Learn how to choose a AI agent

According to our definition, a AI agent's primary purpose is to help end consumers of a service or a product by resolving their issues faster and being available around the clock. Before choosing a AI agent, there are a few important attributes to consider. We list the top 5 here.  

 

1. Multi-channel support

For an ‘always on’ generation, it is important to reach them where they are. This means your AI agent should be available across websites, mobile apps, messaging platforms, and more. Such an omnichannel experience not only guarantees customer satisfaction but also increases your agent productivity and reputation with your clients.

 

2. Customization

The experience of customer support or self-service should be a seamless one. This can be achieved only when the end-user relates to your brand and can interact with it much like they would with a human rep from your company. A AI agent that comes with a customizable set of features is much more likely to work than an agent that looks like a third-party service. 

 

3. Multilingual support

In the business world where geographical boundaries are quickly losing their meaning, especially in the technology space, there is a need to cater to a global audience. That means language or culture can no longer be a barrier to entry. Fortunately, the currently available technologies help bridge this gap effortlessly. A AI agent that provides support for multiple languages offers immense value in choosing it. This feature can help cut costs while also enabling easy scalability of services. 

4. Contextual support

While using a AI agent, it is imperative to put your best foot (code?) forward. In other words, the end-user should not feel they are interacting with a computer program. Thanks to Natural Language Processing & Machine Learning, a AI agent can replicate a human conversation to an appreciable level. Therefore, it is important to keep an eye out on the technologies used under the hood. Also, learning about the AI agent’s use cases can be a deciding factor in the final decision. 

 

5. Analytics & Reporting 

There are a few AI agents that come with an in-built analytics feature. This will help study the behavior of the agent, vis-a-vis its conversations with end-users. It goes a long way to refine the problem-solving capability of the AI agent. It will also serve to optimize conversations efficiently. This can go a long way in reducing dependency on human agents while enabling them to work on mission-critical operations.

After deciding to go down the AI agent route to improve self-service, it is important to get the basics right. A planned strategy in deploying AI agents will ensure a near-seamless experience for all the stakeholders involved. Here are a few tips for a successful implementation of a AI agent in your organization. 

 

1. Create an executable plan 

Before starting to build a AI agent, identify the areas where it is going to be deployed. It is also important to spend some time understanding how the AI agent works under the hood. This will be useful in figuring out how to design your AI agent to fit your exact needs. During this phase, it is also crucial to communicate with the stakeholders involved and get feedback before moving forward. Another part of this first step would be to define roles within the organization clearly. This will increase efficiency and also improve adoption in the long run.

 

2. Know what to expect 

When starting a new project, it is always important to set the right expectations. For a AI agent, that means understanding the goals that are to be achieved by its implementation. What problem does the AI agent solve, and how does it do that? Will the VA do X or Y? Answers to these questions will help temper expectations and help draft alternatives if your project doesn't perform as expected. 

3. Define important metrics 

The next important step should be to define your success metrics. This will significantly help in understanding if you’re on the right track with a AI agent implementation. Setting benchmark rates for self-service adoption or resolution of service requests is a good way to understand the AI agent's performance. When auditing this process, these metrics will guide your results and help suggest improvements, if any.

 

4. Stick to your brand values 

Your AI agent is your service rep. It should match the appearance of your brand and also reflect your values. This can be achieved by designing the AI agent according to your brand design guidelines. For the values part, the AI agent should be programmed to interact with an end user in much the same way as your human agent would. It is crucial to identify vendors that have a customizable option for AI agents to execute this option. 

 

5. Execute and measure 

During the final phase of implementation, bring awareness about the process to improve adoption. Also, promote the features of the AI agent and the necessary use cases. Once the AI agent is live, monitor its usage to understand the user behavior, and tweak your build accordingly.

 

 

Read the next chapter on our guide on the AI agent use cases in ITSM.