Information processing method, program, and information processing device

Abstract

This will enable the system to appropriately obtain information from employees and others in daily operations. [Solution] An information processing method comprising: an information processing device providing conversational AI processing to a user terminal used by a user; acquiring conversational data related to the user's business report through a conversation about the business report via conversational AI processing; generating the user's business report data based on the conversational data; and outputting the business report data to an administrator terminal used by the user's administrator.

Description

Technical Field

[0001] The disclosed technology relates to an information processing method, a program, and an information processing apparatus.

Background Art

[0002] Conventionally, there is known an interview support system that uses a learned model to reduce the human and time burdens in employment interviews and efficiently acquire talented personnel to be hired (see, for example, Patent Document 1).

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] However, in the prior art of personnel systems, in AI processing, the amount and quality of input information are important, but no consideration has been given from this perspective, and most of the consideration has been from the perspective of how to efficiently analyze and examine the input information. Also, problems remain regarding how to extract information from employees and the like in daily operations.

[0005] Therefore, one of the objectives of the disclosed technology is to provide an information processing method, a program, and an information processing apparatus that can appropriately acquire information from employees and the like in daily operations.

Means for Solving the Problems

[0006] An information processing method in one aspect of disclosure involves an information processing device performing the following actions: providing conversational AI processing to a user terminal used by a user; acquiring conversational data related to the user's business report through a conversation about the business report via the conversational AI processing; generating the user's business report data based on the conversational data; and outputting the business report data to an administrator terminal used by the user's administrator. [Effects of the Invention]

[0007] Disclosure technology makes it possible to appropriately obtain information from employees and others in daily operations. [Brief explanation of the drawing]

[0008] [Figure 1] This diagram shows the various processes and objectives related to HR operations in disclosure technology. [Figure 2] This figure shows an example of the configuration of an information processing system 1 according to one embodiment. [Figure 3] Block diagram showing an example of a server according to one embodiment. [Figure 4] This figure shows an example of employee information according to one embodiment. [Figure 5] This figure shows an example of employee-related information according to one embodiment. [Figure 6] This figure shows an example of a processing apparatus according to one embodiment. [Figure 7] A flowchart illustrating an example of business reporting processing according to one embodiment. [Figure 8] A flowchart illustrating an example of processing after acquiring conversation data according to one embodiment. [Figure 9] A flowchart illustrating an example of the processing of each functional module according to one embodiment. [Figure 10] This figure shows an example of the execution screen of a conversational AI according to one embodiment. [Figure 11] This diagram illustrates the concept of work reporting between a subordinate and a superior according to one embodiment. [Figure 12]A diagram showing the concept of business reports for managers according to an embodiment. [Figure 13] A diagram showing an example of an employee dashboard screen according to an embodiment. [Figure 14] A diagram showing an example of the results of personality diagnosis according to an embodiment. [Figure 15] A diagram showing an example of a management-side dashboard screen according to an embodiment. [Figure 16] A diagram showing an example of a cycle of visualizing business, supporting growth, and strengthening engagement according to an embodiment.

Embodiments for Carrying Out the Invention

[0009] Referring to the accompanying drawings, preferred embodiments of the present disclosure will be described. In each figure, those with the same reference numerals have the same or similar configurations.

[0010] [Embodiment] FIG. 1 is a diagram showing each process and each purpose related to HR (Human Resources) operations in the disclosed technology. In the example shown in FIG. 1, a mechanism for collecting data from employees and managers (hereinafter also referred to as "employees, etc.") using conversational AI processing and realizing a sound organization by utilizing the collected data is described.

[0011] In the mechanism of the disclosed technology, conversational AI is used as a communication tool. Conversational AI realizes more effective communication through natural interactions between people. As a result, smooth communication can be achieved through dialogue with AI beyond the operations using conventional keyboards, mice, etc.

[0012] In a conventional face-to-face interview between people, both parties are burdened and the quality of the interview is uneven. For example, the management side has problems in at least one of the following points. · The man-hour of the interview is burdensome, the true feelings cannot be elicited, the work is troublesome, unevenness in emotions is concerning, subjective opinions are formed, and / or harassment is a concern, etc. On the one hand, in face-to-face interviews, the general employees have problems in at least one of the following aspects. · Decreased motivation, decreased sense of satisfaction, communication gap, neglect of process, burden of time with superiors, and / or fear of harassment, etc.

[0013] Regarding the above problems, by using conversational AI, it is expected that the communication between both parties can be improved. For example, on the management side, there are improvements in at least one of the following aspects. · Labor efficiency improvement, visualization of true feelings, automation of information, no emotional unevenness, no fear of being called harassment, and / or respect for subjectivity, etc. On the other hand, on the general employee side, there are improvements in at least one of the following aspects. · Increased motivation, conversation at preferred time, feeling of satisfaction, no communication gap, understanding of process, and / or no harassment, etc.

[0014] To sum up, by using conversational AI, a fair and honest conversation can be enabled, an objective evaluation based on data can be made, and the stress of both parties can be reduced.

[0015] As shown in FIG. 1, in the disclosed technology, not only can the live data from daily business reports be utilized by the organization through natural conversations with conversational AI, but by learning and analyzing the conversation data by talking to the AI, one can grow into an AI that understands oneself, improve the ease of conversation, and obtain more valuable data. Also, in the disclosed technology, although daily business reports are necessary work, by focusing on this and utilizing AI in business reports, it becomes possible to obtain the necessary data from daily necessary work and improve the accuracy of data analysis.

[0016] For example, for an employee (one example of a user), conversational AI can be used to generate employee work report data and visualize information that is usually difficult to see from daily conversations. Furthermore, disclosure technology can perform personality assessments of employees based on conversational data obtained using conversational AI. This allows employees to visualize their own personality, deepen their self-understanding by objectively grasping their current situation, and experience personal growth by eliminating areas for improvement through advice from conversational AI.

[0017] Furthermore, for organizations (management, users, for example), it becomes possible to utilize the multiple functions (modules) described later to visualize, standardize, and / or score their organizational strength based on individual employee analysis, and use this information for organizational development. This enables organizations to identify challenges or risks and understand their organizational strengths.

[0018] Furthermore, the disclosure technology may implement an evaluation module that objectively evaluates employees based on conversation data from each user obtained during business reporting, a recruitment module that conducts candidate interviews, a guidance module that provides various information to employees, a confirmation module that checks employee inquiries, and / or a consultation module that listens to employee concerns. In addition, by analyzing the information obtained from conversation data, it becomes possible to analyze the emotions and personalities of each employee from the conversations and ultimately determine organizational strength. The disclosure technology realizes a healthy organization by providing daily care that enables employees to understand themselves and support their growth, and enables management to improve operations and develop the organization. The system configuration of the disclosure technology described above is explained below.

[0019] <System Configuration> Figure 2 is a diagram showing an example of the configuration of an information processing system 1 according to one embodiment of the disclosure. As shown in Figure 1, the information processing system 1 includes servers 10A and 10B and processing units 20A, 20B, and 20C for one or more users (employee representatives, etc.). Hereinafter, servers will be referred to as server 10 unless individually distinguished, and processing units will be referred to as processing unit 20 unless individually distinguished. For example, the information processing system 1 according to the embodiment constitutes a system that provides support for realizing human capital management based on conversational data acquired using conversational AI.

[0020] Server 10 and processing unit 20 can send and receive data to and from each other via network N. Server 10 may be composed of multiple processing units, and the number of processing units 20 may be arbitrary. For example, processing unit 20 is an information processing unit used when each employee (each user) belonging to an organization (e.g., a company) providing services in the disclosure technology uses conversational AI to report on daily tasks or engage in dialogue.

[0021] The information processing system 1 may implement the aforementioned work reporting module, evaluation module, recruitment module, guidance module, confirmation module, and / or consultation module based on employee conversation data acquired through conversational AI. By improving the job satisfaction of employees through each of these modules, it is possible to realize human capital management. Next, the server 10 and processing unit 20 provided in the information processing system 1 will be described.

[0022] For example, server 10A works in conjunction with server 10B, which performs AI processing such as generative AI, to acquire and analyze conversational data from company employees (users) using conversational AI, thereby supporting the company's labor and human resources management. Server 10B may also be implemented within server 10A.

[0023] Server 10A provides conversational AI processing services from the processing units 20 used by various users, such as managers, administrators, and employees, to acquire more natural conversational data at the user's preferred timing. For example, a regular employee can use this conversational AI processing for their daily work reports, allowing them to submit their reports in a relaxed state at their preferred time. The same applies to managers and administrators; they can use conversational AI processing to receive reports from their subordinates at their preferred time. Server 10A also provides the services of each functional module, as described later, to each user.

[0024] The processing unit 20 is a personal computer, tablet, smartphone, or other processing unit used by each user within the organization. When the processing unit 20 is used by a general employee within the organization, it is denoted by code A; when it is used by an administrator (supervisor, etc.) within the organization, it is denoted by code B; and when it is used by a manager within the organization, it is denoted by code C.

[0025] The processing unit 20A provides business reports to the server 10A using conversational AI processing in response to operations from general employees. The processing unit 20A may, for example, obtain the results of a personality assessment evaluated based on the conversational data during business reporting from the server 10A. The processing unit 20A can also utilize the modules described later.

[0026] The processing unit 20B used by the administrator can retrieve and display the contents of subordinates' work reports from the server 10A in response to the administrator's operations, and can also utilize the modules described later. The processing unit 20C used by the manager can retrieve and display the contents of subordinates' work reports from the server 10A in response to the manager's operations, and can also utilize the modules described later.

[0027] Furthermore, the processing unit 20 used by the user may access a website (or web page) provided by the server 10A using a web browser and receive the labor and personnel management services provided on this website.

[0028] Furthermore, the processing unit 20 used by the user may have an application program (app) installed for using the service provided by the server 10A. This app causes the processing unit 20 to execute at least a portion of the labor and personnel operations disclosed in the embodiments shown below within the service provided by the server 10A. When this app is executed, the processing unit 20 accesses the server 10A to send and receive information used to execute the app. The configurations of the information processing system 1 that enable the execution of the disclosed technology will be described in detail below.

[0029] <Server Configuration> Figure 3 is a block diagram showing an example of a server 10 according to one embodiment of the disclosure. The server 10 includes one or more processors (e.g., CPUs) 110, one or more network communication interfaces 120, a storage device (storage unit) 130, and one or more communication buses 170 for interconnecting these components. Hereinafter, servers 10A and 10B will be described together as server 10, but depending on the implementation, servers 10A and 10B may be configured separately, or some components of server 10 may be configured in another server.

[0030] Server 10 may optionally include a user interface 150, which may include a display and input devices (such as a keyboard and / or mouse, or any other pointing device).

[0031] The storage device 130 is, for example, a high-speed random access memory (main memory) such as DRAM, SRAM, or other random access solid-state memory. Alternatively, the storage device 130 may be one or more non-volatile memories (auxiliary storage) such as magnetic disk storage devices, optical disk storage devices, flash memory devices, or other non-volatile solid-state memory devices. The storage device 130 may also be a non-temporary recording medium readable by a computer, storing programs and the like that, including instructions to the computer. Furthermore, the storage device 130 may be either main memory (memory) or auxiliary storage (storage), or it may include both.

[0032] The storage device 130 stores data, programs, etc., used by the information processing system 1. For example, the storage device 130 stores employee-related information such as employee information for each employee belonging to the organization, conversation data, emotion data, analysis data, personality data, report data, and office data for each employee. Employee information and employee-related information will be described later with reference to Figures 4 and 5.

[0033] Another example of the storage device 130 may be one or more storage devices located remotely from the processor 110. In one embodiment, the storage device 130 stores programs, modules, and data structures, or subsets thereof, executed by the processor 110.

[0034] The processor 110 executes programs stored in the storage device 130 to configure, for example, a service provision unit 111, a conversation control unit 112, an acquisition unit 113, a generation unit 114, an output unit 115, an analysis unit 116, and a function unit 117.

[0035] The service provision unit 111 provides each of the labor and personnel operations disclosed in the embodiment. The service provision unit 111 controls the process of acquiring requests related to labor and personnel operations from each processing unit 20, such as business report requests and requests for the use of each functional module described later, and registering and managing information on each employee. In addition, the service provision unit 111 has a conversation control unit 112, an acquisition unit 113, a generation unit 114, an output unit 115, an analysis unit 116, and a function unit 117 in order to control the execution of the services disclosed in the embodiment. The following describes each process that the service provision unit 111 can provide.

[0036] ≪Business report≫ The conversation control unit 112 provides conversational AI processing to user terminals used by users (such as employees within an organization). For example, the conversation control unit 112 provides conversational AI processing to the user in response to user operations on the user terminal, thereby enabling a conversation with the user.

[0037] The conversation control unit 112 may use a generative AI and an avatar AI to achieve natural-sounding conversations. For example, the generative AI may use a Large Language Model (LLM) that functions as a language generation AI to perform conversations, answer questions, motivate, reach consensus, and conduct interviews. The avatar AI may use the generative AI to generate a more human-like appearance and motion AI to achieve more human-like movements. Therefore, the conversation control unit 112 can enable an AI avatar that is capable of free-flowing conversations to respond in a more human-like manner.

[0038] The acquisition unit 113 acquires conversational data related to the user's work reports through conversational AI processing of work reports. For example, the acquisition unit 113 acquires live conversational data from daily work reports in a natural conversation through conversational AI processing by a work report module requested by the employee.

[0039] The generation unit 114 generates user business report data based on the user's conversation data acquired by the acquisition unit 113. For example, the generation unit 114 uses AI processing to aggregate and analyze conversation data, including daily work content and work progress, and generates business report data. The business report data may be generated in a format where it is converted into text according to the questions and answers from conversational AI processing and filled into each item of the business report template, or the generation AI may generate the business report data using words extracted from the conversation data.

[0040] Since work reports are submitted at timely intervals (for example, daily), the entered information can be processed in real time. Therefore, managers and other supervisors can grasp in a timely manner what employees are currently working on and where problems lie. Conversational AI is said to be able to convey more than five times the amount of information per unit of time compared to text communication. Furthermore, because it includes a wealth of non-verbal information, it can be said to be superior in both the quality and quantity of information. Employees can use conversational AI to submit work reports, making it easier to communicate concerns and problems that might be difficult to convey in face-to-face meetings.

[0041] The output unit 115 outputs the business report data generated by the generation unit 114 to the administrator terminal used by the user's administrator. For example, the output unit 115 outputs the business report data generated by AI processing to the processing unit 20B used by the administrator. There are various methods for output, but for example, the output unit 115 may output using the notification function of the labor and personnel service of the disclosure technology, or it may report using the conversational AI processing described above when a business report request is received from an administrator or manager (also referred to as "administrator, etc."). In addition, the output unit 115 may output report data compiled by the generation unit 114 from the business report data of multiple subordinates under the management of the same administrator to the processing unit 20B used by the administrator.

[0042] In summary, by utilizing conversational AI processing, it becomes possible to appropriately obtain information from employees and others in daily operations. Furthermore, by using conversational AI processing in the daily work reports that employees must submit, it is possible to reduce the burden on employees and expect an increase in the amount of information provided through conversation. In addition, since work report data is generated by the user engaging in conversations about work reports, work efficiency is improved.

[0043] Furthermore, utilizing conversational AI processing can yield the following benefits: • Skill improvement The user's conversational skills, emotional processing, and memory will improve, leading to better learning outcomes. • Improve interpersonal relationships Since users don't feel embarrassed making mistakes when talking to an AI, it increases opportunities for conversation among users. ·engagement There is no harassment from superiors or others, and it is possible to have honest conversations.

[0044] The analysis unit 116 analyzes user conversation data in business reports and extracts issues related to users or the organizations they belong to. For example, the analysis unit 116 extracts issues and problems in business reports from conversation data reported in real time. Specifically, the analysis unit 116 identifies dissatisfied users and the content of their dissatisfaction, analyzes the reasons for declining engagement within the organization, analyzes the causes of high employee turnover, and analyzes the reasons for declining sales.

[0045] For example, the analysis unit 116 may input conversation data obtained from each user and prompts for extracting organizational issues into a generating AI, and extract the output results as issues. Alternatively, regarding issue extraction, the analysis unit 116 may create a list of specific keywords, and when words in conversation data corresponding to those specific keywords are extracted, it may extract the issue corresponding to the extracted words and the user who made the statement.

[0046] The output unit 115 may also output the issues extracted by the analysis unit 116 to an administrator terminal used by the administrator. The output unit 115 outputs, for example, issue data generated by AI processing to a processing unit 20B used by the administrator. There are various methods for output, but for example, as described above, the output unit 115 may output using the notification function of the labor and personnel service of the disclosure technology, or it may report using the conversational AI processing described above when an issue report request is received from an administrator or the like.

[0047] Through the above processing, disclosure technology allows for the extraction of user and organizational issues from daily business report conversation data, enabling managers and others to quickly grasp these issues, consider countermeasures, and implement measures. Furthermore, disclosure technology enables objective analysis and evaluation of conversation data by utilizing analytical evaluation AI that performs morphological analysis.

[0048] The generation unit 114 includes collecting business report data from each user acquired by the acquisition unit 113. The generation unit 114 may also include extracting specific report content that meets predetermined criteria based on the collected business report data. For example, the generation unit 114 determines whether or not predetermined criteria for extracting a user's issue are met. The predetermined criteria include, for example, determining whether or not there is conversational data of what the user said after the conversational AI asked a question about the issue, whether or not an issue is extracted by the generation AI, or whether or not the similarity of specific words related to the issue is determined to be higher than a threshold.

[0049] The generation unit 114 includes generating business report data by making the extracted specific report contents selectable by administrators, etc. The specific report contents include, for example, issues and the users who have those issues. When reporting business report data for multiple users, the generation unit 114 makes it selectable user A who has an issue, so that administrators can be aware of that user's issues. The generation unit 114 may also make it possible to identify that user A has an issue in the business report data of multiple users. For example, the generation unit 114 may add an issue mark when the business report data is displayed, or when the business report data is output as audio, it may add an audio statement that user A has an issue.

[0050] Through the above process, administrators can efficiently understand the content of reports by selecting those containing specific information from among multiple users' work reports. For example, if a specific report contains an issue, the user can be identified and their current issues can be easily understood. Alternatively, the specific report may contain at least one of the following: the user's health status, organizational performance, complaints, or improvement measures. Each of these items can be identified by replacing "issue" in the predetermined criteria mentioned above with any of the other items.

[0051] The output unit 115 may also include reporting the business report data generated by the generation unit 114 to administrators, etc., using the conversational AI processing described above. By using conversational AI processing when processing business reports, the output unit 115 can also acquire conversational data from administrators, etc. Furthermore, it becomes possible to report each user's business report data to busy administrators, etc., via voice, thereby increasing the amount of information available to the listener.

[0052] When reporting business report data, the acquisition unit 113 may include acquiring conversational data from administrators, etc., using conversational AI processing provided by the conversation control unit 112. For example, when reporting business to administrators, etc., the acquisition unit 113 acquires conversational data spoken by the administrators, etc. For example, the conversation control unit 112 may, in response to the voice of the business report request from the administrators, etc. acquired by the acquisition unit 113, output each user's business report via the output unit 115. Alternatively, the acquisition unit 113 may, under control by the conversation control unit 112, acquire conversational data from administrators, etc., while outputting a business report, and have the analysis unit 116 analyze it. The analysis unit 116 may analyze the organization's corporate culture, etc., based on the daily statements of administrators, etc.

[0053] Through the above process, managers and other personnel will be able to review work reports using conversational AI. Even busy managers and other personnel will be able to understand their subordinates' work reports and issues via voice or other means during spare time, such as while commuting. Furthermore, by analyzing conversational data from managers and other personnel, it will be possible to analyze the company culture.

[0054] Personality Diagnosis The analysis unit 116 performs personality analysis based on conversation data, including at least one of personality aptitude assessment, character assessment, and emotional intelligence (EQ) assessment. The analysis unit 116 can, for example, use conversational AI processing to record a history of the conversation data.

[0055] (Personality aptitude test) Analysis Unit 116 diagnoses adaptability to work and the workplace environment based on the history of conversation data as part of a personality aptitude assessment. Based on the history of conversation data, Analysis Unit 116 diagnoses items such as leadership, problem-solving ability, adaptability, communication ability, teamwork ability, and self-management.

[0056] The conversation control unit 112 inserts questions corresponding to each diagnostic item of the personality aptitude test into the questions in the work report and prompts the user for further information. For example, the conversation control unit 112 may prompt the user for questions related to each diagnostic item of the personality aptitude test separately within a predetermined period (e.g., 30 days), and the analysis unit 116 may perform the personality aptitude test based on the user's answers to the questions for each diagnostic item. This allows the user to perform the personality aptitude test in addition to submitting their work report. Alternatively, the analysis unit 116 may input the conversation data from the user's work report into an existing diagnostic engine and have it perform the above-mentioned diagnostic test. Furthermore, the analysis unit 116 may input the conversation data of each user into a trained model that has learned the relationship between the conversation data from the work report and the above-mentioned diagnostic items, and obtain the results for each diagnostic item. The personality aptitude test results can be effectively utilized in the user's career planning.

[0057] (Personality assessment) The analysis unit 116 diagnoses traits to understand inner characteristics based on the history of conversation data as part of a personality assessment. The analysis unit 116 may diagnose at least one of the following: Big Five personality traits ("Openness," "Conscientiousness," "Extraversion," "Agreeableness," and "Neuroticism"), self-efficacy, locus of control, perseverance (GRIT), values, temporal perspective, social skills, self-control, conscientiousness, self-esteem, mindset, optimism / pessimism, learning style, creativity, moral judgment, and resilience.

[0058] For example, the service provider 111 may ask questions about each diagnostic item for personality assessment during user registration, and perform a personality assessment based on the user's answers to these questions. For example, the Big Five personality traits can be assessed by having the user answer the following questions on a 6-point scale from 1 (strongly disagree) to 6 (strongly agree) (https: / / oshio.kinsta.cloud / scales / ). • Things will go better if you clarify ambiguous matters into black and white. I think everyone can be divided into "winners" and "losers." I want to clarify what is safe and what is dangerous. Clearly defining boundaries in everything makes things much easier. Every problem has a "correct" and an "incorrect" answer. I want to clearly distinguish between information that is useful to me and information that is not. Furthermore, the conversation control unit 112 may insert questions corresponding to each diagnostic item of the personality assessment into the questions in the work report and ask the user. For example, the conversation control unit 112 may ask the user questions for each diagnostic item of the personality assessment separately within a predetermined period (e.g., 30 days), and the analysis unit 116 may update the personality assessment based on the user's answers to the questions for each diagnostic item. This makes it possible for the user to take a personality assessment while submitting their work report. The personality assessment only needs to be updated at predetermined intervals. This is because personality does not change easily, so daily updates are unnecessary, for example. The analysis unit 116 may also input the user's conversation data from the work report into an existing personality assessment engine and have it perform the above-mentioned diagnostics. Alternatively, the analysis unit 116 may input each user's conversation data into a trained model that has learned the relationship between the conversation data from the work report and the above-mentioned diagnostic items, and obtain the results for each diagnostic item. The personality assessment results can be effectively used for self-understanding and improving interpersonal relationships.

[0059] (EQ assessment) The analysis unit 116, as part of the EQ assessment, diagnoses various diagnostic items focusing on emotional management and interpersonal skills based on the history of conversation data. The analysis unit 116 may diagnose at least one of the following: self-awareness, social awareness, motivation, self-management, interpersonal skills, and empathy.

[0060] The conversation control unit 112 inserts questions corresponding to each diagnostic item of the EQ diagnosis into the questions of the work report and asks the user. For example, the conversation control unit 112 may ask the user questions for each diagnostic item of the EQ diagnosis separately within a predetermined period (e.g., 30 days), and the analysis unit 116 may perform the EQ diagnosis based on the user's answers to the questions for each diagnostic item. This makes it possible for the user to perform the EQ diagnosis at the same time as submitting their work report. Alternatively, the analysis unit 116 may input the conversation data from the user's work report into an existing EQ diagnosis engine and have it diagnose each of the above diagnostic items. Alternatively, the analysis unit 116 may input the conversation data of each user into a trained model that has learned the relationship between the conversation data from the work report and each of the above diagnostic items and obtain the results for each diagnostic item. The EQ diagnosis results can be effectively used to solve emotional issues. For more information on EQ diagnosis, please refer to the applicant's Patent Publication No. 7487986.

[0061] Through the above processing, users can deepen their self-understanding and experience daily growth through daily interactions with the conversational AI. Furthermore, the analysis unit 116 can display the analysis results on the user's terminal dashboard screen, enabling the following: • AI can analyze and display today's emotions. • You can check the diagnostic indicators, which are updated daily. AI that understands itself can provide appropriate advice.

[0062] The conversation control unit 112 may also include changing the content of the conversation by the conversational AI according to the diagnosed personality. For example, the conversation control unit 112 inputs at least one of the following into the generating AI used by the conversational AI: a personality aptitude test, a character test, and an EQ test. Specifically, when generating a conversation during a business report, the conversation control unit 112 may include instructions in the prompts of the generating AI used by the conversational AI processing to generate conversation data considering the diagnosed personality test results of the user. The analysis unit 116 may construct an AI that generates the user's personality using the evaluated personality test results.

[0063] Through the above process, it becomes possible to customize the content of conversations for each individual user in the conversational AI processing that users use on a daily basis. As a result, the more each user utilizes the disclosure technology service, the more user-friendly the conversational AI becomes. Furthermore, it becomes possible to generate a personality for each user using the results of personality assessments.

[0064] ≪Facial expression analysis≫ The acquisition unit 113 includes acquiring facial expression data during the user's conversation. The acquisition unit 113 uses the camera function of the user's processing unit 20 to acquire facial expression data during the business report.

[0065] The analysis unit 116 analyzes the acquired facial expression data and quantifies the emotion. The analysis unit 116 may also understand the meaning of facial expressions, posture, hand movements, etc., through the camera and infer the emotion. For example, if an AI that analyzes emotions from facial expressions is already publicly known, the analysis unit 116 may use this publicly known emotion recognition AI to acquire emotion data (joy, sadness, surprise, anger, etc.). The analysis unit 116 may also include understanding the user's psychological state from the analyzed user emotion data.

[0066] Through the above process, it becomes possible to analyze the user's facial expressions when using conversational AI and inform the user of their emotions. It also becomes possible to visualize the user's emotions in real time.

[0067] ≪Integration of internal data≫ The acquisition unit 113 includes acquiring internal data, including data set in the calendar function used by the user, data entered via the chat function, and / or document data including rule data, labor management data, or employee data managed by the organization to which the user belongs.

[0068] For example, the acquisition unit 113 may acquire user schedule data set in the calendar function used by the user, or acquire user text data entered using a chat tool. The schedule data is used to select candidate dates for events (meetings, interviews, etc.). The text data from the chat function may be used for the personality assessment described above. The acquisition unit 113 may also acquire document data, including rule data, labor management data, or employee data, managed by the organization to which the user belongs, from an internal database.

[0069] The conversation control unit 112 may also include having the conversational AI process converse based on the acquired internal company data. For example, by incorporating internal company data into the generative AI or learning model used in the conversational AI process, the conversation control unit 112 may have the AI ​​converse about available dates and times based on schedule data, report personality diagnosis results and work report contents based on text data entered into the chat function, or converse about the information and confirmations related to the work described later based on internal document data.

[0070] Through the above process, by incorporating data used within the company, it becomes possible to resolve business-related issues using conversational AI processing. For example, it becomes possible to use conversational AI processing to enable users to perform tasks such as scheduling, supplementing personality assessment data, supplementing work content data, and answering other questions and confirmations related to personnel and labor.

[0071] The service provision unit 111 may also include storing each user's business report data and internal company data in a storage device (an example of a storage unit) 130. The function unit 117 may further perform AI processing corresponding to a predetermined function based on each business report data and / or internal company data stored in the storage device 130. The predetermined function is, for example, a function that supports tasks related to labor and personnel management.

[0072] Through the above processing, it becomes possible to support tasks related to labor and human resources in addition to business reporting, by using not only conversation data obtained from users, but also schedule data used by the organization, input data from the chat function, and document data stored in the organization's database.

[0073] ≪Evaluation Module≫ If the specified function includes an evaluation function, the functional unit 117 may also include performing AI processing to set goals for a specified user's work or to evaluate the specified user's work based on each business report data and internal company data. For example, the evaluation module of the functional unit 117 may use AI processing to set goals and conduct evaluation interviews for each user.

[0074] The functional unit 117, as a concrete example, sets evaluation indicators and visualizes performance results and user performance based on business report data. For example, the functional unit 117 learns in advance the relationship between the user's business report data and past user evaluations, and obtains user evaluation data from the business report data.

[0075] Through the above process, by evaluating users, administrators and others can make decisions about assigning the right people to the right positions, thereby improving the accuracy of the use of disclosure technology.

[0076] ≪Modules to be adopted≫ If the specified function includes a recruitment function, the functional unit 117 may include AI processing to ask questions to job candidates based on each business report data and internal company data. For example, the functional unit 117 uses a generating AI to perform the questions that the human resources department would ask a candidate undergoing a job interview. Specifically, the functional unit 117 prompts the generating AI to start a conversation by including in the prompt that it should ask questions as a human resources interviewer. The functional unit 117 then asks the next questions based on the user's conversation data. The functional unit 117 may also include in the prompt the AI ​​to ask questions as if it were a human resources interviewer, using the personality assessment results of the human resources interviewer and employee data.

[0077] Through the above process, managers and other personnel can streamline their work by having AI handle the time-consuming task of conducting job interviews.

[0078] ≪Guidance Module≫ If the specified function includes a guidance function, the functional unit 117 may also include performing AI processing to provide onboarding guidance or answers to labor-related inquiries based on internal company data. For example, the functional unit 117 may import internal company document data containing onboarding guidance or internal company document data containing labor management rules, etc., into the LLM, specify these internal company document data, and input prompts for questions from managers, etc., into the generating AI.

[0079] Through the above process, administrators and others can streamline their work by having AI handle time-consuming tasks such as providing guidance and responding to inquiries.

[0080] ≪Verification Module≫ If the specified function includes a verification function, the functional unit 117 may also include performing AI processing to verify employment history or reasons for leaving based on internal company data. For example, the functional unit 117 may import employee data into the LLM and, when it obtains questions such as verifying the employment history or reasons for leaving of a specified user, it may use a generating AI to provide answers.

[0081] Through the above process, managers and others can streamline their work by having AI handle time-consuming tasks such as verifying employment history and answering questions about reasons for leaving.

[0082] ≪Consultation Module≫ If the predetermined function includes a consultation function, the functional unit 117 may also include AI processing to receive mental health or career consultations from each user based on internal company data and / or personality diagnosis results, etc. For example, the functional unit 117 inputs instructions to the generating AI to include the personality of the user seeking consultation and the content of the consultation in the prompt, and obtains an answer.

[0083] Through the above processing, things that would normally be difficult to say become easier to say because the other party is an AI, and by utilizing conversational AI processing, even users with low language expression abilities can be assisted in conversation.

[0084] As described above, the disclosure technology can combine conversational AI, emotional AI, analytical and evaluation AI, and personality generation AI as needed to accumulate conversational data, emotional data, analytical data, and / or personality data. The disclosure technology can use this data to build an organization's information infrastructure. Furthermore, it is possible to switch from the aforementioned conversational format to a chat format using conversational AI without using avatar AI, depending on the environment. This allows users to report according to their usage scenarios and work styles.

[0085] ≪Examples of each data set≫ Next, examples of data stored in the storage device 130 of the server 10 will be described using Figures 4 and 5. Figure 4 is a diagram showing an example of employee information according to one embodiment. Figure 5 is a diagram showing an example of employee-related information according to one embodiment.

[0086] The employee information shown in Figure 4 includes various data / information such as employee ID, name, contact information, address, department, and employment status. The employee ID includes the employee ID of employees (general employees, managers, and executives) who use the system disclosed here. The name includes the user's name information. The contact information includes information such as telephone number, email address, and social media accounts. The address includes the employee's address, and the department includes the department to which the employee belongs. The employment status includes the employee's employment type. In addition, information such as date of birth, job title, performance evaluation, skills, and marital status may also be included in the employee information.

[0087] The employee-related information shown in Figure 5 includes various data / information such as employee ID, conversation data, emotion data, analysis data, personality data, report data, and office data. The employee ID is the same example as the employee ID in the employee information shown in Figure 4. Conversation data is conversation data acquired by conversational AI processing, and a history may be stored. Emotion data includes emotion data analyzed from conversation data and / or facial expression data, etc. Analysis data includes issues analyzed based on conversation data. Personality data includes data that shows the characteristics of the user's personality, formed based on accumulated conversation data and personality diagnosis results, etc. Report data includes work report data generated from the user's conversation data when reporting work. Office data is internal company data including data set in the calendar function used by the user, data entered via the chat function, and / or document data including rules data, labor management data, or employee data managed by the organization to which the user belongs.

[0088] <Processing device configuration> Figure 6 shows an example of a processing unit 20 according to one embodiment of the disclosure. For example, the processing unit 20 is a device used by employees (including managers) of an organization. The processing unit 20 includes one or more processors (e.g., CPUs) 210, one or more network communication interfaces 220, a storage device (storage unit) 230, a user interface 250, and one or more communication buses 270 for interconnecting these components. Hereinafter, when the processing unit 20 is used by employees, each component is denoted by the code A; when the processing unit is used by managers, each component is denoted by the code B; and when the processing unit is used by executives, each component is denoted by the code C.

[0089] The user interface 250 includes a display 251 and an input device (such as a keyboard and / or mouse, or any other pointing device) 252.

[0090] The storage device 230 is, for example, a high-speed random-access memory (main memory) such as DRAM, SRAM, or other random-access solid-state memory. Alternatively, the storage device 230 may be one or more non-volatile memories (secondary storage) such as magnetic disk storage devices, optical disk storage devices, flash memory devices, or other non-volatile solid-state memory. The storage device 230 may also be a computer-readable non-temporary recording medium. Furthermore, the storage device 230 may be either main memory (memory) or secondary storage (storage), or it may include both.

[0091] The storage device 230 stores data and programs used by the information processing system 1. For example, the storage device 230 stores application programs for the processing unit 20 in the information processing system 1.

[0092] The processor 210 constitutes the service processing unit 211 by executing a program stored in the storage device 230. The service processing unit 211 includes, for example, a web browser and an email application. The web browser enables the viewing of web pages provided by the server 10. Furthermore, the execution of an application for the installed user terminal enables the viewing of web pages that provide the aforementioned services. The service processing unit 211 has a communication control unit 212, a display control unit 213, and an operation control unit 214 in order to receive services.

[0093] The communication control unit 212 acquires screen information for various screens related to disclosure technology transmitted from the server 10. For example, the communication control unit 212A of the processing unit 20A used by employees acquires screen information for various screens such as the work report screen using conversational AI processing, the screens of various function modules available to general employees, and the evaluation screens for general employees. The communication control unit 212B of the processing unit 20B used by administrators acquires screen information for various screens such as the management screen for receiving work reports from general employees and the screens of various function modules available to administrators. The communication control unit 212C of the processing unit 20C used by managers acquires screen information such as the management screen for receiving work reports from employees and the screens of various function modules available to managers. The communication control unit 212 outputs to the server 10 information selected and set using each screen, predetermined requests, and work information related to the service.

[0094] The display control unit 213 controls the display of screens related to the service on the display 251 based on the screen information acquired by the communication control unit 212. For example, the display control unit 213A of the processing unit 20A used by employees controls the display of various screen information such as the work report screen using conversational AI processing, the screens of each function module available to general employees, and the evaluation screens of each general employee. Similarly, the display control unit 213B of the processing unit 20B used by administrators controls the display of various screen information such as the management screen for receiving work reports from general employees and the screens of each function module available to administrators. The display control unit 213C of the processing unit 20C used by managers controls the display of various screen information such as the management screen for receiving work reports from employees and the screens of each function module available to managers.

[0095] The operation control unit 214 receives user operations on UI components displayed on each screen and transmits the operation information to the application on the processing unit 20 or outputs it to the server 10. For example, the operation control unit 214 outputs various labor and personnel information selected, set, or entered by employees, managers, or executives to the server 10.

[0096] The communication control unit 212 transmits each operation information received by the operation control unit 214 to the server 10 via the network communication interface 220.

[0097] Through the above process, the processing unit 20 used by employees, managers, or executives can perform processing in cooperation with the server 10, and use conversational AI processing to acquire, analyze, and evaluate conversational data from users. Furthermore, as mentioned above, by using conversational AI processing, users can report on their work in a relaxed environment where they can speak at their own pace.

[0098] <Operation Description> Next, we will describe the various operations of the information processing system 1. Figure 7 is a flowchart of an example of business report processing according to one embodiment. The example shown in Figure 7 is an example of processing when the server 10 receives a business report from a user using conversational AI processing.

[0099] In step S102, the conversation control unit 112 of the server 10 provides conversational AI processing to the user terminal used by the user. For example, the conversational AI processing uses a generation AI and an avatar AI to enable more natural conversations.

[0100] In step S104, the acquisition unit 113 of the server 10 acquires conversational data related to the user's work report through conversational AI processing of the work report. For example, the acquisition unit 113 acquires live conversational data from daily work reports in a natural conversation through conversational AI processing by a work report module requested by the employee.

[0101] In step S106, the generation unit 114 of the server 10 generates user business report data based on the user's conversation data acquired by the acquisition unit 113. For example, the generation unit 114 uses AI processing to aggregate and analyze conversation data, including daily work content and work progress, and generates business report data.

[0102] In step S108, the output unit 115 of the server 10 outputs the business report data generated by the generation unit 114 to an administrator terminal used by the user's administrator. For example, the output unit 115 outputs the business report data generated by AI processing to a processing unit 20B used by the administrator.

[0103] Through the above process, by utilizing conversational AI processing, it becomes possible to appropriately obtain information from employees and others in daily operations. Furthermore, by using conversational AI processing in the daily work reports that employees must submit, it is possible to increase the amount of information provided through conversation without burdening employees. In addition, since work report data is generated by the user engaging in conversations about work reports, work efficiency is improved.

[0104] Figure 8 is a flowchart illustrating an example of processing after acquiring conversation data according to one embodiment. The example shown in Figure 8 is an example of the analysis processing of server 10.

[0105] In step S202, the analysis unit 116 analyzes the acquired conversation data or facial expression data to quantify the emotions. For example, the analysis unit 116 may understand the meaning of facial expressions, posture, hand movements, etc., through the camera and infer emotions. The analysis unit 116 may also read the intent and emotions of the conversation from the content of the conversation, tone of voice, speed, and emphasis, based on natural language processing of the conversation data and analysis of the speech data.

[0106] In step S204, the analysis unit 116 performs analysis and evaluation based on the conversation data. This analysis and evaluation may include, for example, personality diagnosis or identification of issues.

[0107] In step S206, the analysis unit 116 performs a personality analysis of each user. For example, the analysis unit 116 forms the user's personality based on the personality diagnosis results. For example, if the number of times an item A is evaluated above a predetermined value exceeds a threshold among the items evaluated in the personality diagnosis results, then the user may be said to possess the characteristics of item A, and these characteristics of item A may represent the user's personality. Note that steps S202 to S206 only need to be performed if at least one of them is executed.

[0108] As described above, the disclosure technology can combine conversational AI, emotional AI, analytical and evaluation AI, and personality generation AI as needed to accumulate conversational data, emotional data, analytical data, and / or personality data. The disclosure technology can use this data to build an organization's information infrastructure.

[0109] Figure 9 is a flowchart illustrating an example of the processing of each functional module according to one embodiment. In the example shown in Figure 9, the server 10 executes each process when the user selects one of them.

[0110] In step 302, the service provision unit 111 of the server 10 determines whether each trigger related to the service has occurred. For example, if the acquisition of conversation data is the trigger, the process proceeds to step S304; if the user (administrator) operation indicates an employment process, the process proceeds to step 306; if the user (administrator) operation indicates a guidance process, the process proceeds to step S308; if the user (administrator) operation indicates a confirmation process, the process proceeds to step S310; and if the user (general employee) operation indicates a consultation process, the process proceeds to step S312.

[0111] In step S304, the functional unit 117 of the server 10 performs AI processing to set goals for a given user's work or to evaluate a given user's work based on each business report data and internal company data. For example, the evaluation module of the functional unit 117 uses AI processing to set goals and conduct evaluation interviews for each user.

[0112] In step S306, the functional unit 117 may include performing AI processing to ask questions to job candidates based on each business report data and internal company data. For example, the functional unit 117 may use a generating AI to generate questions that the human resources department would ask job candidates undergoing interviews.

[0113] In step S308, the functional unit 117 may include performing AI processing to provide answers to onboarding instructions or labor-related inquiries based on internal company data. For example, the functional unit 117 may import internal document data containing onboarding instructions or internal document data containing labor management rules into the LLM, specify these internal document data, and input prompts for questions from managers or executives into the generating AI.

[0114] In step S310, the functional unit 117 may include performing AI processing to verify employment history or reasons for leaving an employee based on internal company data. For example, the functional unit 117 may import employee data into the LLM and, when it obtains questions such as verifying the employment history or reasons for leaving a designated user, it may use the generated AI to provide answers.

[0115] In step S312, the functional unit 117 may include AI processing to receive mental health or career consultations from each user based on personality diagnosis results, etc. For example, the functional unit 117 inputs instructions to the generating AI to include the personality of the user seeking consultation and the content of the consultation in the prompt, and obtains a response.

[0116] Through the above process, not only can business reports be automatically generated, but conversational AI processing can be used to support various labor and human resources-related tasks, thereby streamlining complex operations.

[0117] <Screen example> Next, we will describe an example of each screen displayed in the information processing system 1. Figure 10 is a diagram showing an example of the execution screen of a conversational AI according to one embodiment. Screen D2 shown in Figure 10 shows an example of a screen in which a conversational AI avatar is activated to generate a daily report as a business report, and the user is interviewed about the contents of the business report.

[0118] As shown in Figure 10, users can input work report content by interacting with an avatar, eliminating the need for tedious text input. Furthermore, as mentioned above, the avatar is created using a personality-generating AI that understands the user, making it easier for the user to talk and discuss issues.

[0119] Figure 11 illustrates the concept of work reporting between a subordinate and a superior according to one embodiment. In screen D4 shown in Figure 11, Mr. Yamada from the sales department uses conversational AI to submit a work report, and the server 10 automatically generates the work report data. Similarly, work report data for each employee in the sales department is generated. In the example shown in Figure 11, Mr. Taniguchi from the sales department uses conversational AI to receive work reports from his subordinates. As shown in Figure 11, the AI ​​in the disclosure technology shares key information from the field.

[0120] Department Manager Taniguchi can select employees with issues from within the sales department and receive work reports from those employees. Employees with issues can be identified through the analysis of conversation data by the Analysis Department 116.

[0121] Figure 12 shows a concept of reporting work to management according to one embodiment. In screen D6 shown in Figure 12, the manager asks the conversational AI about the progress of each department. At this time, the conversational AI reports the work report data of each employee, which has been aggregated by the generation unit 114, to the manager. This makes it possible to aggregate the situation on site on the day in a conversational manner and report it to the manager or executive.

[0122] Figure 13 shows an example of an employee dashboard screen according to one embodiment. Screen D8 in Figure 13 has a business report area and a personality diagnosis area. For example, in the business report area, when the user operates the business report area, conversational AI processing as shown in Figure 10 is executed, allowing the user to perform business reports in a dialogue format. Also, when the user operates the personality diagnosis area shown in Figure 13, the personality diagnosis results screen shown in Figure 14 may be displayed.

[0123] Figure 14 shows an example of the results of a personality diagnosis according to one embodiment. Screen D10 in Figure 14 may display three diagnosis results: EQ diagnosis, personality aptitude diagnosis, and character diagnosis. In the example shown in Figure 14, each item is listed for each diagnosis, but a diagram such as a radar chart may be used to make it easy for each user to understand which evaluation values ​​are high. Users can keep a history of changes in their diagnosis results so far, deepen their self-understanding through daily conversations with the conversational AI, and feel their daily growth.

[0124] Figure 15 shows an example of a management dashboard screen according to one embodiment. Screen D12 shown in Figure 15 includes an area for receiving subordinates' work reports and an area for understanding issues, such as those analyzed by the analysis unit 116. In the work report area, it is possible to listen to each employee's work reports through conversation, as shown in Figure 11 or Figure 12, or to receive work reports aggregated by department.

[0125] On the screen for identifying issues, the issues extracted by the analysis unit 116 are displayed. Furthermore, the manager's dashboard may use a calendar function to display the average of predetermined employee scores on a daily basis. These predetermined scores could be, for example, engagement scores, healthcare scores, or scores related to the extracted issues. The analysis unit 116 may also calculate an organizational score, which indicates the state of the organization, based on conversational data from employees. The organizational score may be calculated by quantifying the following items: motivation, communication, engagement, emotions, opinions / ideas, feedback, job satisfaction, problem-solving ability, career growth, stress levels, information literacy, and work-life balance, and then substituting these values ​​into a predetermined function. The values ​​for each item may be calculated from each employee's conversational data based on the number of times they make statements corresponding to each item. For example, a conversational AI may periodically ask questions about motivation, and the motivation score may be calculated based on their answers.

[0126] As described above, the disclosed technology provides a mechanism for smoother organizational operations by using conversational AI to provide daily care for employees. Figure 16 shows an example of a cycle of work visualization, growth support, and engagement enhancement according to one embodiment. In the example shown in Figure 16, employees use the aforementioned conversational AI to submit daily work reports. This allows employees to submit work reports easily, deepen their self-understanding by grasping the results of personality assessments, and visualize their growth by strengthening areas for improvement. Furthermore, based on the employees' work reports, the analysis unit 116 uses the aforementioned AI processing to aggregate and analyze each individual's work and mental state. This enables an understanding of work, analysis of individual situations, and aggregation and organization of issues. In addition, management and supervisors can grasp the analysis results from the analysis unit 116 through the dashboard, etc. For example, management and supervisors can grasp the work content and individual situations analyzed by the analysis unit 116 and respond to issues. Furthermore, regarding the response to challenges, the AI ​​processing by the analysis unit 116 identifies areas for improvement, suggests areas for improvement, and supports business improvement and organizational development. For example, the analysis unit 116 can obtain areas for improvement by inputting the content of the challenge and prompts asking for areas for improvement to address the challenge to the generating AI. By suggesting these areas for improvement to employees, employees can put the improvements into practice and feel a sense of growth. By repeating the cycle described above, it is possible to visualize the work of employees, allow them to feel a sense of growth within the organization through daily work reports, and improve their engagement.

[0127] The embodiments described above are illustrative examples for explaining the disclosed technology and are not intended to limit the disclosed technology to these embodiments only. The disclosed technology can be modified in various ways as long as it does not deviate from its essence. Furthermore, the processing on the server side and the user's processing unit side may be integrated as appropriate, or processing may be transferred to the other device or to another device. [Explanation of symbols]

[0128] 1...Information processing system, 10...Server, 20...Processing device, 110...Processor, 130...Storage device, 111...Service provision unit, 112...Conversation control unit, 113...Acquisition unit, 114...Generation unit, 115...Output unit, 116...Analysis unit, 117...Function unit, 210...Processor, 211...Service processing unit, 212...Communication control unit, 213...Display control unit, 214...Operation control unit, 230...Storage device, 251...Display

Claims

1. Information processing device, To provide conversational AI processing on the user's terminal. To obtain conversational data regarding the user's business report through the conversational AI processing of the business report, Based on the aforementioned conversation data, generate the user's business report data. Output the aforementioned business report data to the administrator terminal used by the administrator of the aforementioned user. An information processing method that performs the following.

2. The aforementioned information processing device Further analysis of the aforementioned conversation data is performed to extract issues related to the user or the organization to which the user belongs. The output mentioned above is, The information processing method according to claim 1, further comprising outputting the extracted issues to the administrator terminal.

3. The above generation is, To collect business report data from each user, Based on the collected business report data, extract specific report content that meets the prescribed criteria. The information processing method according to claim 1, further comprising generating the business report data by making the extracted specific report content selectable by the administrator.

4. The output mentioned above is, The information processing method according to any one of claims 1 to 3, further comprising reporting the aforementioned business report data to the administrator using conversational AI processing.

5. The aforementioned information processing device The information processing method according to claim 4, further comprising obtaining conversational data from the administrator using the conversational AI processing when reporting the business report data.

6. The aforementioned information processing device The information processing method according to claim 1, further comprising performing an analysis of personality, including at least one of a personality aptitude test, a character test, and an emotional intelligence (EQ) test, based on the aforementioned conversation data.

7. The aforementioned information processing device The information processing method according to claim 6, further comprising changing the content of the conversation by the conversational AI processing according to the diagnosed personality.

8. To obtain the above means, This includes obtaining facial expression data of the user during the conversation, The above analysis is, The information processing method according to claim 6, further comprising analyzing the user's emotions from the facial expression data.

9. To obtain the above means, This includes acquiring internal company data, including data set in the calendar function used by the user, data entered via the chat function, and / or document data including rule data, labor management data, or employee data managed by the organization to which the user belongs. The provision described above means, The information processing method according to claim 1, further comprising having the conversational AI process engage in a conversation based on the aforementioned internal company data.

10. The aforementioned information processing device The aforementioned business report data and internal company data for each user are stored in the storage unit. The information processing method according to claim 9, further performing AI processing corresponding to a predetermined function based on each business report data and / or the internal company data stored in the memory unit.

11. Performing the aforementioned AI processing is The information processing method according to claim 10, wherein the predetermined function includes an evaluation function, and further includes performing AI processing to set goals for the work of a predetermined user or to evaluate the work of a predetermined user based on the respective business report data and the internal company data.

12. Performing the aforementioned AI processing is If the predetermined function includes a recruitment function, the information processing method according to claim 10 includes performing AI processing to ask questions to job candidates based on the respective business report data and the internal company data.

13. Performing the aforementioned AI processing is If the predetermined function includes a guidance function, the information processing method according to claim 10 includes performing AI processing to provide onboarding guidance or respond to labor inquiries based on the internal company data.

14. Performing the aforementioned AI processing is If the predetermined function includes a verification function, the information processing method according to claim 10 includes performing AI processing to verify employment history or reason for resignation based on the internal company data.

15. Performing the aforementioned AI processing is If the predetermined function includes a consultation function, the information processing method according to claim 10 includes performing AI processing to provide mental health or career consultations to each user based on the internal company data.

16. In an information processing device, To provide conversational AI processing on the user's terminal. To obtain conversational data regarding the user's business report through the conversational AI processing of the business report, Based on the aforementioned conversation data, generate the user's business report data. Output the aforementioned business report data to the administrator terminal used by the administrator of the aforementioned user. A program that executes the command.

17. An information processing device having a processor, The aforementioned processor, To provide conversational AI processing on the user's terminal. To obtain conversational data regarding the user's business report through the conversational AI processing of the business report, Based on the aforementioned conversation data, generate the user's business report data. Output the aforementioned business report data to the administrator terminal used by the administrator of the aforementioned user. An information processing device that performs the following actions.

Images