Conversational AI vs Operational AI vs Chatbots

By Ruth Favela
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You can’t deny the power that artificial intelligence has for scaling businesses, especially in customer support. 

As people, we want to do what we can to make our lives better and easier to manage and we should want the same for our teammates. 

AI has elevated the customer support space by making it easier for customers to get the support they need when they need it. 

We’ve seen artificial intelligence support automated answers to customers’ most asked questions. Whether customers are getting help from knowledge base articles or from a web widget that automatically sends a response, AI is making these solutions possible. 

Today’s AI technologies are more intelligent and contextual than ever before and can actually help you leverage your company’s stored knowledge to the fullest extent. AI can make it easier for your support agents to do their jobs and better serve your customers, resulting in happy customers who return to you time and time again and employees who are loyal to you. 

What can be confusing for some is understanding the differences between types of artificial intelligence and what they do. To ease some confusion, let’s talk about three technologies that use artificial intelligence to help make customer support easier for businesses: operational AI, conversational AI, and chatbots. 

What is Artificial Intelligence (AI)?

Artificial intelligence, also called “machine intelligence,” is intelligence displayed by machines. 

AI is usually seen in a machine or computer system that can perform activities that require some level of intelligence to be completed. 

It’s the theory and development of computer systems being able to perform tasks normally requiring more than basic machine intelligence, such as visual perception, speech recognition, decision-making, and even translation between languages.

When it comes to customer support, AI is being seen everywhere within it. As opposed to more traditional software, customer support AI is a system that does not need to be explicitly programmed to return specific outputs according to some given input. 

AI, however, can be separated into different types with functions that differ from one another.

Conversational AI vs Operational AI 

Recently, leaders from Forethought, ArenaCX, and Zendesk met to discuss this very topic

According to Alan Pendleton, CEO and cofounder of ArenaCX, “We have AI for operations and AI for conversations.” 

AI for operations, or operational AI, often means using natural language processing to automatically tag and triage incoming customer inquiries, building more accurate demand forecasts, routing and distributing workload optimally among teams, and empowering agents with recommended knowledge and responses. 

AI for conversations, or conversational AI, typically consists of customer- or employee-facing chatbots that attempt a human conversation with a machine. 

Operational AI helps perform an operation or a function that allows for knowledge intake, while conversational AI helps with the back-and-forth between customers and agents for any customer support interaction. 

AI for operations and conversations eventually have to work together to make the entire customer support process successful for both agents and customers. Operational AI can help triage and label tickets while conversational AI can carry the back and forth between customers and the AI. 

So then how do chatbots come into play? 

How do Chatbots Fit In with AI? 

A chatbot is a computer program that simulates human conversation, either via voice or text communication. Organizations use chatbots to engage with customers alongside more classic customer service channels such as via socials, email, and text. 

In customer service, companies use chatbots to boost agent productivity while enhancing the customer experience to make for happier customers who are satisfied with what you can offer.

There’s a big difference between a chatbot and genuine conversational AI, but chatbot experiences can differ based on how they function. Traditionally, chatbots are set to function based on a predetermined set of if-then statements and decision trees that give answers based on keywords. That is a rules-based chatbot. 

Chatbots were the first tools to emerge that utilized some AI technology. These days there are chatbots that leverage natural language processing and machine learning to understand what a user is searching for. 

The problem with traditional chatbots is they aren’t truly AI because they are rule based yet most chatbots claim they are AI when they don’t use NLP or ML. You only get an answer if you put in what the chatbot is searching for. When it comes to customer support, chatbots just aren’t enough to truly meet the needs of customers. 

With a chatbot, you’d have to be exact with your verbiage in order for it to spew out the answer you’re searching for. Here’s an example; say you’re trying to figure out the location of a package you ordered. The company you’re asking likely gets this question hundreds of times a day. 

If you ask the chatbot, “Where is my package?” then you’ll get an exact answer. But what if you ask something like, “My package is missing.” or “Item not delivered,” You may run into the problem of the chatbot not knowing you’re asking about package tracking. 

A step up from a chatbot would be AI for customer support in the form of a web widget that utilizes proper machine learning and natural language processing to understand the intent of a message being sent in. This form of a chat bot would understand what is being asked based on the sentiment of the message and not keywords that trigger a response. 

With the proper AI tools, messages that don’t explicitly say, “Where is my package?” will still be understood to be asking the location of an item. This goes a long way for many scaling customer support teams and enables them to automatically deflect incoming customer queries with artificial intelligence while still maintaining high customer satisfaction. 

What does Customer Experience Have To Do With AI? 

Now that you understand the differences in AI a little more, you probably want to know the impact AI can have on customer support teams and the people they serve. 

These days, customers and brands say they care more about the customer experience than ever before. 

And the fun thing about customer experience, is that every customer will be put through whatever experience you offer whenever they interact with your business. Their journey involves every interaction they have with your business and will take some strategizing to ensure a positive one. 

Improving your CX takes a lot of work, some of which may include: 

  • Researching customer insights
  • Asking for feedback 
  • Implementing CSAT and NPS surveys 
  • Gathering data, etc. 

Strategizing to meet customer needs requires you have the people and tools necessary to move with agility whenever it is needed. Customers are still facing many challenges when seeking support and are finding it difficult to overcome their pain points. 

What Next?

So if the experience you put your customers through matters more to them now than the quality or price of the product or service you offer, what are you doing to improve that experience?

With AI tools designed for customer support teams, you can improve the journey your customers go through whenever they need to interact with your business. 

Companies like Route have found solutions to their support issues with the help of customer support AI, making it possible for their support teams to deflect up to 40% of support tickets with automated workflows that serve customers right away. 

By 2035 AI technologies are projected to increase business productivity by 40% and you should join along for the ride! 

With CX playing such a large part in what companies offer, the time to strategize and improve yours is now. 

You can make the most of your strategy by looking into customer support AI solutions. AI solutions like those offered by Forethought are powered by machine learning and natural language understanding that can learn from your data and understand the intent of a customer inquiry.

If you’re interested in learning more about the intricacies behind operational AI and conversational AI, check out our webinar that features Alan Pendleton and Seth Earley, leaders in the CX and AI spaces. They have a lot more to say about the power of AI for conversations and operations. 

You can watch the webinar here or set up a time to chat with us to learn more! 


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