The power of artificial intelligence (AI) often gets buried by the buzzwords surrounding it. AI can empower; it’s agile, and works at an incredibly fast-pace. All of this is true, but it can steer the conversation of AI’s applicability from real use cases and show what impact it does have.
AI is a useful way for businesses to optimize customer support and streamline existing workflows, bringing the future of automation, less manual and laborious day-to-day tasks to today. Think of AI like a partner: it doesn’t run the show, but exists as a collaborative agent in the overall goal of a business’s intent. For customer service, for example, a customer’s experience and support is of the utmost concern. Providing them with a strong interaction will keep them as returning customers, and perhaps they’ll bring more customers, too.
A key way to do this is with Agentic AI. An AI agent isn’t a chatbot, exactly, but it exists in the same ecosystem customers can tap for support.
Ahead, let’s look past the headlines and buzzwords around AI, and take a look at the top use cases for AI agents, an essential tool in the technology’s offering.
What is an AI agent?
Often, an image of a self-realized, sentient being (like a robot) is what comes to mind when one thinks of an AI agent. Self-driving cars would be another. In essence, an AI agent is an autonomous tool that can respond to its surroundings or situations and perform tasks based on the information it has. Because an AI agent has the ability to take in information, process it, and then act upon it, sentience often comes to mind. And while an image of human-like robots who can act on their own is compelling, that’s not what today’s businesses are generally using it for.
AI agents today, particularly in customer service, are used to streamline the customer experience with less live agent intervention. That can look like an AI agent having a conversation with a customer and being able to respond from more complex and specific information.
There’s an intuitive aspect to AI agents that doesn’t exist with other AI technologies (namely chatbots, which are scripted and used for more rigid interactions.) AI agents are run on technologies like machine learning, generative AI, large language models (LLM), and natural language processing (NPL). With all of that, an AI agent will then have a better chance of understanding and responding to a customer’s needs.
Top 8 use cases for AI agents
Let’s take a look at 10 of the top use cases for AI agents with a focus on customer service and support.
1. Personalized recommendations
Good customer service and support is often marked by providing a customer something without asking them if they want or need it. Like reading their mind. AI agents have the ability to do something similar: by having access to a customer’s file or the information they are feeding to the tool, an AI agent can provide additional product or service recommendations. This can be based on prior buying behavior, engagement with other products on a website, or giving a customer enrolled in a loyalty program options that those not enrolled won’t get.
2. Multilingual customer support
The world isn’t exclusively English-speaking. Nor is it exclusively any language speaking. There’s an abundance of rich, vibrant languages that people speak first, and may feel they best understand over any other language they loosely know. An AI agent—trained well and deeply—has the ability to provide a customer the kind of multilingual support they require in the language they choose, not what they are told to do.
By enabling AI agents to learn and process other languages from large datasets, customers then feel more satisfied and taken care. It’s important to continuously train the tool to understand different linguistic nuances and continuously strive to improve it.
3. Automation, not manual labor
There are so many ways AI and, in particular, AI agents can work to automate otherwise manual processes and tasks. This can look like scheduling in a calendar, capturing data, or processing and presenting data. For customer support agents who are speaking to customers, especially at length, AI agents can summarize the call from the agent’s notes, or transcribe the call, and keep a record of it for another agent so a customer doesn’t necessarily need to explain everything all over again.
Even conversations AI agents have with a customer are automated. They are more than a chatbot, which is a more scripted AI tool that can answer preset questions.
4. Ticket routing
While there are many benefits and use cases for AI agents that benefit the customer, AI agents can help the live customer support agents by routing and triaging tickets.
An AI agent has the ability to respond to the urgency of a customer’s ticket or request; prioritizing those that are in need of a solution fast—and it often requires a live agent to get a resolution—while working with the less urgent customer queries. This can lead to higher resolution rates.
5. Data collection and tracking
6. Information retrieval
One thing that chatbots and AI agents share a similarity in is information retrieval and assistance. The comparison sort of stops there. Where chatbots can provide a customer information, it’s often a script or formulaic. And that’s a great cost-saver because customers looking for basic company information or checking on a shipment and order or anything that can be easily programmed will save on time and money from live agents answering such queries. But AI agents have the ability to, while in conversation with a customer, retrieve relevant articles, data, and other types of information as a reaction to what the customer is saying.
7. Continuous availability
Try as many customer support centers do, they can’t all be available at every hour, in every timezone, every single day. But that’s not the case with AI agents that can help customers no matter what time of day.
AI agents become an incredibly useful partner for live agents’ “off-hours.” If a customer does need to speak to someone urgently, there’s a window of time to do so. Even if getting to a resolution is urgent, and an AI agent is there to do intake, they can then route the query to an agent as soon as one is available because of the technologies it’s run on (in order to respond to a situation) and how it’s programmed to route issues.
But it’s comforting to know and have an AI agent who can respond more intelligently, and compassionately, based on NLP.
8. Cost efficiency
One of the primary reasons AI technology has taken such a leap in recent leaps is because it’s a cost-effective solution. It’s not that AI is taking jobs. It’s that AI, and especially AI agents, are taking up the jobs that are perhaps tedious and laborious, and rerouting work to where live agents and other people can have the most impact.
An AI agent will have the ability to get through more customer queries than a live agent. By pulling up customer information from their file, and asking specific questions with the ability to respond and react, an AI agent can move customers through the support cycle much faster, and get to other customers with similar speed.
Conclusion
AI agents are a great option for many businesses looking to optimize operations with a digital tool. Like we mentioned before, AI agents act as a partner, not looking to take over. An AI agent can help customers find information they need, give them personalized recommendations of what they might want, transcribe calls for live agents to refer back to later on, and even remain available all day, every day in multiple languages.
