From the manufacturing and design industries to the legal and marketing sectors, there seems to be no industry or process that AI is not transforming and changing for the better. Sure, there are challenges, as expected from technology that is at its infancy. One that comes to mind is data privacy and transmission slowdown, but edge AI is addressing even that.
AI is also making substantial changes in the necessary human process of sending and receiving information or communication. The method of automating communication has become a day-to-day scenario in the form of conversational AI.
What is Conversational AI?
Chatbots, interactive voice recognition systems, mobile assistants, and voice assistants—all of them fall under the category of conversational AI. Their common ground? They all use AI to automate conversations, thereby creating more personalized user experiences.
Conversational AI uses a combination of powerful language technology, including natural language processing (NLP), speech recognition, and machine learning (ML). Computers can understand and respond appropriately to a person’s query made through text or voice inputs. And so, instead of waiting for another human being to answer questions, people can get instant feedback and answers from machines.
How Does Conversational AI Work?
The first step in the conversational AI process is for a user to send a query to the machine. He or she can do that via a smartwatch, a mobile device, or even a toy. The user intends to get a response or answer to a question such as playing an audio file or getting the directions to a shop.
Once the query is received, the AI system converts the message into a format it can read. Some use voice recognition, others use text recognition, and still others use a combination of both. To work, the machine needs to connect to a working application programming interface (API). An API defines interactions between the user and the machine. In simple terms, it translates the user’s query into a machine-readable question and the system’s response into a human-readable answer.
The response goes through dialog management, the process by which the machine matches the user’s intention for giving the query. Afterward, the answer is translated back to human-understandable language and synthesized to come out as either an audible or readable response.
Here’s a very simple diagram showing the conversational AI process.
What are the Common Applications of Conversational AI?
We already use conversational AI in our daily lives. We ask Siri to find the nearest automated teller machine (ATM), for instance. We can even tell Alexa to book us a flight. Because of conversational AI, we can converse with computers, and they can respond using our natural language. Below are some real-world applications of conversational AI.
Chatbots are the first thing that comes to mind when talking about conversational AI in the customer service industry. Customers can find instant resolutions, and time zones cease to be an issue. The workload of customer service representatives has become lighter as AI can resolve repetitive yet labor-intensive issues. As a result, customer service representatives can focus on more complicated problems, while simple customer queries are addressed by chatbots quickly.
The financial sector isn’t far behind when it comes to conversational AI. In fact, Bank of America launched a digital financial assistant called “Erica,” while HSBC has “Amy.” These banking chatbots can answer common customer queries, thus improving customer service while reducing the banks’ operating costs.
Aside from addressing customer concerns, banking chatbots can also help clients manage their finances better. Erica, for instance, can advise a particular account owner how much he/she can save based on his/her account balance and monthly spending habits.
According to a survey, 90% of consumers want to communicate with brands. Website chatbots can give prospective customers instant answers about product features, prices, and other details. Also, the average consumer uses at least three messaging apps on his/her phone, and companies can take advantage of this. For instance, social media chatbots can send promotional messages to the brand’s social media followers.
Even before the coronavirus pandemic, access to healthcare has been a major global problem. Patients need to wait for hours to be attended to by a physician. The doctor would then check the patient’s vital signs while talking about what’s bothering the patient. In the end, the doctor prescribes the necessary medication. In several cases, however, patients don’t really need to see a doctor.
Chatbots can assess patients, then give them the right prescriptions or schedule an appointment with a specialist if necessary, to unclog healthcare delivery.
During the health crisis brought about by COVID-19, where going to medical facilities is not ideal, the need for conversational AI in the healthcare industry becomes even more glaring. Conversational AI gives patients round-the-clock access to healthcare without exposing them to the virus. This benefit is helping governments manage the health crisis.
AI, in general, is helping the world fight against the coronavirus. The technology can help assess and predict the spread of the outbreak. It could also be instrumental in coming up with a vaccine. ML can also be used to combat coronavirus-related fake news by identifying tweets and posts of authorized experts only. That way, governments can obtain official and reliable information that they can convey to the public.
Conversational AI is predominantly used by businesses that want to take advantage of the innate human need for conversation. The technology is also proving very useful with the ongoing coronavirus pandemic that’s currently gripping the world. Used correctly, conversational AI can transform industries, ushering in a world of chatbots and mobile virtual assistants.