We’ve all heard of artificial intelligence or AI. It has various applications in several industries. In fact, it has become an inseparable part of our lives. We see AI applications everywhere, from smart homes to chatbots. Thanks to artificial intelligence, machines have almost replaced humans. So, we can get more work done in less time. In this article, we’ll talk about conversational AI and its use cases. First, let’s take a brief look at what we’re going to cover:
- What Is conversational AI?
- What Are the Components of Conversational AI?
- Conversational AI Use Cases
- Benefits of Conversational AI
- Challenges of Conversational AI
What Is Conversational AI?
Conversational AI refers to any machine or software that can talk to humans. This definition may remind you of chatbots or voice assistants. But in fact, it’s not as simple as it seems. It uses natural language processing and machine learning to identify speech and interpret user inquiries. Unlike chatbots which offer predefined answers to FAQs, this technology analyzes speech and enables real-time human-computer interaction.
What Are the Components of Conversational AI?
As mentioned above, machine learning and natural language processing (NLP) are the main components of conversational AI. Machine learning refers to algorithms which constantly improve themselves so as to recognize future patterns. NLP is a field of AI which is used to interpret natural language. Here, we explain the four steps of NLP:
- Input generation: First, users try to communicate with an app or a website. So, they either speak or type their inputs.
- Input analysis: Depending on the input type, we can use either ASR or NLU to analyze the user needs. If the input is text-based, the application uses NLU (natural language understanding) to figure out what the user wants. In case of voice-based inputs, both ASR (automatic speech recognition) and NLU are used to identify what is being said.
- Dialogue management: After analyzing the user speech, the application uses NLG (natural language generation) to provide a response for user inquiries.
- Reinforcement learning: To deliver a better user experience in future, the application must make sure that the created responses are accurate.
Conversational AI Use Cases
When it comes to conversational AI, many people immediately think of chatbots. But this technology is not limited to chatbots. There are numerous areas where it plays an important part. From daily tasks like searching the Web to hiring employees, conversational AI has woven into the fabric of everyday life. Human agents no longer answer user questions across websites. Thanks to this technology, bots answer FAQs, provide personalized suggestions and help users with their purchase. Amazon’s Alexa, Siri, Bixby and other virtual assistants are tangible use cases of conversational AI. Moreover, this technology facilitates HR processes. With conversational AI, HR professionals don’t have to go through the hassle of recruiting candidates and training employees.
Benefits of Conversational AI
Clearly, this technology has made everything much easier. In fact, it has brought significant benefits to both businesses and customers. Here are some of the most important advantages of conversational AI:
1. 24/7 Customer Support
Businesses using this technology can provide around-the-clock service to their customers. Therefore, there’s no need for employees to be available 24/7. Moreover, people are usually impatient. They want their problems to be solved asap. Chatbots and virtual assistants can respond instantly to customer questions. This is pretty beneficial to businesses since they can deal better with impatient customers.
2. Cost Efficiency
As this technology eliminates the need for customer service staff, the number of employees in an organization greatly reduces. This results in lower company costs. Conversational interfaces enable businesses to offer service outside working hours. But it’s better to hire customer service employees as well. Talking to human agents can sometimes be useful since they can help customers in case of complicated problems.
3. Customer Engagement
Businesses use chatbots and voice assistants to provide customers with real-time answers to their questions. Conversational interfaces allow companies to deal with multiple customers at the same time. In other words, people don’t have to waste time waiting in a queue in order to connect to a live agent. As a result, such companies can deliver a better experience to their customers.
Challenges of Conversational AI
Although it offers several advantages, there are certain challenges to deal with. As this technology has not yet fully developed, businesses should overcome the following challenges:
1. Language Input
Voice assistants and chatbots are not smart enough to understand everything you say. To have a better interaction with chatbots or voice-enabled devices, it’s better not to use slangs. Actually, the way you speak and the phrases you use, can significantly affect this interaction. Therefore, when talking to a voice assistant, you should pay attention to your accent and pronunciation.
Ensuring user privacy is one of the most important challenges of conversational AI. As you know, this technology relies heavily on the data collected from the user. So, it is of the utmost importance that this information is kept secure. Creating chatbots or voice-enabled assistants, particularly with respect to user privacy, can get more people to trust you.
3. Discovery and Adoption
It takes time for people to get used to a new technology trend. Generally, people are reluctant to share their personal account data or medical information with others. When it comes to conversational AI, they’ll be interacting with a machine rather than a human. So, everything gets even worse. To overcome this challenge, you should educate your customers about the benefits and use cases of this technology.