An Overview of Conversational AI
Hundreds of millions of people use Facebook Messenger, Kik, WhatsApp, and other messaging platforms to communicate with their friends and family every day. Millions more are experimenting with speech-based assistants like Amazon Alexa and Google Home. As a result, messaging and speech-based platforms are quickly displacing traditional web and mobile apps to become the new medium for interactive conversations. This overview of Conversational AI will detail how this advanced technology works and how it is a driver for digital transformation for businesses.
As users worldwide become more dependent and accustomed to these platforms, it’s no surprise that enterprises are rapidly adopting Conversational AI solutions to keep up with user interests and demands. While the ultimate goal of deploying these solutions is to revolutionize service experiences for customers and employees, it is important to know what Conversational AI and Chatbots are, how they help brands differentiate themselves within the market, and how best to leverage them.
How It Works
At its core, Conversational AI refers to technologies that leverage supervised and unsupervised natural language processing (NLP), understanding (NLU), and generation (NLG) to discern and interact with users in a natural, human-like manner. While these words are often used interchangeably, they differ in terms of function.
Natural language processing converts unstructured data into a structured data format that enables Conversational AI solutions to understand and derive meaning from natural human language in any given context. It does this by identifying entities, word patterns, and ambiguities within a text, enabling Conversational AI solutions to process language accurately at high speeds. By making sense of human language, NLP helps Conversational AI solutions perform various tasks, such as assigning support tickets in the right categories or plucking out specific information within long textual pieces.
NLP also helps Conversational AI solutions grow more intelligent over time. Instead of relying on manual updates from support agents, Conversational AI solutions autonomously learn in real-time from every interaction, enabling them to identify trends and patterns within future support requests. By recognizing these patterns, Conversational AI solutions can differentiate or make associations between pieces of text, allowing them to expedite issue resolutions.
While NLP enables Conversational AI solutions to process human language, Natural language understanding, a subset of NLP, helps Conversational AI solutions understand the intent behind a user’s query regardless of how they phrase their questions. It does this by auto-classifying topics, analyzing sentiment, and extracting key terms within a text to define the function and meaning of words. By recognizing user intent, Conversational AI solutions can analyze the consumer’s needs to provide accurate responses to their support requests.
Conversational AI solutions can respond to these questions because of natural language generation, another integral subset of NLP. Leveraging NLG, Conversational AI solutions automatically produce appropriate textual responses to users based on structured data accumulated over time.
Why is Conversational AI Important?
Looking further into this overview of Conversational AI, it’s key to ask why this technology is so important. While the advanced capabilities of NLP, NLU, and NLG all sound fascinating, you might be wondering why they matter. How will these capabilities benefit business processes? What makes Conversational AI unique compared to traditional tools and solutions?
More often than not, service agents are bogged down by high ticket volumes, causing them to feel burnt out and unmotivated to do their jobs. Ticket resolution times are then delayed, causing employees and customers to grow impatient and disgruntled. Leveraging NLP, NLU, and NLG, Conversational AI solutions automate repetitive tasks and workflows that service agents traditionally perform. By relieving service agents from monotonous tasks, Conversational AI solutions not only enable them to become more productive and attentive towards higher priorities, but users also avoid having to wait hours or even days to get their issues resolved. By eliminating long user wait times, Conversational AI solutions ensure customers and employees receive the answers they need in a matter of seconds, leaving them happy and eager for future interactions.
Conversational AI solutions can also detect user emotion through sentiment analysis. With traditional solutions such as rule-based chatbots, users were stuck interacting with cold machines that failed to recognize urgency or emotion. In contrast, Conversational AI solutions can identify the customer’s tone to modify their behaviors accordingly, making their responses more natural, personalized, and human-like. For example, when a customer is frustrated or upset, Conversational AI solutions can recognize this and work to improve the customer’s mood. They can achieve this by becoming more sympathetic towards the customer or offering additional suggestions to resolve their issues. By facilitating back-and-forth conversations that mirror human interaction, Conversational AI solutions ensure every user receives a positive and engaging service experience.
Understanding the intent behind user queries also makes Conversational AI solutions beneficial to businesses. By recognizing the purpose behind a user’s question, Conversational AI solutions can provide customers and employees with fast and accurate resolutions. Ticket volumes will then decrease, enabling employees to have more time to do their work while empowering customers to solve issues on their own.
The implementation of Conversational AI solutions is also quick, easy, and hassle-free. While building custom Conversational AI platforms requires a significant amount of time and prep work, purchased Conversational AI solutions integrate immediately with existing knowledge bases and systems, eliminating the need for additional training or data cleansing. By deploying with minimal effort, Conversational AI solutions demonstrate value on day 1 for both customers and employees.
The Future of Conversational AI at-a-Glance
Today, instant availability and accessibility matter more than ever. Digital businesses are no exception to this. As more and more users now expect, prefer, and demand conversational self-service experiences, it is crucial for businesses to leverage Conversational AI to survive and thrive within the market.
Following are expert predictions from Gartner about how AI will transform digital businesses in the next five years:
“By 2022, 70% of white-collar workers will interact with conversational platforms daily (Gartner). $3.9 trillion projected AI-derived business value growth by 2022” (Gartner).
“By 2023, 30% of customer service organizations will deliver proactive customer services by using AI-enabled process orchestration and continuous intelligence” (Gartner).
“By 2024, AI will become the new user interface by redefining user experiences where over 50% of user touches will be augmented by computer vision, speech, natural language, and AR/VR” (IDC).
“By 2025, customer service organizations that embed AI in their multichannel customer engagement platform will elevate operational efficiency by 25%” (Gartner).
Aisera offers the most feature-comprehensive and technology-advanced self-service automation solution in the market, which blends AI Virtual Assistant technology, Conversational AI (cognitive search), and Conversational Automation into one SaaS cloud offer for IT Service Desk and Customer Services. You can book a demo for the conversational AI platform today!
Aisera’s proprietary unsupervised NLP/NLU technology, User Behavioral Intelligence, and Sentiment Analytics are protected by several patent-pending applications.