee the protection of this sensitive data.
Dehumanising the relationship between supplier and customer
Artificial intelligence is powerful and can simulate a human attitude in many respects thanks to deep learning. This raises fears of a dehumanisation of the customer relationship as solutions are developed. It's up to your company to determine the place given to the human element, but it's important to remember that the general public is now looking for authenticity. This parameter must therefore be taken into account when determining the proportion of automation.
Lack of transparency in algorithms
AI algorithms are complex, making it all the more difficult to understand their operating model. What's more, designers are rarely transparent about how the information used for deep learning is collected. In the near future, the challenges will be both ethical and regulatory, to ensure greater transparency.
Towards a customer relationship enhanced by artificial intelligence
Customer service is undergoing a metamorphosis with the arrival of AI in data processing and workflows. To make AI an effective customer relationship management tool, we need to take the time to understand the various issues involved. This will make it easier to identify the best solution for your business.
But beyond the technology, the main issue remains the human element: AI must be designed as a lever to improve the quality of interaction, not to replace it. By combining artificial intelligence, active listening and personalisation, businesses can build smoother, more responsive and engaging customer experiences, while optimising the resources of their support teams.
FAQs on AI in customer service
Which KPIs should be monitored to measure the performance of AI?
Here are the KPIs to focus on to validate the effectiveness of AI in customer service:
- Response time ;
- Resolution time ;
- Your team's occupancy rate for resolving a problem;
- Number of tickets handled;
- Satisfaction rate;
- Cost per resolution.
There are many other indicators to evaluate. The choice will depend on your objectives.
How long does it take to deploy a functional AI solution?
There is no predefined rule for the AI transformation of a company. Some solutions can be deployed in a few days, but require several months of training. Other software can be programmed progressively over several weeks. It all depends on the complexity of the project.
Can AI adapt to my multi-channel flows (email, chat, telephone, etc.)?
AI can be adapted to your multi-channel flows. In fact, that's one of its main advantages.
How is AI transforming contact centres?
AI benefits both customers and agents. For the public who contact the company, availability is optimised, as is the handling of problems. For your teams, the workload is relieved of time-consuming and often trying tasks.
Article translated from French