Those of us who grew up before the digital revolution of the last couple of decades are familiar with the days customer service complaints were made via traditional ‘snail’ mail. Letters would get put in the mailbox and hopefully we’d get a call or a letter back to address our concern.
Today, getting resolutions to our customer service inquiries is a much quicker and less frustrating process, due in large part to the growth in availability and capability of conversational AI.
Conversational AI is a type of artificial intelligence that enables computer programs to engage in natural dialogue with humans. This technology allows users to communicate with machines in a way that feels more like a conversation than traditional forms of interaction, such as typing commands into a search bar. Conversational AI can be used to power chatbots, which are computer programs that can simulate a human conversation, as well as voice interfaces, which allow users to interact with devices and services using their voice.
Conversational AI is not a new concept. In fact, the first chatbot, ELIZA, was created in 1966 – that’s right, a long time before you had a personal computer at home or had a phone call answered by a digital agent.
ELIZA was a computer program that could talk to people in natural language by interpreting their questions and providing scripted responses. However, it wasn’t until the late 1990s that chatbots started to gain in popularity. This was due, in part, to the development of new artificial intelligence (AI) technologies that made it possible for chatbots to understand and respond to complex questions.
In recent years, the growth of conversational AI has been fueled by the rise of messaging apps and the development of artificial intelligence technologies such as machine learning and natural language processing (NLP). Today, conversational AI is being used in a wide range of applications, including customer service, sales, marketing, and website navigation.
Yes, conversational AI has been around in various forms for decades but it has only recently become mainstream with the development and growing popularity of chatbots and voice assistants.
10 years ago, conversational AI was mainly used in customer service and support to help customers with their queries. It was also used in personal assistants to help with tasks such as booking appointments and finding information. It was limited to these specific uses and was not widely used for other purposes because the technology was not as developed as it is today.
Back then, just a decade ago, conversational AI was only able to understand very simple queries and commands and could not hold a conversation with a user and did not have the ability to understand natural language. It has evolved a lot in just 10 years.
Today, conversational AI is used in various chatbots and AI virtual assistants you’ve heard of and might even own, such as Amazon's Alexa, Apple's Siri, and Microsoft's Cortana. These platforms are used to engage with customers and provide them with information or assistance.
They are valuable tools because of the advancements in machine learning and natural language processing that have increased their power and their utility. NLP allows these platforms to understand human speech and respond in a way that is natural for humans.
NLP became a factor in conversational AI development in the early 2010s. It was then that developers were able to create platforms that could understand and respond to human speech with a high degree of accuracy. Over the last decade, conversational AI has become more refined and user-friendly, making it an essential part of many customer service interactions.
The evolution in chatbot technology is largely due to the advancement of natural language processing (NLP). NLP has enabled chatbot technology to understand and interpret human dialogue more effectively, which has led to more realistic and lifelike chatbot interactions.
What’s more, chatbot development platforms have become more user-friendly and accessible, making it easier for anyone to create their own chatbot.
Chatbots that do not include NLP technology most certainly serve their own valuable purpose, often diverting questions that it can easily answer to free up agents’ valuable time. Conversational AI takes them to the next level.
Chatbots have always been able to interpret simple commands, but they have not always been able to understand natural language. The recent advancements in natural language processing helps chatbots to understand the full context of a sentence, rather than just the individual words. This allows chatbots to respond more naturally to human dialogue and to understand complex questions.
Not only can chatbots understand natural language, but they can also respond in natural language. This means that modern-day chatbots, that have the added benefit of conversational AI, can converse with humans in a way that is natural and fluid. This helps to create a more realistic and engaging user experience.
Chatbots are not only able to understand and respond to human dialogue, but they can also learn from it. By understanding the nuances of human conversation, chatbots have become smarter and better able to serve the needs of their users thanks to conversational AI. NLP helps chatbots become more realistic and more lifelike.
This evolution in chatbot capabilities makes them more user-friendly, more in tune with what you are saying and asking for, and they can have more realistic conversations. This makes for a better overall user experience as users can communicate more naturally with chatbots, and chatbots can learn more about what users want and need.
As chatbot technology improves, and as chatbots become a more popular part of everyday customer service interactions, they continue to improve and evolve to better meet everyone’s needs, most specifically, though:
Conversational AI can help your team be more efficient by automating simple tasks and providing customer support. Everyone is happier when work can get completed effectively and efficiently. It’s better for time management, better for steady workflow and better for triaging that which can be handled by a bot versus a human.
Conversational AI can provide a more personalized experience for your customers by understanding their preferences and needs. Customers are more receptive to engaging with an automated system if it understands them and can help them reach a satisfying resolution to their question, comment or concern.
3. Customer engagement
Conversational AI can help keep your customers engaged by providing an interactive experience that is fun and easy to use. They are much more likely to stay on the line and self-serve their way through the bot or directly to an agent, if they need to. This way, businesses are less likely to have customers get frustrated and give up their efforts to reach them for a resolution.
Conversational AI is still in its infancy in many ways, with a world of possibility and insight it has yet to reveal. That’s why we can expect conversational AI to be an even more important part of our lives going forward. It will become more natural to talk to AI assistants and they will be able to handle more complex tasks.
We will also see more AI virtual assistants being used in business and industry. It will slowly but surely start taking on more complex tasks such as providing more nuanced customer service needs or managing finances.
Customers will also be able to use AI virtual assistants to buy things online or book appointments. They will feel empowered to do more things on their own because of the ease and convenience of conversational AI knowing that they can get help when they need it and that it is safe and secure.
We can continue to expect advancements in natural language processing and machine learning that will help AI assistants become even more accurate and efficient. This will help to make the user experience even better and more natural. As the technology continues to evolve, so too will the ways that we can use conversational AI to make our lives easier. The future includes and will enjoy the benefit of conversational AI.