Chances are, you have interacted with a chatbot at some point in the past few months due to a significant increase in the adoption of AI technology. Gartner predicts that by 2022, 70% of customer interactions will involve emerging technologies such as machine learning (ML) applications, chatbots, and mobile messaging, up from 15% in 2018.

Chatbots are for more than just customer interactions – AI agents can help take enterprise-wide digital transformation to the next level and provide guided interactions to help customers solve their issues, resulting in optimized costs. But, before you can start thinking about how these helpful robots can propel you into the future, there are a few basics to understand.

What's the difference between a AI agent and Chatbot?

To understand how a chatbot or AI agent can improve your business, it's essential to understand these terms.

What is the difference? It might not be a simple answer.

While the terms chatbot and AI agent are sometimes used interchangeably, there is still a debate amongst industry analysts, experts, and the technology community on the definition. And it is important to note that although there isn't one definition everyone can agree on, we can still look at both concepts in terms of their functionality.

According to Chatbots Magazine, "… a chatbot is a service, powered by rules and sometimes artificial intelligence, that you interact with via a chat interface." This makes a lot of sense since the word itself is composed of "chat," which would indicate a conversational or chatter function, and "bot," which can refer to an application that can be programmed to automate tasks.

On the other side, if we look at "AI agent," the composition of words makes it seem that the functions should go beyond "chatter". This would also make sense since an "agent" is someone (or something) that can act on a person's behalf.

In other words, if you have ever used online customer support to resolve an issue with your phone bill or chatted with a service desk agent at your job to reset a password, you most likely interacted with a AI agent. This concept, however, should not be confused with call center agents that work remotely, who can also be called "AI agents."

Essentially, this technology can provide basic information to customers or employees, help guide the users through questions, and automatically reroute complex conversations or issues to an actual human agent if needed.

Where bots can help the business

It is no secret that one of the main uses for AI agents is to automate processes and reduce workload for support agents. Two common places to do this is in customer service and in the IT service desk. However, it is important to note that AI agents can be used in nearly any department enterprise-wide to facilitate the sharing of information.

How chatbots can help with customer service

From providing insights about a product order to automatically cancelling a financial transaction and issuing a refund, agents can provide customers with all the information they need so your customer service agents can dedicate more time to work complex issues. This helps provide a uniform message to the customers, increasing brand loyalty and creating a more streamlined experience.

Many retailers, like Amazon, Target, and 1-800-Flowers.com are now using virtual bots to assist customers during the buyer's journey. Through the use of artificial intelligence (AI) the agents can study the customer's behaviors and dislikes in order to personalize the experience during the buying process. They can then give customers product suggestions or recommendations and assist with tasks, such as we see in the image below.

 

How AI agents fit into IT service desk

Similar to customer service, AI agents can be used to help reduce the ticket volume of the IT service desk and help provide support to employees 24/7. They can also facilitate employees with IT services at an enterprise level and to any department within the organization.

For example, let's say that one of your employees is having issues with their computer audio and uses a AI agent to solve this issue. The agent should be able to ask basic questions such as "are you using headphones or your computer speakers?" and then determine what to suggest depending on the response. If the employee says that the headphones are the problem, then the agent could potentially send a request order for new headphones automatically without the employee needing to call the service desk.

What is the relationship between AI agents and Artificial Intelligence (AI)?

Artificial intelligence has been a hot topic in recent years. This isn't referring to the type of AI you might have seen in the movies (don't worry, no Terminator, I Robot, or Transformers will take over your chatbot). Rather, AI capabilities like machine learning (ML) and natural language processing (NLP) have become popular additions to many organizations wish lists.

Even the best out-of-the-box chatbot solution requires a little bit more to work properly. This is where AI capabilities, which "train" your AI agent on how to function, come in. Here is how they work:

But even with ML and NLP, these agents can't simply predict the information users are looking for, and this is why its success will also depend on where it obtains its information from.

Although not associated with AI, if your knowledge base does not have the right content, then the AI agent will not be able to analyze it and provide the most accurate information to users' context. Think about investing in your knowledge base and using a knowledge management tool as part of an ongoing initiative towards improving your user experience.

Things to consider when choosing a AI agent

At the end of the day, the purpose of your AI agent will define how you train it and what capabilities it should have; however, there are some aspects to take into consideration that could be deemed essential.

Omnichannel and Multiexperience Access – Users must be able to access agents from anywhere, including mobile apps, messaging platforms, web applications, or websites – regardless of their device or location.

Conversational Interface – Natural language processing (NLP) will allow agents to fill in the gaps when users write in less technical terms or use altered terminology, creating consistent conversations and providing a seamless user experience.

Response Accuracy Capabilities – Not only will filling in the gaps help with the conversation flow but with the use of machine learning (ML) the responses can be generated more accurately and relevant for users.

Automation Features – It may seem obvious but not all bots can execute user requests automatically without the need for a pre-programmed script—automation features are important because it's what helps minimize human agent involvement.

Software Integration – Incorporating the agents with ITSM tools, CRM platforms or knowledge management software allows it to exchange information easily between applications and even between departments in your organization.

With the above capabilities, AI agents can provide customers and employees with a consistent and interactive user experience.