What conversational AI is and how it optimizes your customer experience

For a long time, chatbots were useless for business purposes. Communicating with them felt too much like a "robot". However, thanks to new AI models such as Generative AI (Generative AI) and Large Language Models (LLMs), however, this has changed dramatically. When used correctly, companies can automate important processes with conversational AI. The technology enables machines to communicate with humans in a natural way. To do this, it uses voice-based interfaces such as chatbots, virtual assistants or voice assistants.

We explain the components that make up Conversational AI, how you can use them in practice and how your business can benefit from them. We also show you step by step how to properly feed conversational AI with data yourself and provide further content on our platform.

What is Conversational AI?

conversational ai definition

Conversational AI is a technology that understands natural language (natural language processing) and responds to them to enable human-like conversations with users. Through the use of algorithms and machine learning (ML), it enables computers to interact with users in real time and answer queries by analyzing speech and generating contextual responses.

The term is a collective term for various technologies that use artificial intelligence to conduct conversations and includes well-known systems such as Siri, Alexa and various bots. Companies use conversational AI primarily for automated customer interactions on websites, via messengers and social media channels. It is used for both spoken and written language (scripted language) and is used in areas such as customer service, sales and personnel development.

Conversational AI in numbers

Conversational AI technology has had an impressive development that will not stop in the near future:

  • The number of interactions handled by conversational commerce agents has increased by up to 250 percent in various industries since the beginning of 2020.
  • While only 29 percent of all companies used AI in digital marketing in 2018, 84 percent did so in 2020.
  • In February 2022 gave 53 percent of all adults in the US say they have communicated with a customer service bot in the past year.
  • In 2022, 3.5 billion chatbot apps were used.
  • By 2030, Conversational AI will have a global market value of just over $32 billion.

How does Conversational AI work?

Conversational AI is an advanced area of technology that utilizes a variety of techniques and methods, including machine learning (ML), big data analytics, processing natural language (Natural Language Processing), speech recognition and synthesis as well as dialog management. These systems are trained with large amounts of data such as text and speech, enabling them to understand and process human language. By continuously learning from interactions, they improve the quality of their responses over time. Conversational AI enables chatbots, virtual agents and voice assistants to simulate human-like conversations and engage in interactive, meaningful communication with humans.


conversational ai components

Conversational AI consists of several components that work together to enable effective, interactive communication between humans and AI systems. These components include:

Machine Learning

The ability to learn and improve from experience is an important part of Conversational AI. Using machine learning, conversational AI can continuously optimize its responses and actions to achieve better results and adapt to user preferences. 

A decisive role is played by natural language processing (NLP, natural language processing). NLP is responsible for understanding and processing human language. It analyzes user input, extracts relevant content and translates it into a form that can be processed by the AI. NLP uses algorithms and models to understand syntactic, semantic and pragmatic aspects of language.

Speech generation

Speech generation produces understandable, natural-sounding, and appropriate responses. It can use prefabricated text modules that are dynamically assembled or create machine-generated texts based on context and user specifications.

User interface

The user interface is the channel through which the interaction between users and the Conversational AI Technology takes place. It can be a voice or text interface that allows users to make requests or give commands. The user interface can be integrated into various environments such as websites, mobile apps, chatbots or virtual assistants.

What is the difference between conversational AI and chatbots?

Conversational AI is an umbrella term for algorithms and models that enable machines to have human-like conversations. Chatbots are specialized applications or systems that use conversational AI to communicate with users.

A distinction must be made between a rule-based and an intelligent chatbot. A rule-based chatbot does not work with artificial intelligence. It is based on predefined rules. What this means in practiceWith this type of bot, users cannot usually enter text freely, but are limited to certain questions and answers. Rule-based chatbots are therefore not a form of conversational AI. Intelligent bots, on the other hand, are based on AI. Users can enter text freely and receive a suitable response. The bots automatically learn and develop through every communication.

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What are the advantages of Conversational AI?

The three most important advantages from which businesses with a support offering benefit are

1. increase in efficiency

Conversational AI helps increase efficiency. Automated processing of customer queries reduces the workload of employees and allows them to focus on more complex tasks. Routine tasks such as answering frequently asked questions can be taken over by chatbots, resulting in improved productivity and cost savings.

2. improvement of data analysis

Conversational AI enables better data collection and analysis. By interacting with customers, the technology generates valuable data that helps your business and the associated service to better understand customer needs and to better understand the needs of your customers. make informed business decisions. Analyzing this data enables companies to identify trends and continuously improve their products or services.

3. Scalability

Bots with a high level of artificial intelligence can - in direct comparison to humans - process an enormous volume of customer inquiries without compromising the quality of the interaction. This makes it possible to process simple customer inquiries automatically and invest the time of experts in valuable customer relationships, thus enabling them to act efficiently even when customer demand increases. Not forgetting the 24/7 availability of the technology, which offers support services even outside normal business hours (service automation).

What are the challenges of Conversational AI?

Conversational AI offers numerous benefits. At the same time, however, the technology also brings these challenges:

1. Voice Input

Regardless of whether the input is written or spoken, conversational AI always has problems with speech input. Background noise, accents and dialects are the main problems for AI. It is also difficult for the technology to understand human aspects related to voice input. It can only rarely understand cultural circumstances, tone of voice, emotions or sarcasm and react accordingly.

2. Privacy and Security

Conversational AI uses personal information to provide a personalized experience. This presents a challenge, as misuse of this data can lead to serious consequences. Companies need to ensure that adequate data protection measures are in place to protect user privacy and avoid potential security breaches.

3. User Concerns

Users may have concerns about the use of conversational AI. Some fear that the technology could replace their jobs. This concern is particularly relevant in areas such as customer service, where conversational AI tools can replace human interactions. Companies therefore need to ensure that they position the technology as a complement to human employees and augment their skills rather than replace them. Another user concern is the lack of transparency of conversational AI tools.

Many people want to understand how the tools make decisions and what data they use.

They said they were concerned that the technology could deliver erroneous results due to biases or insufficient information. Companies therefore face the challenge of developing transparent systems that can be explained in order to gain the trust of users. To this end, the findings of the latest research offer various ways to ensure the quality of the conversation even with very large AI systems.

How does Conversational AI improve the customer experience?

Conversational AI improves the customer experience (CX) through the use of advanced technologies and offers a variety of practical applications that increase efficiency and user-friendliness. Here are 7 examples of Conversational AI in practice:

conversational ai use cases customer experience

1. Customer Support

Conversational AI is increasingly being used in customer support to enable automated, personalized and efficient interactions with customers. Chatbots and digital assistants can answer questions, provide support and solve problems around the clock. For example, a chatbot responds to customer queries in real time on a company website, provides detailed instructions and seamlessly transfers the customer to a human agent if required. This leads to improved customer satisfaction while reducing the workload of the support team.

2. Internet of Things (IoT)

In the integration of voice control in IoT-The strength of Conversational AI is evident in the use of mobile devices. Users can control their devices and systems by voice command, which improves ease of use and the user experience. One practical example is intelligent household appliances that are activated by voice commands. They enable intuitive and efficient interaction that makes everyday life easier. In industrial applications, voice-controlled operation helps to increase efficiency and reduce errors.

3. Search Engines

Conversational AI technology enables a more natural and user-friendly interaction with search engines. Instead of typing in keywords, users can formulate their search queries in natural language and still receive accurate and relevant results. This advanced interaction method facilitates information retrieval and contributes to a more pleasant user experience.

4. Human Resources

In the area of human resources, Conversational AI supports the recruitment and onboarding of employees. Bots answer applicants' questions, provide information on vacancies and facilitate the entire recruitment process. They can also efficiently process internal requests such as vacation requests or employee training, which increases efficiency in HR.

5. Computer Software

Developers use Conversational AI models to create more natural and interactive user interfaces. This enables users to interact with the software via voice commands and perform complex tasks more efficiently. For example, an AI assistant can explain application steps within software or guide users through various functions, thereby optimizing user-friendliness.

6. Voice Assistants

Voice assistants such as Siri and Alexa are prominent examples of the use of conversational AI. These assistants offer a wide range of services, from managing appointments to controlling smart home devices. Their ability to have human-like conversations improves interaction and makes the use of digital services on numerous platforms more intuitive.

Instructions: Prepare Conversational AI in 4 steps

For a conversational AI to offer users and companies a high level of added value, it must be carefully trained with the right data. We show how companies can prepare an intelligent chatbot so that it can communicate effectively with users and meet their requirements. A Conversational AI tutorial in 4 steps:

  1. Find list of frequently asked questions (FAQs)

    Start with a thorough analysis of your (potential) customers' needs and requirements. Identify the most frequently asked questions. This can be done through user surveys, customer service records or feedback mechanisms. Capture these FAQs in a structured list.

  2. Develop goals for Conversational AI

    Analyze FAQs and support tickets and identify the most important goals your users want to achieve. Identify the intentions behind the questions and formulate clear goals for your Conversational AI. For example, a goal might be to provide information, offer support, or help users perform specific tasks.

  3. Understand and develop relevant keywords

    Based on customer goals, identify the keywords that appear in your users' questions and goals. This will help you better understand the vocabulary and context. Create a list of these words. This will serve as the basis for building the Conversational AI Model.

  4. Create dialog flow

    Based on the captured FAQs, goals, and relevant keywords, you can now create the dialog flow of your Conversational AI. Develop a structure that enables your AI to recognize user intent, generate the right answer, and respond to the user in a natural and understandable tone.

With this Conversational AI tutorial, you will lay a crucial foundation for automated customer communication.


Conversational AI significantly improves the customer experience thanks to its wide range of possible applications - from efficient customer support and intuitive control of IoT devices to personalized interactions in various industries, this technology offers numerous advantages. A structured approach is recommended for companies that want to integrate conversational AI into their business processes.

The Konfuzio AI chatbot can be embedded into your website without any programming knowledge and allows you to take advantage of the described benefits such as 24/7 availability, fast and consistent responses and a personalized user experience.

Would you like support with your digital transformation or the automation of your services?

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Jan Schäfer Avatar

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