AI Virtual Assistants: Classification, How They Work, and Applications

In the digital age, the AI virtual assistant is gradually becoming a familiar "companion" in work and life. The development of artificial intelligence is transforming these tools into strategic solutions capable of automating complex tasks and reducing manual operations. According to Mordor Intelligence, the estimated size of the Intelligent Virtual Assistant (IVA) market reached $14.77 billion in 2024 and is projected to grow to over $60 billion by 2029, affirming the pivotal role of this technology in operational optimization.

However, to fully exploit the potential of AI virtual assistants, a comprehensive understanding of their definition, different forms, and main impact when supporting users is needed. What is an AI Virtual Assistant? What types of AI Virtual Assistants are there? What is their operating principle? These questions will be answered in detail in the following article by Viettel AI.

What is an AI Virtual Assistant? Definition and Related Terms

An AI Virtual Assistant is intelligent system software built on an artificial intelligence foundation. The application is designed to simulate human conversation, aiming to understand, analyze, and execute actions based on input requests using natural language (voice or text).

In essence, the AI virtual assistant is not just an automation tool, but an intelligent agent. It uses its ability to learn from a data repository to:

• Understand context: Remembering and referencing information from previous turns of conversation, creating seamless and meaningful interactions.
• Personalize: Learning the user's habits, preferences, and interaction history to provide the most suitable responses and suggestions.
• Execute multi-tasks: Having the ability to connect with and execute commands across various systems and applications (such as sending emails, scheduling appointments, or controlling IoT devices).

With the advent of Large Language Models (LLMs) and Generative AI, the AI virtual assistant can also engage in complex conversations, reason, handle unstructured questions, and communicate closely, like human-to-human interaction. The system can also take on tasks requiring creativity or complex information synthesis, and can even integrate image and video processing capabilities, allowing users to interact by pointing at objects or displaying visual data.

Differentiating AI Virtual Assistants from Chatbots and Voice Assistants

There is often confusion among tools integrated with artificial intelligence designed to assist humans; however, their differences lie in their scope and primary task execution capabilities, and you need to clearly understand this if you want to apply them effectively.

AI Virtual Assistant

• Provides comprehensive support, from searching information to executing complex tasks.
• Operates at the operating system or platform level, with access to and links with many external applications (Google Assistant, Siri).
• Executes commands and simplifies information retrieval in life/work.

Chatbot

• Deeply focused on a specific domain (e.g., only technical support, only answering FAQs).
• Typically embedded within a specific application, website, or messaging channel.
• Solves problems, provides information, and guides users through processes.

Voice Assistant

• Focused on processing voice input/output on devices.
• Tied to audio recording and playback devices.
• Controls devices and accesses information hands-free.

The AI Virtual Assistant represents the entire intelligent system, capable of multi-dimensional decision-making and command execution. In contrast, the AI chatbot and voice assistant are two specific forms of deployment, specialized by channel (text or audio) and purpose of use. In many cases, the AI virtual assistant utilizes both chatbot technology and voice technology to operate effectively across various channels.

4 Popular Types of AI Virtual Assistants Today

Currently, there are many types of AI virtual assistants being deployed in the market. Virtual assistants can be classified in various ways, depending not only on the interaction channel but also on the goals and functions they perform.

Voice-Based Virtual Assistants

This is the type of AI virtual assistant familiar to many individuals, operating thanks to the close combination of Automatic Speech Recognition (ASR) and Text-to-Speech (TTS) technologies, which allows users to interact hands-free via smart speakers or mobile phones.

Their implementation strategy focuses on processing audio signals to execute simple commands such as turning devices on/off or performing quick searches, prioritizing response speed and immediate convenience.

A prime example of a voice-based AI virtual assistant is Google Assistant on smart speakers, activated by command. You simply say, "Hey Google, turn on the living room light and raise the air conditioner temperature to 25 degrees," and the virtual assistant will be able to process the command, communicate with the IoT devices, and execute the task immediately.

Text-Based Virtual Assistants

This type of AI virtual assistant demonstrates the robust development of conversational AI technology, with interactions occurring through a chat interface or dialogue box. These tools leverage the power of Large Language Models (LLMs) to understand and maintain complex context, thereby generating detailed, creative content, or performing extensive analysis and information synthesis tasks.

Completely different from voice virtual assistants, text-based AI virtual assistants prioritize information depth and high analytical/creative capabilities, making them suitable for tasks requiring complex reasoning.

Virtual Assistants for Enterprise Operations

Moving beyond the personal scope, AI virtual assistants for enterprise operations are researched and deployed to expand the supporting capabilities of AI in a professional environment. They are built on an LLM foundation but are fine-tuned and deeply integrated via API into a company's internal systems (such as CRM or ERP).

Their core role is to translate employee requests in natural language into executable actions within the system. The difference lies in their ability to directly impact the enterprise's workflow and confidential data, automating multi-step tasks and optimizing employee performance.

Virtual Assistants Focused on Narrow-Industry Functions

These are highly specialized AI virtual assistants, representing a focus on a single field, trained on high-quality, verified specialized datasets (such as law, healthcare, etc.) to solve specific professional business problems.

The deployment of virtual assistants focused on narrow-industry functions demands near-absolute accuracy and the ability to clearly cite sources, such as the legal virtual assistant used at the Supreme People's Court or Viettel's virtual assistant for searching new administrative units. They clearly demonstrate the important goals of reliability, compliance within the specialized field, and the ability to maximally shorten the time required for searching and retrieving information.

How Does an AI Virtual Assistant Work? The 4-Step Process

The flexible and powerful way an AI virtual assistant processes information is created by a closed, sophisticated information processing procedure that occurs rapidly in an instant. Typically, whether interacting via voice or text, the AI virtual assistant adheres to 4 basic steps of operation to convert a human request into a meaningful action or response.

Step 1: Input Reception and Conversion

In the first stage, the AI virtual assistant receives the request from the user. For text-based AI virtual assistants (Chatbots), the data is received directly in character form. However, for platforms that operate based on voice (Alexa, Siri, Callbot), the system must use Automatic Speech Recognition (ASR) technology to convert sound waves into digital text.

This process is more complex because ASR must filter noise, process intonation, speaking speed, and different regional accents to create the most accurate text sequence possible, preparing for the next processing step.

Step 2: Intent and Entity Analysis

After obtaining the text input, the AI virtual assistant begins language processing using Natural Language Processing (NLP) technology. This is the most crucial step where the virtual assistant attempts to "understand" the meaning of the request.

This process is divided into two main parts:

• Intent Analysis: Determining the user's overall goal (e.g., the user wants to "set an alarm," "search for information," or "perform a transaction").
• Entity Recognition: Extracting specific information necessary to execute the command (e.g., "6 AM tomorrow," "weather in Hanoi," "500 thousand VND").

NLP analyzes the context, key keywords, and sentence structure to accurately decode the request, even when the user uses slang or incomplete sentences.

Step 3: Determining the Response and Retrieving Action

Based on the analyzed intent and entities, the AI virtual assistant determines the necessary action to take.

• If the intent is a simple information search, the system retrieves data from its knowledge base or external search engines.
• If the intent is to execute a task (such as scheduling an appointment or transferring money within an enterprise virtual assistant system), the system activates an API or a pre-programmed procedure in the backend system.

For Large Language Models (LLMs), this step also includes Natural Language Generation (NLG) to construct a coherent, conversational, and context-appropriate response.

Step 4: Response and Learning

Finally, the AI virtual assistant transmits the processed result to the user. If the response is via text (Chatbot), the result is displayed directly on the screen. If the response is via voice (Callbot), the AI virtual assistant uses Text-to-Speech (TTS) technology again to convert the text into audio with a natural intonation.

More importantly, every interaction, especially complex or failed requests, is recorded and analyzed by the Machine Learning system. This data is used to continuously retrain and improve the accuracy of the ASR, NLP, and LLM models in subsequent cycles, ensuring the virtual assistant becomes increasingly intelligent and serves users better.

Key Benefits and Impact of AI Virtual Assistants on Life

AI virtual assistants are reshaping how we work, interact, and live, creating sustainable core values for the entire digital economy.

Enhanced Productivity and Automation of Enterprise Operations

The greatest impact of AI virtual assistants lies in their ability to automate repetitive and time-consuming tasks. In the enterprise environment, virtual assistants not only help free employees from manual, tedious tasks such as data entry, inventory checks, or email classification but also contribute to optimizing the entire operational process.

AI virtual assistants can operate continuously without interruption, ensuring customer service or internal support runs around the clock regardless of time zones or holidays. This enhancement allows businesses to scale up services without proportionally increasing headcount, significantly reducing operating costs.

Furthermore, by processing data and executing tasks with superior speed and high algorithm-based accuracy, the AI virtual assistant minimizes errors caused by manual operations, allowing employees to focus their resources and intellect on strategic work that requires thinking, analysis, creativity, and more complex decision-making capabilities.

Personalizing the Experience and Enhancing Customer Service Quality

For users and customers, the AI virtual assistant provides a fast and customized interactive experience that suits their individual needs.

• Instant and Multi-channel Response: In the field of customer care, chatbots and voicebots provide quick responses across multiple channels (website, app, call center), resolving the majority of frequently asked questions immediately. This result helps increase customer satisfaction as they do not need to wait.

• Deep Personalization: The AI virtual assistant has the ability to analyze behavioral data, purchase history, and the preferences of each user to provide relevant suggestions for products, services, or content. For example, entertainment platforms like Netflix or Spotify use AI to personalize recommendations, while e-commerce sites use virtual assistants to display offers at the right time to the right target audience, thereby boosting sales and loyalty.

Impact on Personal Life and Daily Decisions

Virtual assistants not only serve businesses but also strongly support daily life, transforming technological devices into true collaborators:

• Work and Life Management: From setting alarms, scheduling appointments, sending emails, to managing smart homes (turning lights on/off, adjusting temperature), the AI virtual assistant helps users perform daily tasks quickly and efficiently.

• Support for Learning and Information Retrieval: LLM-based AI virtual assistants like Gemini or ChatGPT become tools for information lookup, document summarization, translation, and even academic consulting, helping users access and process vast amounts of information quickly and systematically.

• Support in Narrow Specializations: Particularly in high-precision industries like legal or healthcare, the AI virtual assistant helps professionals quickly search for treatment protocols and review legal documents, accelerating problem-solving time and enabling important decisions, indirectly improving community health and quality of life.

Conclusion

With their practical effectiveness and positive impact, AI virtual assistants are gradually becoming an indispensable digital infrastructure in the modern technology era. This platform redefines performance by automating tasks, freeing up human resources, and elevating the customer experience with superior personalization capabilities and 24/7 responsiveness. Utilizing core technologies such as Natural Language Processing (NLP), Machine Learning (ML), and Large Language Models (LLMs), the AI virtual assistant is an intelligent, flexible "digital collaborator," ensuring accuracy and speed in problem-solving.

In Vietnam, mastering this technology is key to creating an efficient digital administration and economy. To this end, Viettel AI has been developing a comprehensive AI virtual assistant ecosystem, with key products such as the Virtual Assistant, Data Analysis Platform, Digital Twin Platform, and more.

Contact us for more in-depth and detailed consultation on AI virtual assistants, their application, and management in the digital era.