The wonders of AI have expanded into mainstream fields to the point where they are intrinsically tied to all kinds of technological development. There is AI involvement in everything to the point where one even forgets it’s there. There are now AI power versions of most conventional technologies including the conversational AI used in most modern chatbots.
What Is Conversational AI?
Conversational AI is an artificial intelligence technology that allows users to have human interactions with a synthetic consciousness to interpret their meaning and an appropriate response. It utilizes machine learning, natural language processing, and large volumes of historical and linguistic data to mimic human communication.
It is a multi-lingual, self-learning, and self-improving mechanism, which can recognize human speech as well as textual input and can respond to it in a variety of languages. Conversational AI can be best described as a form of technologically advanced chatbots that are a new and improved version of conventional ones.
The technology is one that can improve traditional virtual agents and voice assistants, optimizing contact center solutions of the future. Although it has its limits, its functionality is developing rapidly.
What Is a Chatbot?
A chatbot, or a ‘traditional’ chatbot is a computer application that simulates human conversation either verbally or textually. An abbreviation of ‘chat robot’, it is a tool that is specifically programmed to solve a problem or tackle a set of queries.
An example of this is a contact center AI chatbot, which can provide consistent and basic customer service through email, phone, and social media. These are used by many organizations.
However, not all chatbots are AI-based. Many that are programmed for tasks of a more streamlined nature use pre-fed values, language identifiers, and keywords to generate a set of stable, automated responses. These are called rule-based chatbots.
Conversational AI vs Chatbot – What Is the Difference?
If both conversational AI and chatbots are primarily AI-powered, the question that arises is, how are they different? Simply put, conversational AI takes the chatbot functionality to a new, far more advanced level, in the following ways.
Multi-lingual
Conversational AI enables customers to interact with websites, devices, and applications in the language of their choice. Meaning it goes above and beyond what a conventional chatbot offers which are limited to question-and-answer based programming in a single language. Conversational AI enables users to communicate in multiple languages, using their natural language and word choice and the BOT will detect the language and respond back in the same language.
Multi-platform
The primary means of interacting with a chatbot is via text, while a conversational AI offers the option of fluent communication through speech, as well. This makes the latter a far more powerful and promising tool, in comparison to the standard chatbot.
This makes it the ideal software for omnichannel contact centers, as offering communication via text and speech makes for a seamlessly integrated means of exchange to support calls, chat, email, and SMS channels.
Multi-Functional
Conversational AI can process several conversations and requests simultaneously, while a chatbot may be unable to address two commands that have been given in the same message. This is best explained through an example.
If a customer reaches out to a chatbot with the following query, “I would like to withdraw x amount of cash, but the ATM swallowed my card,” the bot will simply ignore the second half of the message. After narrating the different procedures for withdrawing money, it will leave the second query unaddressed.
On the other hand, conversational AI can address all of the input at once, whilst making natural, human-like conversation. It can also remember preferences based on historical behavior patterns and choices, naturalizing and personalizing the interaction further.
What Powers Conversational AI?
The functionality is driven by the twofold force of natural language processing or NLP and machine learning or ML. Each of these components plays an important role in powering conversational AI.
Natural Language Processing
This process refers to the artificially intelligent conversion of an individual’s unstructured written or spoken command into complete sentences that can be analyzed by conversational AI. This allows the software to formulate the best possible answer, in a four-step fashion. These steps are:
- Input Generation: Customers input their verbal or textual query through an app, website, or phone call.
- Input Analysis: For text-based input, the conversational AI will implement natural language understanding (NLU) to derive its meaning and intention. For speech-based input, however, it will employ a combination of NLU and automatic speech recognition to assess the data.
- Dialogue Management: This stage involves the use of natural language generation (NLG) in order to curate an appropriate response.
- Reinforcement Learning: The data of each response generated is mapped and refined by machine learning algorithms over time, to ensure maximum accuracy and learning.
Machine Learning
A supplementary field of artificial intelligence, machine learning is comprised of a combination of data sets, algorithms, and features that are constantly self-improving and self-correcting. With more added input, the platform becomes better at picking up on patterns and using them to generate forecasts and make predictions. In simpler words, experience strengthens machine learning AI.
The Advantages of Conversational AI
Here are some of the benefits investing in conversational AI can guarantee.
Better Customer Engagement and Sales Prospects
The new age eCommerce culture demands real-time, 24/7 customer support and Q&A channels. Conversational AI may be a more feasible solution than relying on human labor, as they are more readily accessible, on company terms. Immediate provision of support streamlines the operations, boosts First Call Resolution Rate, and reduces average hold and handle time.
AI-enabled solutions are more efficient and unconditional. There is no ethical constraint regarding the use of AI as there is with the exploitation of the human workforce. Moreover, AI can personalize better than human beings, leading to a better customer service experience which, in turn, increases customer loyalty. AI can even score new customers by creating an outbound sale strategy that necessitates high conversion rates by observing customer preferences and behavior.
Scalability
Conversational AI offers better scalability and expansion prospects, as it is far cheaper to add supportive infrastructure to it, as opposed to recruiting and onboarding new resources. Especially while expanding to a different region or in times of unforeseen boosts in demand, this proves beneficial.
Cost Effective Solutions
It can be incredibly costly to staff the customer support wing, particularly if you’re aiming for 24/7 availability. Providing customer service through conversational AI interfaces can prove even more cost-friendly while providing customers with service when it is most convenient to them. Instead of paying three shifts worth of workers, invest in conversational AI software to cover everything, eliminating salary and training expenses. AI offers lifelong consistency, quality control, and tireless availability, for a one-time investment.