In recent years, conversational AI such as ChatGPT has been gaining attention, leading to an increased trend of utilizing AI chatbots in contact centers. Many companies are interested in introducing generative AI chatbots but struggle to proceed due to a lack of detailed information.
In this article, we will explain the basic characteristics and types of generative AI chatbots, as well as the advantages and disadvantages of introducing them, and the key considerations for implementation. This article is full of useful information to help you understand what generative AI chatbots are and whether they are suitable for your company.
By reading this article, you will acquire basic knowledge about generative AI chatbots. We hope it will help you determine how well they fit your company’s needs and guide you in deciding whether or not to introduce an AI chatbot.
1. What is a Generative AI chatbot?
First off, let’s get to know some basic knowledge about chatbots.
1.1. Traditional types of chatbots
・Scenario type
A scenario-based chatbot is a chatbot that automatically responds according to a pre-set scenario and communicates with users. It provides guidance according to the set option patterns. Frequently asked questions are directed to FAQs, and questions that can be answered with standardized answers, such as fees, are automatically answered. If the chatbot can not answer questions, they will be handed over to staff.
・FAQ type
An FAQ chatbot is a type of chatbot that automatically displays the most appropriate content for the user’s input by comparing past usage data with accumulated articles. Basically, it has a simple structure that responds to all inquiries with specific content recorded in the system, but by preparing a variety of content, users can refer to content that meets their needs and quickly resolve their problems on their own.
1.2. How Generative AI Chabot first started
The birth of Generative AI Chatbots was largely due to technological advances. The evolution of natural language processing (NLP) and the increase in computing resources have dramatically improved text generation and understanding capabilities. By utilizing open source AI, it has become relatively available to anyone, completely changing the development landscape. This has made it possible to meet the needs of users who expect immediate responses and the demand for personalized experiences.
In addition, the benefits from a management perspective are also greater. AI bots reduce labor and operating costs and provide scalability that can handle a large number of users at the same time. In addition, through the use of big data and feedback from user data, highly accurate conversation models have been built and continuous improvements have been made possible.
The emergence of Siri and IBM Watson in 2011 was the reason for the spread of generative AI chatbots. In addition, in 2016, Microsoft, Facebook, and Google announced services for chatbots at their respective events, and chatbot technology suddenly attracted attention.
In 2014, smart devices such as Amazon’s Alexa and Google’s “Google Home” went public, and since then, generative AI chatbots have become widely used in ordinary households.
Social and cultural factors are also driving this trend. The spread of generative AI chatbot has accelerated due to the progress of digital transformation and growing interest in AI technology. In addition, there is an urgent need to use new technology to solve a number of issues that did not exist before, such as the fragmentation of customer needs and the sophistication of demands in the market, and requests for companies to improve business efficiency. The combination of these factors has made generative AI conversational bots indispensable in modern society.
AI-based chatbots are attracting attention as a solution to these issues. Generative AI chatbots can solve a wide range of problems, and great expectations are being placed on them. For example, their potential is expanding in various situations, such as quick response in customer support, 24-hour service provision, initial consultation and diagnostic assistance in the medical field, and individual learning support in the education field.
In this way, generative AI chatbots are becoming increasingly important as they meet social needs as technology evolves.
1.3. What is a Generative AI Chatbot?
Generative AI chatbots are programs that use artificial intelligence (AI) technology to conduct conversations. These chatbots can understand human language and generate appropriate responses. Generative AI chatbots use pre-trained data sets and models to generate conversations and can respond to new information and questions. As such, they are used for a variety of applications, including customer support, information, and entertainment.
2. Generative AI Chatbot: Features and Mechanisms
2.1. Features from the user’s point of view
Generative AI chatbots automatically generate answers based on both “the vast amount of data that the generative AI model has learned in advance” and “the data given at the time of prompt input. As a result, it is characterized by its flexibility to respond to questions that operators may not have anticipated.
Conventional AI chatbots can only display pre-prepared answers and cannot respond to unexpected questions. On the other hand, in the case of generative AI, answers to user questions are generated based on all data that can be referenced by the generative AI.
This is of great benefit to the user because it can generate an answer to any question and resolve the question quickly. It can also respond intelligently even if the user’s question is a long and complex sentence, or if there are variations in spelling.
2.2. How Generative AI Chatbots Work?
Generative AI chatbots have a mechanism for dynamically generating responses to user input. This process takes place as follows
2.2.1. Input by user
First off, users enter questions and requests in natural language. This input is unrestricted in format and content, allowing users to ask questions intuitively. For example, “Can you tell me how to fix my car tire?” or “What is the weather like next week?” and so on.
2.2.2. User input is converted to prompts (on the user’s system)
User input is converted into prompts within the chatbot system. A prompt is formatted text that clearly communicates a question or instruction to the generative AI. At this stage, the user’s natural language input is formatted in a way that is easily understood by the generative AI.
2.2.3. Generative AI receives prompts and generates responses based on pre-trained data and prompt input data
When the generative AI receives a prompt, it consults a vast database of previously learned data to generate the most appropriate response to the content of the prompt. The training data includes past dialogue data, encyclopedic knowledge, and information on specialized fields, which are comprehensively leveraged to derive the most appropriate response.
2.3. Features of Generated AI Chatbots
Unlike traditional AI chatbots, generative AI chatbots have the ability to generate new answers to user questions, in addition to displaying pre-checked, fixed answers. Specifically, they have the following characteristics
2.3.1. Flexible response
Traditional AI chatbots rely on pre-programmed scenarios and fixed response patterns and cannot respond to unexpected questions. Generative AI chatbots, however, can understand user questions on the fly and generate appropriate responses. This allows them to respond flexibly to unexpected questions.
2.3.2. Data-based response generation
Generative AI generates answers by referencing extensive pre-trained data, so answers can be expected to be based on a wealth of knowledge. This allows users to obtain more accurate and useful information.
2.3.3.Responding to user needs
Generative AI chatbots can gain a deep understanding of user input and respond precisely to their needs. For example, if a user’s question is long and complex, or if there are variations in spelling, AI can accurately understand the intent and provide an appropriate response.
In this way, a generative AI chatbot can meet the diverse needs of users with flexibility and adaptability not found in traditional chatbots. This is expected to increase customer satisfaction and improve operational efficiency.
3. Effectiveness of Generative AI Chatbots
Generative AI chatbots are one of the technologies that have been rapidly gaining popularity in recent years. In fact, many companies are considering their introduction. The introduction of generative AI chatbots is expected not only to improve the quality of customer service, but also to increase the efficiency of internal operations and enhance competitiveness through the use of data. This article describes the specific benefits of introducing generative AI chatbots from the following two perspectives.
3.1. Customer Experience Improvement
3.1.1. Improve customer satisfaction
Customers will be able to resolve simple questions on their own without having to interact with customer support staff. This allows customer support staff to focus on complex inquiries that are difficult for chatbots to handle, and is expected to improve the quality of responses to difficult issues. As a result, customers will be able to resolve their questions and issues faster, leading to higher customer satisfaction.
In addition, customers will no longer feel hesitant to call and will be less likely to leave questions unanswered. This reduces the number of support complaints, such as “disconnected” and “slow response,” and contributes to improving the credibility of the company. The same effect can be expected for the internal help desk.
Since customers can easily ask for help, minor inquiries that have been overlooked will be brought to the surface, and minority opinions will be recorded as data. In addition, personal information that is difficult to obtain directly from human operators can be collected, further expanding the scope of data utilization.
3.1.2. Improved efficiency and reduced workload for customer support and helpdesk operations
Generative AI chatbots can operate 24 hours a day, 7 days a week, 365 days a year, so customers are not left frustrated when a representative is unavailable. As customer needs become more diverse, the content of inquiries is also becoming more complex. In many cases, it is difficult to provide sufficient customer support with scenario-based responses based on pre-trained data. However, a generative AI chatbot automatically learns the most appropriate response based on accumulated data, making it possible to provide more flexible and appropriate responses than scenario-based responses.
This improves the efficiency of inquiry response and reduces the time customers spend waiting. In addition, prompt and accurate responses can be expected to increase customer satisfaction and in the company. The greatest feature of a generative AI chatbot is that it continuously learns to improve the accuracy of its answers.
Scenario-based chatbots are limited in what they can answer. If it cannot respond to a question, a human has to answer again. In such cases, the benefit of cost reduction cannot be achieved. However, a generative AI chatbot can derive the most appropriate response from a large amount of data and respond to inquiries without the need for a human to respond. This reduces human costs.
3.2. Enhancement of business competitiveness
3.2.1. Use in Marketing
Understanding customers through data analysis: Generated AI chatbots collect large amounts of data through interaction with customers. By analyzing this data, it is possible to understand customer behavior patterns and needs and develop targeted marketing strategies.
Personalized marketing: Enables personalized offers tailored to each individual customer. This increases customer engagement and maximizes the effectiveness of marketing campaigns.
Campaign Optimization: Analyze historical campaign data to identify effective methods and timing to optimize your next marketing effort.
3.2.2. Improve competitiveness by accumulating data
Accumulating the response logs of the generated AI chatbots as data will improve the quality of customer service and the competitiveness of the entire company. The accumulated data will be used as an internal knowledge base, and knowledge sharing among employees will increase. This improves the skill level of the entire organization, leading to enhanced competitiveness.
Even when a staff member takes over the job, he or she can respond smoothly based on the past logs. Furthermore, the response data accumulated in chat rooms can be used to brush up on products and contract details, and to adjust manuals and packages, leading to the provision of products and services that meet customer needs.
4. Miichisoft’s Generative AI Chatbot Solution
Miichisoft’s dxGAI Chatbot, a generative AI chatbot, uses RAG technology (*) to maximize support efficiency and help improve performance in various aspects, including potential customer development and user interaction.
* About RAG (Retrieval Augmented Generation)
Retrieval Augmented Generation (RAG) is a technology for improving the accuracy and reliability of AI generation models, utilizing data acquired from external sources. RAG is a combination of information retrieval (Retrieval) and text generation model (Generation). In other words, it fills a void in the way large-scale language models (LLMs) work.
The dxGAI Chatbot builds a knowledge database with uploaded internal data in a variety of formats (pdf, csv, doc, etc.). Leveraging historical and learned data from customer and internal interactions, along with operator feedback through the platform, the chatbot is automatically updated and optimized to improve reply times and accuracy.
In addition, users chan add chat functionality to any web page using simple embed code. They can also customize the chatbot interface to adjust colors, logos, content, etc. to create a branded impression. line, Slack, Notion, WhatsApp and Zapier.
If you are considering implementing a chatbot in the future, please feel free to contact us.
5. Examples Of Generative AI Chatbots by Industry
Companies are already actively implementing generative AI chatbots.
5.1. Erica: Virtual Financial Assistant at Bank of America
Bank of America’s Erica uses personal data and analytics to revolutionize the way customers manage their finances. Erica provides up-to-date account balances, weekly expense reports, credit score information, and 24/7 support for quick problem resolution. Customers can interact with Erica using voice and text.
Erica provides the following features. Proactively provide helpful personalized insights and financial advice. It also notifies customers when their next invoice is due and schedules payment dates. In addition, it answers any questions they may have about their account.
How it Works:.
Erica is only available on Bank of America’s mobile app, which can be downloaded for free from the App Store and Google Play.
5.2. Edward: Virtual Host at Edwardian Hotel
Edward is an AI SMS chatbot that assists Edwardian Hotel guests Edward uses cell phone numbers to access guest details. Additionally, it provides a highly personalized experience Edward understands guest needs and can respond to over 1,200 topics with extreme accuracy. As a result, hotel room service revenues have increased by up to 50%.
Edward introduces hotel amenities and provides directions and brief advice. Respond to hotel complaints, provide room availability, and accept reservations, as needed. In addition, they process payments.
How it Works:
Edward is available to Edward Hotel guests only. Guests receive a text link upon check-in and communicate with Edward via SMS text.
5.3. Julie: Amtrak’s Virtual Travel Assistant
Ask Julie is a very convenient system that helps Amtrak passengers get the answers they need without having to call customer service. Specifically, Amtrak has seen an eight-fold return on investment and a $1 million reduction in customer service costs.
In addition, the ease of user interaction through Julie has increased Amtrak’s booking rate by 25% and is generating 30% more revenue than other channels.
Some of Julie’s key features include:
First, it helps passengers book tickets; Julie makes it easy and fast for passengers to book tickets, saving them time and effort.
Second, it helps passengers fill out the necessary forms. Filling out various travel-related forms is also facilitated by Julie’s guidance.
Finally, Julie provides information on reservations, stations, and routes, giving passengers all the information they need to help them plan their trip.
Julie is available both on Amtrak’s website and by phone, and is designed to help passengers obtain information smoothly and efficiently.
6. FAQs
What is a Generative AI Chatbot?
Generative AI chatbots are AI chatbots that use natural language processing technology to generate responses in real-time based on user input. Unlike traditional scenario-type or FAQ-type chatbots, they flexibly create responses based on pre-trained data and user prompt input.
What are the benefits of a generative AI chatbot?
The main benefits of a generative AI chatbot include
・Flexibility: Respond appropriately to unexpected questions.
・Data-driven answer generation: Leverages vast databases to provide accurate and useful information.
・Responds to users’ needs: Accurately understands and responds to complex questions or questions with inconsistent spelling.
What is the difference between a generative AI chatbot and a traditional chatbot?
Generative AI chatbots are more flexible and adaptable than traditional scenario-based or FAQ-based chatbots because they generate answers in real time using pre-trained data. Traditional chatbots rely on predefined scenarios and fixed response patterns, which can make it difficult to respond to unexpected questions.
7. Conclusion
The features, mechanisms, and benefits of introducing a generative AI chatbot are explained in detail. Compared to conventional scenario-type and FAQ-type chatbots, generative AI chatbots are much more flexible and adaptable and can respond to a variety of user needs. By introducing them, we expect to improve the quality of customer support, increase customer satisfaction, and improve operational efficiency. In addition, the accumulation and utilization of data will help optimize marketing strategies and strengthen competitiveness.
Miichisoft’s dxGAI Chatbot utilizes RAG technology to provide efficient support and high performance. If you are considering implementing this service, feel free to contact us. We hope the Generated AI Chatbot will help improve your company’s operations and increase customer satisfaction.
