In today’s digital era, businesses are increasingly leveraging conversational AI technology in order to improve the quality of their products and services. Startups and large corporations are trying to reap the benefits of this promising technology before their competitors get a share of the pie. This comes to no surprise when we look at artificial intelligence market forecasts. In fact, according to Tractica, the use of AI software is estimated to grow to $36.8 billion by 2025 with a projected compound annual growth rate (CAGR) of 56.8%.
A conversational AI is a set of technologies allowing computers to conduct human-like interactions with human users through automated messaging and applications such as chatbots. Conversational Artificial Intelligence helps a robot lead human users to a specific goal, and allows for human-like conversations between machine and humans on a large scale.
In essence, a conversational AI can be defined as the element responsible for the logic behind robot exchanges: it is the brain and soul of a chatbot, but also a range of applications.
Conversational AI is powered by Natural Language Processing (NLP). NLP focuses on interpreting human language, while developers present the basic framework for how a conversation can unfold. Simply put, conversational AI and humans work together to create a virtual conversational experience in real time through chatbots or conversational platforms. It is the evolution of artificial intelligence, which has learned to speak and listen.
A conversational AI platform is a tool that automates human-machine interaction and workflows. Developers can use it to build custom chatbots or virtual assistants and integrate them within their website/portal, social media platforms, messaging channels (Facebook messenger, Slack, etc.) and more.
Advanced AI conversational platforms such as Botpress’ use natural language processing (NLP), natural language understanding (NLU) as well as deep learning (DL) to allow humans to interact with websites and applications via text or voice. Thanks to deep learning, this technology constantly teaches itself through reinforcement learning and improves its user interactions.
Throughout history, communication has either been verbal, written, or visual. This allowed us to participate in many customer conversations and learn more about ourselves and the world around us. Conversations, in particular, require two different elements. Multiple people and a means of communication.
Fortunately, throughout the years and with technological advances, we’ve discovered new innovative means of communication. We have unlocked new ways to communicate directly with our technology in a conversational environment using chatbots.
Not only that, but they make our personal and professional lives easier. Indeed, today we can go on vacation and ask for a device to lower the blinds at home as if we were there, to turn on the air conditioning when we are about to arrive, to tell us how to say thank you and more.
Conversational AI works when the application receives data input from a human, which can be in the form of written or spoken words. If the information is spoken, then Automatic Speech Recognition (ASR) is used to transcribe the spoken words into text.
A voice or text input is provided by a human user to the conversational AI, usually through virtual assistants or chatbots.
Using NLU for text input analysis and ASR when dealing with voice messages, the conversational AI determines the intent behind the user’s message using in-depth analysis of the provided data. This requires an advanced linguistic analysis, and can only be offered by conversational AI.
Once the user’s message is analyzed and the intent behind the interaction is determined by the chatbot or virtual assistant, a response is formulated based on Natural Language Generation (NLG) or selected from the workflows / Q&A.
Every time a conversational AI interacts with a customer or consumer, it increases the size of the dataset used for training which will improve the precision of its understanding and responses to user inputs. Thanks to this, a conversational AI will continuously perform better, offering users better services and customer experience.
An application uses Natural Language Understanding (NLU), which is part of NLP, to determine the meaning of the text and the intent behind it. Once the dialogue is understood, the system uses dialog management in order to form a response based on its understanding of the text’s meaning. It could also use Natural Language Generation (NLG), the other element of NLP, in order to convert its response in a format that will be understood by humans. Following this step, the application sends its response to the user (either through text or speech synthesis).
Finally, machine learning allows the application to learn and improve its performances over time. Deep learning makes the machine more intelligent through each interaction, allowing them to continually improve their interactions with humans.
Conversational AI uses the following technologies in order to understand, react and learn from interactions:
Automatic speech recognition (ASR) is an integral part of Conversational AI, a technology that enables spoken language to be identified, which can lay the foundation for a positive customer experience. If the application cannot correctly recognize what a customer is saying, then it must respond. However, if it cannot recognize what one is saying about a product or service, then the app may not provide a good user experience.
This technology is used by conversational AI to understand how people organize their thoughts, feelings, language, and behavior. It is a subfield of computer science, artificial intelligence, and linguistics whose objective is to give a conversational AI the capacity to interpret text and simulate the human ability to understand the language. In simple terms, NLP analyzes the meaning and the customer intent behind the text using tools such as sentiment analysis.
This is used to form an intelligent response to a user query and offer a customer experience that replicated the one achieved by human representatives in customer service departments.
This technology focuses on the analysis and interpretation of patterns and data structures that make learning, reasoning, and decision-making possible without human interaction. It allows the user to feed a computer algorithm with a huge amount of data, from which the computer analyzes all the information and is able to make decisions and make recommendations based solely on the data entered.
Now that you know what a conversational AI is, how does it benefit you? Well, having "virtual agents" assisting your human agents can help in many ways.
There are various conversational AI applications:
AI chatbots are programmed so that customers type keywords in order to receive the appropriate answer to their query. AI chatbots use natural language processing (NLP) to analyze, understand and process human speech. Common online chatbots are the rule-based chatbot, the retrieval-based chatbot and the generative-based chatbot.
A rule-based AI chatbot answers human questions based on a predefined set of rules that can be straightforward or very complex. This type of online chatbot is limited by its set of rules, and will be inefficient when answering questions that do not match its rules, on which it was not trained. Therefore, this type of online chatbot doesn't always meet customer expectations and often works with simple questions.
A retrieval-based AI chatbot possesses a database of predefined questions and will use heuristics to find the most appropriate answer to a user or customer question. Search results are generated through means varying from simple algorithms to complex machine learning and deep learning. This system is good at predicting a set of keywords, but does not generate new content.
A "generative model chatbot" is a chatbot which doesn't use any predefined database, while Deep Learning is a model based on Machine Translation techniques. "Generative models" are typically based on Machine Translation and instead of translating from one language to another, they "translate" a request into an output.
It was initially invented to solve machine translation problems, although its success was later proven for processes such as summarization and question answering. They are able to help consumers with a wide variety of questions.
Virtual personal assistants’ applications use NLP and ASR to answer customer requests. However, these digital assistants are linear: they cannot carry context from one interaction to another for deep learning and reinforcement learning. Siri, Google Home, and Amazon Alexa are examples of virtual personal assistants.
Virtual customer assistants use a conversational AI system that is more advanced: virtual customer assistants are able to carry context from a conversation with one consumer to another. These virtual assistants are specialized in dialogue management, which is why they are used to improve customer service and help a consumer reach its goals.
Virtual employee assistants are specialized digital assistants that are purpose-built. These virtual assistants are used to automate processes and make enterprise operations more efficient. Both virtual customer and employee assistants use advanced conversational AI technologies.
If you’re using a chatbot, which is a conversational AI application that is less advanced, you’ve probably faced at least one of the following challenges:
When you’re dealing with sensitive data and personal consumer information, Conversational AI applications have to be designed in very secure ways to make sure that privacy is respected.
A lot of factors can influence the conversation between a machine and a human such as language, sarcasm, slang, etc. Conversational AI systems have to adapt to constant changes in communication to be able to keep up with human conversations.
Conversational AI applications are becoming easier to use but there are still people that are not 100% comfortable with using this technology, mostly because they have little knowledge about it. Educating your customers about it can help the technology be better received for people who are not familiar with it.
Conversational AI will drastically change our interaction with commerce online. It will affect all aspects of when, where and how you interact and communicate with your clients. With conversation based on Artificial Intelligence, you will hold seamless, synchronous conversations with your clients across any platforms they decide to choose to be using, no matter where they are located and the medium they are using. Conversational AI is the future of enterprise and customer interactions, and has proven to meet customer expectations across a wide range of industries.
Conversational AI platforms rely on data, context and intent to interact with users and manage dialogues. AI chatbots communicate with users in either written or oral language. They are designed to hold conversations with humans to provide them the information they need and perform the required tasks. Their use is unlimited: they can direct website visitors to the appropriate services, give customers detailed information about products, improve customer support, provide immediate resources to employees, schedule appointments, etc.
Chatbot platforms facilitate the communication between businesses and their stakeholders. The language that is used by AI platforms even takes into account emotional inputs in order to understand the real meaning behind messages. In fact, they are used in the healthcare industry to offer emotional support to patients. AI conversational technology such as AI chatbots can be leveraged by all types of businesses and institutions within a range of different sectors:
AI solutions are highly scalable. They are available in various languages and on multiple communication channels.
AI platforms collect valuable data and insights, which can help businesses improve their service and products. They can also navigate huge databases quickly and find the requested information much faster than a human.
Chatbots are operational 24 hours a day, 365 days a year. This improves your customers’ experience and satisfaction. You don't miss a single opportunity!
With task automation, employees are more productive and spend less time on pointless tasks. Plus, customers can find the information they are looking for faster.
They save companies a lot of money in the medium and long term by automating tasks and increasing operational efficiency.
AI platforms lean and become smarter and more flexible after each conversation they have with users.
Chatbots can record data, trends, and metrics in order to monitor interactions and improve their processes and responses accordingly.
Conversational AI platforms can easily be integrated within social networks and messaging apps (WhatsApp, Messenger, etc.) to carry out all kinds of procedures without having to change the channel, through mobile apps downloaded on mobile devices.
Artificial intelligence is one of the top emerging technologies. People are rapidly seeing its potential and value but businesses still need to grasp and understand the different uses of AI chatbots (ex: employee chatbots). The competition is fierce in this market but solutions still need to be fine-tuned.
Here are the main market trends surrounding conversational AI:
Businesses are making good use of conversational data and analyzing it in order to get into the minds of their customers and better understand their needs. This helps them improve the quality of their AI chatbot, services and products.
Most businesses initially implement chatbot platforms in order to improve the customer experience and later realize that they can be leveraged for internal use. Conversational interfaces are very useful for employees as they can provide immediate and useful information and perform automated tasks. This helps companies in a range of different fields improve productivity and efficiency.
Chatbots are gradually becoming a thing of the past, and with reason. Bots are tools that are built to perform automated tasks and map out conversations while AI-powered chatbots use machine learning to understand intent and context to provide the most appropriate answers. Plus, over time and through experience, they learn and improve the conversational experience.
AI platforms are more powerful because they can hold conversations with users and provide a personalized experience. Businesses and institutions are switching from bots to AI platforms because they are looking for more intelligent solutions.
We are increasingly seeing the emergence of open-source conversational AI platforms. Thanks to these platforms, collaboration is made possible so that developers and experts can work hand in hand to provide advanced solutions. This enables infrastructure optimization, task automation, knowledge sharing and constant advancements for AI conversational platforms.
Business owners that have heavily invested in technology have seen their projects fail due to lack of customization. They are now looking for flexible solutions that adapt to their changing needs. They want AI platforms that generate positive ROI and that are customizable.
If you are looking for a flexible, open-source AI conversational platform, Botpress is the best solution for your business. Don’t hesitate to contact us if you want to have more information regarding our services.
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Salaries are a significant expense for all businesses, and staffing an entire customer service department represents a large cost, especially from smaller enterprises. Conversational AI interfaces and virtual assistants can reduce business costs around customer assistance, while helping to keep customers happy during times other than your business hours. Chatbots and virtual personal assistants can respond instantly, providing 24-hour availability without the associated costs in salaries, training and equipment.
When interacting with potential or existing customers on the web, businesses can program conversational AI to handle various use cases. This ensures that interactions will be thorough and comprehensive, ensuring consistency and continuity; valuable human resources can also be available to handle more complex queries.
Large businesses are always looking to improve their customer experiences, as it is the key to creating loyal customers in the competitive online world. Since conversational AI tools can be accessed more readily than human workforces, this virtual solution allows customers to access support promptly while encountering less friction on their customer journey. Faster and easier engagement during customer interactions can lead to increased customer satisfaction and incidentally sales, recommendations and referrals. As satisfaction grows, customers will believe they offer stronger brand loyalty, and be more exposed to referral business.
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