introduction
For businesses, "utilizing internal knowledge" is a crucial topic that can significantly impact their competitiveness. However, in reality, many companies struggle with issues such as "information being scattered," "difficulty accessing necessary information," and "information being tied to specific individuals." One solution gaining attention to overcome these challenges is next-generation knowledge utilization using "chat x AI."
In conclusion, by utilizing chat AI, internal knowledge evolves from something to "find" to something to "extract." This shift from traditional search-based to conversational approaches brings about significant changes in operational efficiency, productivity, and talent development.
This article provides a clear and easy-to-understand explanation of chat AI, from its basics to its benefits and key points for success, even for beginners.
The potential of knowledge utilization through chat and AI
What is internal company knowledge? A simple explanation of the basics.
First, "internal knowledge" refers to the knowledge and information accumulated within a company. Specifically, this includes operational manuals, sales know-how, customer service history, and troubleshooting methods. These are the company's "intellectual assets," and whether or not they can be utilized directly impacts performance.
However, in many companies, this knowledge is not properly managed. It is commonly scattered across file servers and cloud storage, making it difficult to know where anything is located. Furthermore, much of it is "tacit knowledge" that exists only in the minds of veteran employees, which contributes to the over-reliance on individual knowledge.
The key concepts here are "explicit knowledge" and "tacit knowledge." Explicit knowledge is knowledge that has been clearly documented in the form of documents or data, while tacit knowledge is unarticulated knowledge based on experience and intuition. Chat AI has the potential to function as a bridge between these two.
In other words, it's important to understand that internal company knowledge is not merely a collection of information, but rather an asset that only gains value when it is put to use.
Challenges and limitations of traditional knowledge management
Traditional knowledge management systems have primarily been designed around the premise of "searching." Examples include internal portals, FAQ systems, and document management tools. However, these systems have several fundamental challenges.
First and foremost, there's the issue of "dependence on search skills." If you don't know the right keywords, you won't be able to find the information you need. For example, if a new employee doesn't know the technical terms, the search itself may not even be possible.
Next is the challenge of "not being able to keep up with updating and organizing information." Because knowledge is constantly increasing, unorganized information accumulates, resulting in a "useless database."
Furthermore, the "poor user experience" cannot be overlooked. Having to search across multiple tools or read lengthy documents hinders the speed of practical work.
These challenges can lead to situations where valuable knowledge exists but goes unused. This represents a significant loss of opportunity for businesses.
The revolutionary changes brought about by chat AI
The most distinctive feature of chat AI is that it allows users to access information in a "conversational format." Users can obtain the necessary information simply by asking questions in natural language (language like that used in everyday conversation).
For example, simply typing "Please explain the basic flow for handling customer complaints" will integrate relevant knowledge and present it in an easy-to-understand format. This is an experience that was difficult to achieve with conventional search systems.
A key technology that comes into play here is "Natural Language Processing (NLP)." This refers to the technology that enables computers to understand and process human language. This technology makes it possible to handle ambiguous questions and inquiries that include context.
Furthermore, because AI generates the optimal answer by cross-referencing multiple sources of information, it enables "information integration." This eliminates the need for users to read multiple documents, dramatically improving work efficiency.
Thus, chat AI has the potential to fundamentally change the way we utilize knowledge.
Specific benefits of implementing chat AI
Improved efficiency in information retrieval and increased work speed
In conclusion, the introduction of chat AI significantly reduces the time spent searching for information. Traditionally, the process required "search → read → understand," but with chat AI, it changes to a simpler flow of "listen → understand."
For example, if a sales representative wants to find past proposal examples, they would traditionally have to search multiple folders and read through the relevant documents. However, by using chat AI, they can simply type, "Tell me about past successful proposal examples," and the key points will be presented in an organized format.
The key concept here is "UX (User Experience)." UX refers to the entire user experience when using a service. Chat AI significantly improves UX, enabling stress-free information acquisition.
As a result, employees can focus on the tasks that truly matter to them, leading to increased productivity throughout the organization.
Eliminating reliance on individual expertise and promoting knowledge sharing
One of the major challenges for companies is "personalization." This refers to a situation where only certain employees understand the work content and know-how. In this situation, there is a risk that operations will be disrupted if those employees are absent.
Chat AI can significantly contribute to eliminating this reliance on individual expertise because it can centralize knowledge and convert it into a format that anyone can access.
Furthermore, AI can learn from past interactions and documents, and extract some of the tacit knowledge as explicit knowledge. This makes it easier for veteran employees' expertise to be shared throughout the organization.
The key concept here is "knowledge management." This refers to a series of processes for collecting, organizing, sharing, and utilizing knowledge within an organization. Chat AI plays a role in automating and streamlining this process.
As a result, the overall skill level of the organization is raised, enabling stable business operations.
Use in employee training and onboarding
Chat AI is also highly effective in training and onboarding new employees. New employees often have many questions and need to ask senior employees, which can often be burdensome for both parties.
By implementing chat AI, you can create an environment where you can ask questions 24 hours a day. For example, you can get immediate answers to questions such as, "Please explain the procedure for expense reimbursement," or "What is the purpose of this task?"
The key point here is improving the "self-resolution rate." The self-resolution rate refers to the percentage of people who can solve problems without relying on others. Chat AI increases this rate and also contributes to reducing training costs.
Furthermore, AI helps maintain consistency in responses, preventing inconsistencies in instructional content. This also has the benefit of standardizing the quality of education.
Key points for successful implementation and use cases
Knowledge base that should be organized before implementation
Thorough preparation is crucial for the successful implementation of chat AI. In particular, establishing a knowledge base is essential.
A knowledge base is a system that serves as the foundation for accumulating and managing information within a company. Introducing AI without a properly established knowledge base will not yield sufficient results.
First, it's necessary to organize existing documents and data, removing duplicates and unnecessary information. Furthermore, classifying and tagging the information is crucial to create a structure that AI can easily understand.
Furthermore, the perspective of "governance" is also important. Governance refers to the rules and operational systems for managing information. By clearly defining who is responsible for updating information and which information is correct, a highly reliable knowledge base can be built.
Case studies of actual business applications
Companies that have actually implemented chat AI have reported various positive results.
For example, one IT company implemented chat AI for handling internal inquiries, resulting in a roughly 40% reduction in the number of inquiries. This allowed support staff to focus on more complex tasks.
In addition, in the manufacturing industry, on-site workers can use tablets to ask questions to chat AI, allowing them to instantly check work procedures and troubleshooting methods, which has led to a reduction in work errors.
Furthermore, in the sales department, the AI's ability to present past success stories and proposal materials has improved the quality of proposals and led to an increase in the closing rate.
As these examples show, chat AI can be used in a wide range of fields, regardless of industry.
Tips for successful operation and improvement
Implementing chat AI isn't the end of the process; continuous operation and improvement are crucial. The first thing to focus on is "gathering feedback." You need to understand user usage and satisfaction levels and use that information to make improvements.
Furthermore, "improving the accuracy of responses" is also a crucial point. Since AI relies on training data, it is necessary to regularly update its knowledge and improve its accuracy.
Furthermore, "measures to promote usage" are also essential. It is important to create an environment where employees can actively use the system through internal training and the development of guidelines.
Finally, being mindful of a "small start" is also key to success. Instead of aiming for company-wide implementation from the beginning, starting with a specific department or task allows you to verify the effects while minimizing risks.
summary
Utilizing internal knowledge through chat and AI has the potential to significantly change the way companies work. By evolving from traditional search-based knowledge management to a conversational and integrated system, numerous benefits can be gained, such as improved operational efficiency, elimination of reliance on individual expertise, and enhanced talent development.
On the other hand, establishing a knowledge base and operational structure is essential for successful implementation. By properly addressing these aspects, the effectiveness of chat AI can be maximized.
As AI technology evolves, the importance of knowledge utilization will only increase. Now is the time to re-evaluate your company's knowledge utilization and take steps towards the next generation of work.