What is conversational AI – Definition, Benefits and Use Cases

In this article, we’ll explain what conversational AI is, how it works, and why so many organizations are beginning to use it.

What is Conversational AI?

Conversational AI is the artificial intelligence software that enables everyday devices like computers or smartphones to understand natural language. Conversational AI uses technologies like natural language processing, machine learning, and big data to do so.  By virtue of how your computer or phone processes speech, the software learns and discovers a person’s intent and responds accordingly. Rather than mechanically tapping the buttons and prodding the screen, conversation AI engages with you in a natural, conversational way. Conversational AI is the type of artificial intelligence that’s already widely available and expected to be a part of most future technology.

While most people think of AI in terms of robots and self-aware beings like HAL 9000, Conversational AI is a trend that has emerged and is projected to grow exponentially, harvesting on the need to improve customer experience.

The Benefits of Conversational AI

How long has it been since you got on the phone with an airline and attempted to be put through to a human operator? Many of us probably remember the frustration of getting through only to be transferred again, being given contradictory information, or being bounced from the automated menu to the automated menu and then back to the automated menu. Virtual agents and chatbots can improve many different aspects of a business, including customer service, sales, and more.

These are the main benefits of conversational AI:

• Increased productivity – Automated support is available 24 hours a day, seven days a week, and can handle simple requests, allowing customer service representatives (CSRs) to respond to concerns more quickly and reduce overall resolution times. Virtual agents also boost employee productivity by allowing human agents to engage in multiple messaging conversations at the same time, as well as handle simpler tasks and requests as they arise.

• Lower customer care costs – Because customer service has a high operating cost, this is a significant benefit for businesses. Conversational AI can handle more requests than humans, provide relevant and correct information faster, and improve accuracy and complexity over time.

• Brand messaging which is interactive – Apple’s Siri, Microsoft’s Cortana, and Amazon’s Alexa are all examples of conversational AI as brand messengers. Following this lead, virtual agents enable you to personify your brand and meet your customers within their preferred channel, moving beyond static display ads, web copy, or paid social to create a truly interactive experience.

• Improved NPS – Brief NPS surveys can be conducted at the end of a call with conversational AI, providing a quick and easy way to gauge the quality of your customer’s experience. Even if you choose to query your customers in another way, the ease and productivity that virtual agent messaging provides will improve your NPS score.

• A better employee experience – By handling simple requests like resetting passwords and checking delivery status, virtual assistants free up human agents to handle more complex issues and build customer relationships.

How Conversational AI Works

Conversational AI combines natural language processing (NLP), machine learning (ML), speech recognition, natural language understanding (NLU), and other language technologies to process and contextualize spoken or written language, as well as determine the optimal way to handle and respond to user input.

What is natural language processing, and how does it work?

Natural language processing is an area of artificial intelligence that allows computers to comprehend text and speech in the same way that people do. NLP allows computers to detect words, deduce purpose, and react in a human-readable manner.

NLP is comprised of four parts:

1. Humans interact with computers through text or voice. This is frequently accomplished through the use of a phone, website, app, or smart home device.
2. Natural language understanding (NLU) is used by the computer to determine the intent for text-based input. To understand text or speech inputs, NLU employs computer software. The computer uses NLU and automated speech recognition for voice-based input. The input translates spoken words into text, allowing computers to understand and process speech.
3. Natural language generation is used by the computer to produce a response. The response is a subset of NLP that turns computer data into natural language.
4. Machine learning algorithms are used by the computer to increase its comprehension and accuracy over time.

Conversational AI use cases

When we think of conversational artificial intelligence, we typically depict online chatbots and voice assistants with customer support capabilities and omnichannel deployment. The majority of conversational AI apps incorporate substantial analytics into their backend programs, assisting in the creation of human-like conversational experiences.

Despite its restricted emphasis, conversation AI is a highly valuable technology for businesses, assisting them in becoming more profitable. While an AI virtual agent is the most prevalent kind of conversational AI, there are numerous alternative industrial use cases. Several examples include the following:

• Throughout the customer lifecycle, online AI agents are displacing human agents. They respond to commonly asked questions (FAQs) regarding issues such as shipping or offer personalized advice, such as cross-selling products or recommending appropriate sizes for users, fundamentally altering how we think about client involvement across websites and social media platforms. Message bots on e-commerce sites with virtual agents, messaging programs such as Slack and Facebook Messenger, and duties typically performed by virtual assistants and voice assistants are all examples.
• Businesses can improve their accessibility by lowering entry barriers, particularly for people who rely on assistive technologies. For these populations, Conversation AI functions such as text-to-speech dictation and language translation are frequently used.
• Numerous human resource operations can be optimized through the use of conversational AI, including staff training, onboarding processes, and data updates.
• Conversational AI has the potential to increase patient access and affordability while also increasing operational efficiency and streamlining administrative processes such as claim processing.
• Today, the majority of households have at least one IoT gadget, ranging from Alexa speakers to wearables to cell phones. These gadgets communicate with end-users using automatic voice recognition. Amazon Alexa, Apple Siri, and Google Home are all popular applications.
• Numerous duties in an office environment are facilitated by conversational AI, such as autocomplete for Google searches and spell-check.

Conclusion

Businesses that embrace conversational interfaces will be better equipped to understand their customers. This means faster problem resolutions, improved satisfaction, and decreased costs. Visit this page to schedule a call with our team to discover how you can use conversational AI in your customer service.