How Do I Choose the Best AI System?

4 minute read

Don’t be overwhelmed by the number of AI platforms available. Not every AI system is built to handle your specific business needs. Read this article to find out the most important aspects of choosing an AI system, and how that choice impacts your business processes and customer experiences.

[Note: The topics and subjects covered in this article will be discussed in-depth during IPsoft’s second annual Digital Workforce Summit on June 7. See registration link below.]

Choosing an AI system can be a difficult task. With so many virtual assistants, chatbots, and cognitive agents on the market, it can be tough to decipher the difference between functionality and marketing speak. Fortunately, the AI market has matured to a point where we’re able to make apples to apples comparisons. By doing so, we’re able to determine which tools offer comprehensive functionality and which tools are still developing. This is especially true for enterprises that are looking to implement AI to improve business processes and customer experiences.

In this article, we’ll examine the features that you should consider when choosing an enterprise AI system. We’ll break down what each feature delivers, and the ramifications of choosing a platform that doesn’t have it. Keep in mind: Every business has different needs, different intended use cases, and different budgets, so it’s important to make purchase decisions based on your pre-defined requirements.

Choose these features for the best AI system experience

Empathetic Response — When customers come to your website to resolve issues, they want to be greeted by an AI system that is able to comprehend the tone of their communications. Whether customers are panicking because of possible identity theft, or happy because they may have just won an online sweepstakes, your AI system has to greet them in manner that indicates emotional intelligence. In fact, this feature is emerging as one of the more important differentiators between AI tools and platforms in the market, as one of the primary goals with AI is to mimic human behavior as much as possible – including delivering emotional responses – to free up actual humans for other work.

Customers that don’t feel as if an AI system comprehends the emotion behind their statements will ask to be transferred to human agents. This scenario is a waste of time for you, your customer, and your employees. If you test a solution that offers bland, middle-of-the-road responses to emotional statements and questions, you’ll likely want to look elsewhere.

Intelligent Understanding — If your intention is to implement an AI system that communicates with customers and employees, you’ll want something that responds, understands, and even jokes the way humans do. Customers become frustrated with AI systems when they feel as if their requests aren’t being understood, or if the AI system isn’t responding in intelligible words and phrases.

Look for an AI system that not only communicates in natural language and understands it, but one that can recall past experiences and reference those experiences in natural-sounding phrases. Humans speak using short phrases, exclamations and euphemisms -- you want an AI platform that can recognize them. You’ll also want to make sure your AI system is able to process information and ask for clarification if and when it doesn’t feel it has fully understood what’s being asked.

Context and Channel Switching — Although many customer interactions may occur in one setting, many conversations take place across multiple devices, on multiple channels, and at different time periods. It’s crucial that you find an AI system that can remember past conversations and bring those past interactions with them wherever conversations may occur. So, if Jane talks to your AI system on an iPhone on Monday, but she logs on with her desktop on Tuesday, your AI system needs to know who Jane is, what Jane wanted, and how the system can help. If Jane is forced to verify her identity and restate her issue during that second interaction, Jane’s frustration level goes up.

Additionally, your AI system must be able to switch from topic to topic without getting confused. Customers don’t understand that ordinary, entry-level chatbots can only receive and handle requests in linear format. So a customer may jump back and forth from topic to topic and confuse a chatbot.

Conversely, cognitive AI systems are able to receive information in any order or in the middle of handling a service issue, and triage the information by handling the most pressing concerns first, and coming back to less pressing items later. If a customer calls to reset their password, but in the middle of the conversation realizes that their credit card is being used by a thief, a cognitive AI system will interrupt the password reset, solve the credit card fraud issue, and then finish the password reset. A basic chatbot will be forced to finish the password reset before jumping into the credit card theft issue – assuming that chatbot has been programmed to do so. It’s possible the chatbot would need to elevate the issue to a human agent in order for anything to be done.

There is only one digital colleague on the market that offers all of these features with expert-level accuracy and emotional intelligence. That’s Amelia.

The Best AI System? Amelia

There is only one digital colleague on the market that offers all of these features with expert-level accuracy and emotional intelligence. That’s Amelia.

IPsoft’s Amelia is a digital colleague designed to provide emotional, multichannel, and contextually savvy assistance. Don’t take my word for it. Head over to to learn about how we train Amelia, her specific use cases in banking, insurance, and healthcare, and how you can build custom Amelia abilities to meet your specific business needs.

Please join us at the Digital Workforce Summit on June 7th, 2018. Complimentary registration here!

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