4 Mistakes to Avoid When Implementing Conversational AI

Let’s face it — businesses are struggling to keep up with consumer expectations. Customers want faster, more responsive service via every channel. Not only this, they expect to be able to transition seamlessly between channels. And meeting these demands can put an incredible strain on human resources.

That’s just one of the reasons businesses are increasingly leveraging conversational AI to better support their customer base. Using conversational AI, businesses can serve far more customers, without significantly increasing their overhead or overtaxing their customer service teams.

Soon, conversational AI and chatbots will be ubiquitous, and so powerful that choosing not to implement some sort of automated customer communication will put businesses at a real disadvantage.

But, there are a handful of mistakes businesses routinely make in AI implementation that you should watch out for. Here are our top 4 pitfalls to avoid:

1. Investing too much in the AI and not enough in the supporting ecosystem

Even though AI is the heart of any conversational AI platform, the supporting ecosystem is equally important. The data that the AI uses to learn and adapt, and the infrastructure that the AI itself is built on are both vital for the AI to function properly.

Also, remember that your machine learning programs for training the AI are part of the supporting ecosystem. Investing adequate resources to train your AI is mandatory.

The right supporting infrastructure will address talk-time latency issues by connecting your AI to a network that gives you a dependable connection and low enough latency for natural conversation. The AI platform may get most of the attention. But, the supporting infrastructure can make or break your user experience.

2. Using conversational AI for the wrong things

Even though conversational AI has many benefits, there are times when it’s simply not a great fit.

In situations where the customer knows exactly what they want, and just wants to get the task done as quickly and simply as possible, a conversational AI isn’t always a great tool. In fact, conversational AI tends to work best best in situations where the complexity of the task would make a GUI or touch tone menu too cumbersome.

Or, if there’s no possible way that the task could be completed with a fixed set of inputs — like a chatbot therapist — conversational AI is capable of helping customers through non-linear processes.

So, make sure that AI is the right tool for the job before you start building it. Otherwise you risk creating unnecessary barriers, and ultimately, frustrating your customers.

3. Creating an AI that converses awkwardly

This one may be the most challenging to solve, because emulating true human conversation is tricky.

But, you can usually avoid creating an awkward AI by following a few simple rules:

• Your AI must be clear that it’s not a human. It also needs to clearly articulate what it can and cannot do. Never try to fool customers into thinking they’re talking to a human. It’s just a fast way to lose customer trust.
• Construct your AI so that customers don’t need to constantly repeat information. Saying things over and over again really irritates people. So, make sure that your AI stores answers to previously asked questions and has access to customer profiles.
• Quickly gather customer intent. Your AI can’t help the customer if it doesn’t know what they need help with. So, set up your AI so that it can discern intent as early in the conversation as possible and start moving toward the solution efficiently.

Clearly, your AI doesn’t need conversational skills that feel truly human. Conversational AI just needs to be conversational enough that it avoids speaking mistakes that drive people mad.

4. Not planning for when your AI fails

No matter what, your AI will occasionally misunderstand or fail to understand what the user wants.

If the AI can’t understand what the user wants, your AI needs to either ask the customer to state their intent again or ask clarifying questions. However, it should only do this a few times. If the customer can’t communicate with the AI after a few tries, the AI should quickly route the customer to a human or to another communication channel.

However, you also need to build in a way for customers to tell the AI that there’s been a miscommunication. Sometimes the customer will speak to the AI, the AI will assign the wrong intent, and will start helping the customer with the wrong thing. In these cases, there must be a command that tells the AI there’s a misunderstanding, such as the customer saying, “Help,” or “Wait.”

If your AI leads the customer in circles or can’t understand customers, and there’s no way for the customer to communicate to the AI that there’s an issue, your AI will simply frustrate users and degrade your customer experience. Always build in ways to address communication issues as quickly as possible.

If you avoid these common mistakes, you’re well on your way to building an AI solution that can enhance — rather than detract from — your customers’ experiences.