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What is conversational voice AI?

Updated: Jan 13, 2023

Young person standing in front of a microphone

Artificial Intelligence (AI) tech has been helping humans make daily life easier for decades. The built-in smartness of the technology helps remove common hassles while making everything more efficient.

For example, you don’t have to tap a button when you want to play a tune. Just say, “Alexa, play….” Plus, you can translate anything from a foreign language using an impressive collection of AI translation apps instantly!

Voice assistants and Interactive Voice Response (IVR) are now common AI technology that pales in the face of a new solution. Enter conversational voice AI!

Thousands of businesses are realizing the potential of using conversational AI to connect with their employees and customers.

Read on to explore conversational AI and the reasons it’s the ultimate tool to transform how you build relationships.

Understanding Conversational AI

Conversation Artificial Intelligence combines multiple technologies so computers and humans can communicate effectively and clearly via text or speech. At a basic level, conversational AI deciphers the meaning behind written or spoken input from a human.

Examples of text-based human-to-computer interactions include virtual agents and chatbots. Voice assistants, such as Google Home Assistant, Apple Siri, and Amazon Alexa, are notable examples of voice-first AI and speech-based interactions with computers.

The human language pattern is nuanced, while computer language has definitive rules in ones and zeros. Consider how long it takes an infant to learn their native language. This scenario shows that while human speech is complex, computers see everything in black and white.

Differences in communications styles with added nuance and texture make it challenging for computers to understand humans. Conversational AI bridges this communication gap to provide users with beneficial and natural interactions.

Uses of Conversational AI

Conversational AI has many uses across all industries.

From security to marketing to customer service, this intelligent set of technologies is helping businesses connect with their employees and customers. The technology is, in fact, a critical piece in the digitization efforts of most organizations—especially after the COVID-19 outbreak.

However, developing and deploying target-specific conversational AI initiatives offers high success rates as opposed to rushing a product to the market. Your organization must tailor the technology to your unique requirements rather than relying on plug-and-play solutions, such as voice assistants and chatbots.

The advancement of this technology is bringing along new opportunities. Current applications are already prevalent in the following industries:

  • E-learning

  • Advertising

  • Automation

  • Marketing

Advanced conversational AI not only lets us use voice to instruct or ask machines questions, but you can also use AI to hold hyper-realistic conversations with users.

Voice-Based Conversational AI

The technology is developing and allows voice-based natural conversations between machines and humans.

The 2011 launch of the smart voice assistant Siri is liable for the wide acceptance of voice artificial intelligence. Fast forward to 2022: over 63% of adults in the U.S. use a voice assistant on their smartphones, TVs, cars, and household appliances!

Customer Service Turns to Voice Automation

Text chatbots can help companies reduce the cost of handling calls from customers. However, research shows only 37% of businesses successfully steered support volumes to chatbots in 2019. What’s been happening is an increase in traffic to contact centers but reducing the hold time by 53%!

These statistics show that your customers prefer calling and will continue doing so. Voice automation is an excellent platform that can help your company deliver above-par customer experiences at lower costs.

Challenges of Creating Voice Conversational AI Against Text

Replicating how humans hold conversations via voice interfaces is difficult. Slang, topic changes, and interpretation are all things humans do in a single conversation, increasing the complexity for machines.

Smart virtual assistants must understand what a user is saying and offer an appropriate response to keep the conversation moving towards a resolution.

Until recently, the conversion from text AI to voice AI has been difficult due to:

  • People use different language when they type

  • People have different speech cadences and accents

  • Voice options don’t offer a graphical user interface but rely on spoken utterances

The only way to overcome these challenges is by using a set of technologies specifically for voice-based interactions.

Technology Powering Conversational AI

The conversational AI’s unique ability to understand user response nuances and context is possible with natural language processing and understanding, text-to-speech engines, and machine learning. The result is a lifelike experience for users.

Here are the components powering voice AI:

Natural Language Processing (NLP)

NLP is an AI sub-field helping computers process and understand human language, whether written text or speech. Computers also understand the context of conversations and user response nuances, also known as intent recognition.

Apart from recognizing speech and machine predictive typing and translation, NLP teaches computers to understand human language. Computers process the language and provide useful information efficiently.

Natural Language Understanding (NLU)

NLU is a sub-set of NLP. This artificial intelligence component interprets text and other unstructured language data.

NLU extracts from natural language inputs. The technology determines how the computer understands input from the user and decides the correct response for the context.

In this context, the intent is mapping between what users are saying and the action your conversation AI should take. NLU uses:

  • Speech-to-text (STT)—for converting spoken language to character messages

  • Text-to-speech (TTS)—for creating speech synthesis output

Natural Language Generation (NLG)

In another NLP sub-category, NLG generates natural language from a machine-representation system, such as a logical form or knowledge base. The technology converts data into something humans can understand.

Machine Learning (ML)

ML provides solutions based on multiple data sources. The technology connects the dots between several inputs and helps improve the quality of response as it learns.

ML makes conversational AI contextual. ML technology uses data and algorithms to improve understanding and interpretation.

How Does Conversational Artificial Intelligence Work?

Conversation artificial intelligence offers accurate and quick responses to user questions. While the responses are instant, conversation AI uses a multi-step process before providing the answers.

Along with the components in the section above, here’s a deeper look into the step-by-step working of voice AI.

1. Generating Input

The first step in the process is the user asking a question or inputting it into the system. Input may be:

  • Text, such as your website’s chatbot, Viber, Facebook, and WhatsApp

  • Voice, such as an online voice assistant and voice bot

2. Analyzing Input

The ML layer of a platform uses NLP and NLU to break down the text from input into manageable parts to extract words. When using voice artificial intelligence, automatic speech recognition (ASR) acts on the voice note to parse sound into something the computer can comprehend.

After acquiring text, the decision engine in the conversational AI platform conducts a speech analytics process to discover intent. The AI uses its training (dataset) to answer the questions while covering multiple utterances and contexts.

3. Generating Output

Since the AI understands the user’s question, it matches the query to the answer using NLG. The AI may interact with your integrated systems, such as the customer database, to find the user profile and previous conversations. This action helps narrow down the answer based on data while adding a personalization effect to responses.

Unfortunately, there are instances the AI won’t map intent with your database. In these scenarios, the AI will pass the conversation to a human agent for better results.

The AI will also convert the response from text to speech. So, users will hear the synthetic voice responses in real-time.

4. Learning Reinforcement

The self-learning component of conversational AI comes into play now. Based on user satisfaction metrics, AI uses ML to refine responses for the next interaction.

Each interaction offers your business plenty of data, with variations in utterances and intent for further AI training. The learning process means your conversational AI gets faster and more adept at offering responses, improving the interaction process with the computer.

Conversational AI Benefits

Using conversational AI offers companies and their customer's several benefits. The technology helps brands carry out meaningful one-on-one conversations with clients while collecting more data on their needs to improve sales.

While each industry has different goals, the benefits of adopting a voice-first approach are the same. Here’s a broad overview of the benefits for customers and businesses.

Benefits for Customer Service

Your customers are more familiar with technology and its speed, so they demand instant answers to queries while wanting more control over the process.

Integrating conversational AI into your customer service process is no longer optional. Here’s how using the technology helps your business stand out by offering the best experiences.

24-Hour, 7-Days-a-Week Efficiency

Conversational AI ensures all your communication channels are running 24/7. Constant and fast support is a critical quality for your customers.

It’s frustrating for your customers when they have to:

  • Wait for hours to solve an urgent issue

  • Explain the same problem to multiple operators

  • Guess if a product they want is available

Use conversation AI to answer common queries, including paperwork, purchasing, or technical support.

Improved Security and Privacy

You must protect customer data and secure their transactions when using digital channels. Excellent service also means including data isolation and protection to comply with auditing and privacy regulations and a security incident management policy.

Artificial intelligence is an excellent way to guarantee speedy threat detection and handling.

Win Over Your Customers

The best way to win over a customer is by offering efficient, timely service. People love brands that can deliver an exceptional experience as much as they value their service or product quality!

Answers to queries must be instant if you want the customers to come back and recommend your brand to others. If they don’t receive a service that meets their needs, your customers will look elsewhere.

Provide Answers Across All Channels

People prefer communicating using instant messaging or a favorite social media platform. You must answer all queries, whether customers contact you via WhatsApp audio or Instagram Messenger.

Adopting voice artificial intelligence across all channels allows you to offer a complete, personalized service for every interaction. You also stay true to the tone and voice of your brand. Enhance the experience by adding glamor to answers using forms, buttons, videos, or images.

Enhanced Personalization

A bot with conversation AI helps you gain a clear profile of each customer so you can offer them a service or product depending on their needs. This level of personalization will set you apart from the competitors.

AI integration is the best solution to provide the answer for each query in an empathetic way. The system will also help you make the best recommendations based on user preferences. Offering a personalized service increases the chances of converting prospects into loyal customers.

Benefits for Your Business

Using conversational AI can positively affect your brand in multiple ways.


Growing businesses deal with thousands of queries daily. The added burden on your agents means customers wait longer for answers.

Use AI to scale your support function by responding to and resolving more queries. The technology will also help you reach a wider audience when it’s available round the clock on multiple channels.

Reduce Your Overall Customer Service Costs

Customer service automation helps optimize time for your agents. The technology can manage sales and after-sales service, automated processes, and handle your FAQs, so support agents only deal with complex requests.

Further, no-code solutions mean the time from implementation to use is short, even without bringing in an IT professional!

Improve Agent Efficiency

Your agents will no longer have to spend time on repetitive tasks, allowing for improved productivity and efficiency.

AI offers each agent the tools for answering customer queries quickly while personalizing the interaction. Your agents also have more time to handle challenging cases that improve business revenue.

Acquire Metrics for Business Continuity

Implementing conversational artificial intelligence helps you learn more about the target audience. You can then offer users what they want anywhere and at anytime. All this is possible using the data your system collects.

An essential component of true customer-centric service is real-time statistics, reports, and metrics on customer satisfaction. For example, some voice helper platforms offer you information on satisfaction, session transfers, and chat reports. The data you gain is vital in making the right business decisions.

Increased Upsell Opportunities

AI is big on customer preferences. It will offer the best up-sell opportunities depending on customer behavior.

Use Cases of Artificial Intelligence Conversation

The top three use cases of conversational AI are:

  • Customer support—Using intelligent automation, AI interacts with the customer at various points to answer queries.

  • Generating leads—AI automates collecting customer data by engaging the user in a conversation. These solutions are quickly replacing traditional methods of collecting lead information, such as forms.

  • Re-engaging customers—The technology can also send customers notifications, updates, and reminders, so a business re-engages with them.

However, each industry applies the use cases based on their requirements.

Industries That Adopt Conversational AI

Here’s how different industries are using voice AI.


Many healthcare institutions understand the value of hands-free conversational AI technologies.

For example, hospitals can use AI for:

  • Providing emergency tips and first aid

  • Improving a patient’s experience

  • Screening symptoms and diagnosing diseases

  • Advising on nutrition

  • Streamlining appointment scheduling

Call Centers

Call centers are handling an endless stream of support queries. Most of the incoming queries and issues don’t need human intervention.

Conversational AI can help relieve over-burdened call center agents by providing an end-to-end resolution cycle. The technology does most common tasks without waiting on an agent to get back to the caller with the information.


Traditional banks need to provide customers with an intuitive and simplified experience. Conversational AI can help facilitate transactions, help with account servicing, and much more.

Some use cases of AI in banking include:

  • Sending out notifications and billing reminders

  • Assisting with mobile deposits

  • Helping customers check bank balances

  • Helping customers find the closest ATM


Conversational voice AI is making an integral impact on the eCommerce industry. The technology helps brands create lasting customer relationships by holding context-based conversations and selling more products.

Use cases for eCommerce ventures include:

  • Cross-selling and up-selling products and services

  • Making sizing suggestions

  • Answering FAQs

  • Finding specific products

  • Placing orders

  • Helping with product returns


The gaming experience is all about immersion in the action. However, the experience can be frustrating when gamers can’t talk to anyone when they run into glitches and bugs.

A voice AI chatbot can take the feedback and even complete some tasks in-game. For example, Fridai allows gamers to use their voices to perform functions, such as sharing clips, giving in-game level walkthroughs, and recording the screen.

Final Thoughts

The fastest communication mode for customers and businesses is real-time speech.

Conversational voice AI provides a secure, flexible, and robust means to service customers. Remember, voice technology is simplifying daily life via voice bots in business apps and smart speakers.

AI-enabled voice technology brings human connections to life, artificially. NLP and NLU-based neural processing in the technology is a powerful way to amp your business!

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