With the advent of robots and chatbots, every company is using artificial intelligence for mechanical tasks. However, it’s important to choose the right system before it becomes a bane rather than a boon
The growing popularity of voice-powered personal assistants such as Alexa and Siri have driven consumer demand for artificial intelligence (AI) systems. And businesses are racing to catch up. In fact, Gartner predicted that one quarter of customer service operations will use virtual customer assistants by 2020.
However, not all AI systems are created equally and choosing which system is right for your business 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. Particularly because every business has different needs, different intended use cases and different budgets, you must make purchase decisions based on your pre-defined requirements.
Fortunately, the AI market has matured to a point where we’re able to make clear comparisons. This allows us 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.
There are several features to consider when choosing an enterprise AI system. The following three provide an overview of important elements today’s AI systems can deliver and the implications of choosing a platform that won't offer them.
Delivering an empathetic response
Today bots are increasingly being used on company websites to resolve any issues customers have, while ensuring they’ll be greeted by an AI system that can communicate like a person. Whether they’re concerned about possible identity theft, or happy because they just won online sweepstakes, your AI system must be one that shows emotional intelligence.
In fact, this feature is emerging as one of the more important differentiators between AI tools and platforms in the market. One of the primary goals with AI is to mimic human behaviour as much as possible – including delivering emotional responses – so humans can focus on other work.
Customers who feel an AI system was unable to comprehend 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.
Implementing an AI system with the intention of communicating with customers and employees means a robot who responds, understands and even jokes the way humans do.
Look for an AI system that not only communicates the way humans do but also understands it and additionally one that can recall past experiences and reference those experiences in natural-sounding phrases. Humans speak using short phrases, exclamations and euphemisms and an AI platform should be able to recognise them. Your AI system should also be able to process information and ask for clarification in case it hasn't fully understood the query.
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.
To provide a consistent customer experience, your AI system should be able to store past conversations and bring those past interactions with them at any given time. For example, if Jane talks to your AI system from an iPhone on Monday but she continues through her desktop on Tuesday, your AI system needs to know who Jane is, what her query was and how the system can help. If Jane is forced to verify her identity and restate her issue during that second interaction, she’ll understandably feel irritated. Not to mention, this is a good way to make customers feel as though they're not appreciated.
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. Thus, a customer may jump back and forth which results in confusion for the chatbot.
Cognitive AI systems have the ability to receive information in any order or in the middle of handling a service issue. They triage the information by handling the most pressing concerns first and then come back to the other items later. For instance, if a customer calls to reset their password but in the middle of the conversation realises 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.
When researching AI for your company, it’s important to remember that not all AI products and platforms are the same or interchangeable. While some provide assistance via voice or are great at scouring data and answering FAQs, others are able to provide recommendations and perform transactions. The goal is to ensure that, whatever you invest in, you’re getting the most out of your AI system experience.