Information processing system, information processing method, and program

Abstract

Information processing system and information processing method for supporting the use and deployment of AI agents , and to provide programs. The agent stores information about the AI ​​agents that are introduced in each organization. a user information storage unit that stores personnel information of each user; Information indicating the organization that introduced the I-Agent and information indicating operational constraints can be shared between organizations. a metadata assignment unit that assigns various metadata to the AI ​​agent, and Based on the operational constraints set in the metadata of the AI ​​agent, Among the AI ​​agents whose original organization is different from the organization, an access control unit that identifies an accessible AI agent according to the information; Processing System

Description

[Technical Field]

[0001] The present disclosure relates to an information processing system, an information processing method, and a method for managing AI agents operated within an organization. The present invention relates to a processing method and a program. [Background technology]

[0002] In recent years, AI agents capable of natural language processing have become increasingly popular in various industries for the purpose of improving business efficiency. For example, in Patent Document 1, an AI agent A system has been disclosed that uses this to generate product improvements based on user posted information. do. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Application Publication No. 2025-042762 Summary of the Invention [Problem to be solved by the invention]

[0004] Challenges in promoting the use of AI agents in business in organizations such as companies include: ,AI agents are developed by specific organizations or specific individuals, such as the development department or the department where they were initially introduced. The use of AI agents is limited to a single user, resulting in personalization and slow progress in their deployment. In addition, there was objective information to judge the effectiveness and sharability of AI agents. There is also the issue of difficulty in assessing the appropriateness of introducing AI agents due to the lack of knowledge.

[0005] One of the objectives of the exemplary embodiments of the present disclosure is to develop a The present invention provides an information processing system, an information processing method, and a program for the above purposes. [Means for solving the problem]

[0006] An information processing system according to one aspect of the present disclosure includes: Agent information recorder that stores information about AI agents deployed in each organization Memories and a user information storage unit that stores personnel information of each user; Information indicating the organization from which the AI ​​agent was introduced, and the operational system of the AI ​​agent The information indicating the contract is assigned to the AI ​​agent as metadata that can be shared between organizations. a metadata assigning unit for assigning the metadata to the metadata; Based on the operational constraints set in the metadata of each of the AI ​​agents, Based on this, among the AI ​​agents whose original organization is different from the organization to which a user belongs, From the information, an accessible AI agent is identified according to the personnel information of the user. and an access control unit.

[0007] By having the above characteristics, the information processing system allows users to easily access A Among the I-agents, an AI agent that can be accessed according to the user's own personnel information This will support the deployment of cross-organizational AI agents. It is possible.

[0008] Other problems and solutions disclosed in the present application are described in the embodiments of the present disclosure. and the drawings. [Brief explanation of the drawings]

[0009] [Figure 1] FIG. 1 is a diagram illustrating an example of the configuration of an information processing system according to an embodiment of the present disclosure. [Figure 2] FIG. 2 is a block diagram illustrating an example of a hardware configuration of the information processing system shown in FIG. [Figure 3] FIG. 3 is a block diagram illustrating an example of the software configuration of the information processing system shown in FIG. [Figure 4] FIG. 4 is a schematic diagram showing an example of a user interface presenting accessible AI agents. [Figure 5] FIG. 5 is a schematic diagram showing an example of a user interface that presents the operational performance of an AI agent. [Figure 6] FIG. 6 is a flowchart showing an example of information processing executed in the information processing system shown in FIG. DETAILED DESCRIPTION OF THE INVENTION

[0010] An information processing system according to an embodiment of the present disclosure will be described below with reference to the drawings. In the accompanying drawings, the same or similar elements are designated by the same or similar reference numerals and names. In the description of the embodiments, redundant descriptions of the same or similar elements will be omitted. It should be noted that the contents shown in the drawings are merely examples for explaining the present embodiment. The drawings are merely examples that show a schematic view to facilitate explanation of the present embodiment. Modifications and changes may be made within the scope that does not cause technical problems.

[0011] <System Overview> The information processing system according to this embodiment is an AI agent operated by a specific business entity. and manage the AI ​​agent sharing across organizations belonging to the business entity. This is a system to support the deployment of use.

[0012] Here, "entity" means an organizational form or legal framework for carrying out a given business activity. The business entities that will operate this system are not limited to a single corporation, but also include research institutions, non-profit organizations, etc. (School corporations, medical corporations, etc.), non-corporate organizations, public organizations, public interest corporations, and business associations An entity may be any entity consisting of at least two or more organizations or companies. There shall be two or more organizations to which each member belongs.

[0013] In this embodiment, the term "organization" refers to any classification unit that constitutes the above-mentioned business entity. For example, if an entity is made up of multiple companies, each company will be treated as an organizational entity. Alternatively, classification units such as departments within each company may be used as organizational units. In the case of a single business entity, the organization has business departments such as sales, development, and human resources. It may also include organizational units that are divided according to their location, such as branch offices. In addition to business divisions, there are also groups for classifying individual business owners and groups for classifying contractors. Groups that categorize collaborators, etc., are defined according to the organizational activities or business involvement forms. Groups defined by classification criteria may also be included. Based on predetermined criteria such as classification, business domain, contract type, location, or collaboration scheme can be flexibly defined.

[0014] An "AI agent" is an artificial intelligence that autonomously performs predetermined tasks on behalf of a user. AI agents are systems that can react to user input, predefined settings, and Based on the settings, etc., execute information processing related to a specified business and output the processing results. The specific implementation functions of the AI ​​agent are not particularly limited. For example, natural language processing, image analysis, data aggregation, predictive analysis, decision support, document creation, and automation It has one or more features such as response, conversational interface, and workflow automation. In this embodiment, a business entity may operate multiple AI agents. For example, automatic creation of sales proposals, automatic response to inquiries from customers, recruitment It is used for one or more business tasks, such as selection support and development code review support. AI agents may be used. Such AI agents may be included in the business entity. It may be developed internally within any organization or acquired from an external vendor within the enterprise. It may be provided to any organization.

[0015] The implementation form of the AI ​​agent used by the business entity is not particularly limited. Agents are designed to operate within an entity's internal network, such as a corporate network. It may be integrated into the body's internal systems and operated by the AI ​​agent. , implemented in an external system such as a cloud infrastructure provided by an external cloud provider. It may also be used through inter-system collaboration methods such as API integration. The agent can communicate with the company through the network, whether it is inside or outside the company that is implementing this system. If it can be used as such, it can be managed in this system.

[0016] In this embodiment, a single corporate entity is a user entity of the system. We will use the example of managing AI agents operated in each department included in the information processing system. However, this example is merely an example and does not necessarily represent the actual system. The use cases to which the system can be applied are not limited to this example.

[0017] Each organization in the business entities mentioned above will independently introduce or customize AI agents. If this is the case, the personalization or division of AI agents within a specific organization or specific person may occur. This will lead to divisionalization, and even AI agents that can contribute to the overall business will not be deployed across departments. In addition, the data assets used in AI agents may not be developed sufficiently. If personal information and / or confidential information is included in the data, the AI ​​agent may be carelessly used by others. In some cases, there are circumstances that prevent the deployment of AI agents to other departments. When deploying AI assets horizontally, it is necessary to verify their sharability and effectiveness. The management system does not clearly state the effects of introducing AI agents and their scope of application. However, it was difficult to make cross-departmental decisions regarding implementation.

[0018] In the information processing system of this embodiment, for each AI agent, the organization from which it was introduced, It is equipped with a function to add attribute information including target business operations, operational constraints, etc. as metadata. In addition, the operational constraints set in the metadata and the personnel information (affiliation) managed for each user Based on the user's name (organization, position, etc.), the system selects the user from among the AI ​​agents introduced by other organizations. This allows for the user to specify which AI agents are accessible to the user. It is possible to systematically and objectively decide whether or not to share AI agents, which tend to be operated in a closed environment. This will support the safe and effective deployment of AI agents across organizations. The details of this system will be explained below using examples shown in the drawings.

[0019] <System configuration> As shown in FIG. 1, the information processing system of this embodiment includes a management server 1 and one or more users. The management server 1 and the user terminal 2 communicate with each other via a network NW. In this embodiment, the network NW is mainly The network NW is not limited to the Internet. For example, Constructed using public telephone network, mobile phone network, wireless communication network, Ethernet (registered trademark), etc. The illustrated configuration is an example and is not limiting.

[0020] <Management Server 1> The management server 1 processes various information related to the management of AI agents operated by the business entity. The management server 1 is an information processing device that executes the Even if it is configured on-premise using a general-purpose computer such as a Alternatively, it may be logically realized by cloud computing. 1 is a block diagram illustrating an example of the hardware configuration of the management server 1. The above configuration is an example, and the management server 1 may have other configurations. At least a processor 10, a memory 11, a storage 12, a transceiver 13, and an input / output unit 14 and the like, which are electrically connected to each other via a bus 16.

[0021] The processor 10 controls the overall operation of the management server 1 and transmits and receives data between the various elements. A computing device that controls communication, executes applications, and processes information necessary for authentication processing. For example, the processor 10 is a CPU (Central Processing Unit) and / or GPU (Graphics Processing Unit) The management server 1 has the following functions (means): This is realized by executing a program stored in the memory 11 and expanded in the memory 11.

[0022] Memory 11 is DRAM (Dynamic Random Access Memory) The main memory is made up of volatile storage devices such as flash memory and HDD (Hard Disk Drive). and auxiliary storage consisting of non-volatile storage devices such as a disk drive. 11 is used as a work area for the processor 10 and is also used when the management server 1 is started. BIOS (Basic Input / Output System) that runs on It also stores various setting information, etc.

[0023] The storage 12 stores various programs such as application programs. In particular, it stores programs for executing the various functions of this system. A database storing data used for the above may be constructed in the storage 12. For example, the storage unit 120 described later is a part of the storage area of ​​the memory 11 and / or the storage 12. It is realized as:

[0024] The transmitting / receiving unit 13 is configured to transmit various information from the management server 1 to the user terminal 2 and the like via a communication network. The transmitting / receiving unit 13 is a communication interface for communicating with the information processing terminal. tooth (registered trademark) and BLE (Bluetooth Low Energy), etc. Short-range communication interface and / or USB (Universal Serial The device may further include a bus terminal and the like.

[0025] The input / output unit 14 is connected to information input devices such as a keyboard and a mouse, and an output device such as a display. The input / output unit 14 is a touch panel that has both functions of inputting and outputting information. The input device may include a printer, a speaker, etc. as an output device. stomach.

[0026] A bus 16 is commonly connected to the above elements, and transmits, for example, address signals, data signals, and Transmits a seed control signal.

[0027] <User device 2> The user terminal 2 is connected to a member of the business entity (a member is a person who is a member of the business entity regardless of his / her title or position). The user terminal 2 is an information processing terminal possessed by a person (which refers to a person who belongs to the company). For example, it may be a mobile device such as a smartphone or tablet, or a work The computer may be a general-purpose computer such as a workstation or personal computer. The terminal 2 also includes a processor 20, a memory 21, a storage 22, a transceiver 23, an input / output These are electrically connected to each other via a bus 26. Each element in the hardware configuration can be configured in the same way as the management server 1 shown in Figure 2. Therefore, detailed explanation of each element of the user terminal 2 will be omitted.

[0028] <Management Server 1 Functions (Software Configuration)> Figure 3 shows a block diagram illustrating the functions (software configuration) implemented in the information processing system. The management server 1 is realized by the processor 10 executing a program. The functions include, for example, a setting processing unit 101, a metadata adding unit 102, an access control unit, and the like. 103, an expansion candidate output unit 104, a usage application acceptance unit 105, and a counting unit 106. These functional units may be functions executed by the processor 10 of the management server 1. However, instead of the management server 1, a processor of another information processing device such as a user terminal 2 may be used. The storage unit 120 of the management server 1 may be configured to execute the The system may include various databases such as an account information storage unit 121, a user information storage unit 122, etc. good.

[0029] The agent information storage unit 121 stores the AI ​​agents introduced in each organization of the business entity. Specifically, the agent information storage unit 121 stores information about the AI ​​agent. The AI ​​agent's basic information and configuration information are linked to the identification information that uniquely identifies the agent. , information showing the operational performance of the AI ​​agent (hereinafter referred to as operational performance information) and the like are stored. It may be possible.

[0030] For example, the basic information of an AI agent includes information indicating the organization that introduced the AI ​​agent. (hereinafter referred to as "origin organization information") and is executed by the AI ​​agent. It may also include information indicating the target business (hereinafter referred to as target business information). The adopting organization referred to here is the organization that developed or first introduced the AI ​​agent within the enterprise. This refers to the organization that will be responsible for management or the base organization at the time of implementation. The target business is to introduce an AI agent and determine the tasks that the AI ​​agent will perform. The scope of work is defined as "business." The target business information includes "creating sales proposals" and "customer support." Business domain names such as "Human Resource Selection Support" and "Financial Analysis" and more specific task names The basic information may include text data that outlines the content of the task. In addition to the above, historical information such as the agent name, version information, operation start date, revision date, etc. Information, developers, administrators, technologies used (e.g., types of LLM, fine tuning) It may also include information indicating the AI ​​agent's external cloud platform. If provided by a provider, information about the provider, including the identity of the provider Information used to connect with AI agents (e.g., API endpoints, communication The agent information storage unit 121 may store basic information such as the communication method, etc.

[0031] In addition, the configuration information of the AI ​​agent includes information indicating the operational constraints of the AI ​​agent (hereinafter referred to as The operational constraints of an AI agent are as follows: The entity's policies regarding access, operation, and data usage of AI agents Specifically, operational constraint information refers to the policies, rules, and restrictions of the AI ​​agent. Data used by the agent (e.g., the basis on which the agent performs its tasks) It may also contain information indicating the security classification of the underlying knowledge base, and may be specified by the implementing organization. Even if the introduction target user range information indicating the range of users who can use the AI ​​agent is included, The range of users who can access the system can be determined by, for example, the user's position (e.g., section manager or above), the organization's It may be specified by attributes (e.g., only employees belonging to the head office), contract type (e.g., limited to full-time employees), etc. The operational constraint information includes the information specified by the introducing organization, such as the above introducing organization target user range information. It may also contain information indicating the terms of use of the AI ​​agent. In addition to the user range, the conditions for use include restrictions on the location of use and the use of AI agents. Device restrictions, time restrictions, data usage conditions (data category restrictions, data retention These conditions include period conditions, restrictions on external service integration, limitations on available functions, and operation authority levels. The agent information storage unit 121 stores the usage information specified by the introducing organization. Operational constraint information indicating conditions may be stored in association with the introducer organization information.

[0032] Other restrictions include restrictions on the time of day access is possible, and the use of AI agents. These include conditions that limit the data that can be entered into the AI ​​agent. The content of the operational constraints is not particularly limited. The configuration information of the AI ​​agent may include other information in addition to the above. stipulates the data items that can be shared among organizations among the information about AI agents. Settings, which specify the data items to be collected as operational performance, and inputs to the AI ​​agent. It may also contain templates of prompts to be entered and applied to the AI ​​agent. The settings are not necessarily limited.

[0033] The operational performance information includes, for example, the AI ​​agent's input to the user. The log information may include a record of the history of the series of interactions leading up to the client's response. Log information is acquired directly when an AI agent is embedded in an internal system. When using an AI agent on an external cloud, the data sent and received via API Information (input information to the AI ​​agent, output information from the AI ​​agent), and Including data accompanying the sending and receiving information (e.g., processing time, whether communication was successful, number of calls, etc.) In addition, the operational performance information may include the A / S by users of each organization. Statistical information showing the adoption status of I-agents, and statistical information showing the frequency of use of AI-agents , KPI improvement rate or ROI (Return on Investment = effect / cost) Information showing the effectiveness of the introduction, expressed as the ratio of The evaluation score may include, but is not necessarily limited to, at least one of the following evaluation scores that indicate the evaluation result: stomach.

[0034] Statistical information showing the implementation status includes, for example, the number of users, the total number of departments that have implemented the system, and the implementation rate ( (The ratio of users to the number of members belonging to the business entity, and the ratio of organizations that have adopted the system to the total number of organizations) Examples of statistical information showing frequency of use include, for example, the number of accesses in a predetermined period. Number of active users, average number of uses (per user, per organization), average usage time (per session) the number of transactions per specified period, the ratio of usage by business, and peak usage. The format for expressing the effects of the introduction will depend on the target business of each AI agent. For example, the change in the number of transactions before and after implementation (productivity improvement rate), the time required for business processing, Reduction rate of time (e.g. 30% reduction), reduction rate of human error (quality index), cost reduction amount or reduction rate (e.g., reduction of 2 million yen per year), sales increase and avoided opportunity loss (indirect effect), etc. Examples of information that indicates the evaluation of an AI agent include a satisfaction rating (5 levels) Evaluation, etc.), evaluation by items such as operability / response speed / accuracy, and feedback by free description (qualitative information), based on quantitative indicators such as NPS (Net Promoter Score) Other operational results include the number of troubles, usage, etc. This may include fees, operating costs, etc.

[0035] In addition to the above data, the agent information storage unit 121 also stores information about the AI ​​agent. When operating in a business entity, information to be used or accumulated is recorded in the agent information storage unit 12. The data structure of 2 is not necessarily limited.

[0036] The user information storage unit 122 stores information about users who belong to a business entity. The user information storage unit 122 associates the user with identification information (user ID) that uniquely identifies the user. The personnel information of the user is stored for each user. Information indicating the user's organization, job title, job responsibilities, employment contract, etc. It may also include information related to the contract between the business entity and the user. The information indicating the position of the user is the job type, position, job grade, job responsibilities ( The user information storage unit 122 may also include the scope of responsibility, the scope of authority, etc. Information indicating the user's usage history of the AI ​​agent may also be stored.

[0037] The setting processing unit 101 registers various setting information related to the introduction and operation of each AI agent. The setting here refers to the introduction of an AI agent into an organization, To deploy it in a state where it can be used for business tasks, it is executed by a designated developer or administrator. This will include the definition of the configuration adjustments and operational policies to be implemented.

[0038] The setting processing unit 101 outputs a setting screen to the user terminal 2 in response to a request from the user. , even if the user's setting operation for the AI ​​agent is accepted through the setting screen, The settings screen allows you to set policies, rules, and restrictions for using the AI ​​agent. An input format for accepting the specification of various setting items such as the above may be presented. In this case, the setting processing unit 101 performs the following in response to the setting operation of the user accepted via the setting screen: The scope of data to be used as the knowledge base for the AI ​​agent, the security classification of the data, The scope of users who can access the agent, the user's usage rights, the location of responsibilities, and the prompt text The process of registering setting information such as templates in the agent information storage unit 121 is executed. For example, the scope of accessible users may be determined by the department to which the user belongs within the business entity (e.g., the legal department). , HR department, etc.), job title (e.g., manager or above), contract type (e.g., full-time employee only), etc. Accordingly, whether or not the service can be used may be set on a rule basis.

[0039] Please note that AI agents may be developed using external tools or provided by external providers. In this case, the setting processing unit 101 uses a system cooperation technique such as API cooperation. The setting processing unit 101 may also use the information to acquire various setting information for the AI ​​agent. The setting history and change log may be recorded.

[0040] The metadata providing unit 102 allows predetermined information about the AI ​​agent to be shared between organizations. This executes the process of assigning metadata to the AI ​​agent as metadata that can be used. "To give" means to give predetermined information about the target AI agent to the AI ​​agent. The information is linked to the identification information of the entity and can be searched and / or referenced by each organization of the business. The metadata assignment is performed for each AI agent. It will be carried out.

[0041] Specifically, the metadata assigning unit 102 indicates the organization from which each AI agent was introduced. Information indicating the scope of use and operational constraints is assigned as metadata that can be shared between organizations. Examples of operational constraint information that can be shared between organizations include information used by AI agents. It may also include information indicating the security classification of the data being used, and may be used in accordance with the AI ​​standards defined by the implementing organization. This may include information indicating the terms of use of the agent. The scope of users who can use AI agents is determined by their position in the organization where the agent is introduced. The range of users who are introduced and the conditions related to the usage environment (usage location, terminal, time restrictions) Information indicating the terms and conditions for data use, information indicating restrictions on functionality and operation levels, etc. The metadata assigning unit 102 may assign the following information to the AI ​​agent: Information about the organization that introduced the AI ​​agent and the terms of use stipulated by that organization The data security information may be added in association with the operational constraint information indicating the above. The operation constraints indicating the service classification and the range of users targeted by the introduction source are assigned to the users by the access control unit 103 described later. It is used to identify accessible AI agents, which is performed on a per-user basis.

[0042] The metadata assigning unit 102 also assigns the AI ​​agent as metadata that can be shared between organizations. Information indicating the target tasks executed by the agent and the operational performance of the AI ​​agent Information may be assigned to each AI agent. Operational results that can be shared between organizations The information includes, for example, statistical information showing the adoption status of AI agents by users in each organization. information, statistical information showing the frequency of use of AI agents, and performance indicators expressed as KPI improvement rates or ROI. Information showing the effect of the user's input and the evaluation score showing the results of the user's evaluation of the AI ​​agent. At least one of these may be included. Metadata such as target business, operational performance, etc. This is used in the process of extracting recommended agents by the deployment candidate output unit 104, which will be described later.

[0043] The data structure of the metadata is not necessarily limited to the above example. Some of the information may be specified as data items that can be shared between organizations. In this case, the metadata providing unit 102 provides agent information recording for the target AI agent. Among the information registered in the memory unit 121, information corresponding to the definition of the data items of the metadata The extracted information may then be set as a data attribute that can be shared between organizations. The processing may be performed as follows.

[0044] Each piece of information to be used as metadata may be collected by manual input operations by the user. Alternatively, it may be collected from an external system by means of API integration, etc. Regarding metadata, the log information accumulated through the use of AI agents is stored in advance. It may be generated by analyzing it according to certain rules.

[0045] The access control unit 103 controls the AI ​​agents that the user can access based on the user's personal information. Specifically, the access control unit 103 identifies each user based on the information. Based on the operational constraints set in the metadata of the AI ​​agent, Among the AI ​​agents whose original organization is different from the organization, The AI ​​agent that can access the system is identified based on the information. indicates a user to be judged by the access control unit 103. For example, The control unit 103 receives a request from the user to present a list of AI agents, or Upon receiving a request to determine whether or not to grant access to the target, each AI The access control unit 103 determines whether or not the user can access the agent. Determine whether users have access to AI agents introduced by organizations other than their own. Not only that, but even if the AI ​​agent is introduced by the user's organization, A process for determining whether or not access is permitted may be executed according to operational constraints of the I-agent.

[0046] Access is determined based on rules that use operational constraint information contained in the metadata. For example, the access control unit 103 determines whether or not the operation constraints indicated by the metadata and the personal circumstances of the user are met. The information is compared with the user's personnel information to determine whether it complies with the operational constraints of the AI ​​agent. In addition, the access control unit 103 may determine whether the operational constraints are based on predetermined criteria. The access permission of a user of a predetermined organization may be determined based on whether or not the user satisfies the above criteria. The decision may be based on one or a combination of factors. good.

[0047] As a specific example, the access control unit 103 may Among the operational constraint information shown in the table, the security of the data used by the AI ​​agent is If the security category is equal to or greater than a predetermined threshold (for example, The information is classified as "Top Secret" and is only permitted to be disclosed to a very limited number of people, such as the development manager and management. If the data is accessed through a network, the AI ​​agent is deemed to be inaccessible and the You may exclude AI agents from the list of those accessible to the user. The service control unit 103 is configured to determine the position of the user indicated by the personnel information and the position of the user used by one AI agent. Refer to the security classification of the data used and determine the access rights to the data as defined by the user's position. If the access privileges do not meet the security classification indicated in the operational constraint information, the access is denied. The AI ​​agent is selected from the AI ​​agents that the user can access. May be excluded.

[0048] The access control unit 103 also receives operational constraint information corresponding to the introduction source organization information, particularly the introduction The information indicating the terms of use stipulated by the source organization is sent to users who belong to an organization different from the source organization. The AI ​​agent that the user can access based on the results of the comparison is then used to identify personnel information. For example, the operational constraint information may be specified based on the position, etc., of the introducing organization. The access permission may be determined by using the introduction source target user range information defined accordingly. In this case, the access control unit 103 determines whether the access control unit 103 is a The target user range information of the introduction source is diverted to the organization to which one user belongs, and the one user is For example, the AI ​​agents who are available to the customer at the level of section chief or higher in the organization may be identified. If a person in a position is set as a target user, the target user range will also be set in other organizations. By repurposing this, it is determined that users from other organizations can access the system if they are section chiefs or higher. If the operational constraints limit the organizations that can use the AI ​​agent, Access may be determined based on whether the organization to which the user belongs is one of the organizations permitted to use the service. The rules for determining whether or not access is permitted are not necessarily limited to the above examples. 103 is a system that determines the AI ​​agent usage history and violation history of operational rules. It may also be possible to determine whether or not access is possible.

[0049] In this system, access to each AI agent is determined based on the rules as described above. Once this is established, the organization's administrator may edit the access rights of each member. For example, the access control unit 103 may issue a request to an administrative user who manages a specific organization. A table of organizations showing the AI ​​agents accessible to each user in a given organization (A list showing the access permission settings for users belonging to each organization) Then, through the organization list, the access of each user to each AI agent is displayed. The administrator user can edit the access permission of each member according to the edit operation. The user's accessibility settings for each AI agent may be changed.

[0050] The expansion candidate output unit 104 outputs the expansion candidate information to the access control unit 103. Possible AI agents are presented to the user along with metadata about the AI ​​agents. Specifically, the expansion candidate output unit 104 performs a process of presenting the expansion candidate to the user in response to a request from the user. A display screen (user interface) showing a list of AI agents deployed in the business entity The list of available A services is displayed on the display screen of the list. Detailed information about the I-agent may be presented.

[0051] For example, Figure 4 shows an example of a list of AI agents displayed to the user. In the example in Figure 4, the introduction status of each AI agent, such as the target business, the organization that introduced it, and the number of users, is shown. The status, implementation effects such as KPI improvement rate, and recommended flags are displayed in a list for each agent. In addition, on the list display screen shown in Figure 4, the number of accessible AI agents is displayed. In addition to the presentation, AI agents that are determined to be inaccessible may be presented. In this case, each AI agent is displayed in a manner that allows the user to distinguish whether or not it is accessible ( For example, a flag indicating whether or not access is permitted is displayed. The access control unit 103 determines whether or not access is permitted for each user, and the access control unit 103 determines whether or not access is permitted for each user. The display mode of the list as shown in FIG. 1 is dynamically controlled by the expansion candidate output unit 104. Through the UI displayed, users can select their own AI agents from those operated by other organizations. You can find out which potential agents are available for your business.

[0052] The development candidate output unit 104 simply presents the AI ​​agents that the user can access. Instead, we select the AI ​​agent that is recommended for use by the user from among these AI agents. Specifically, the deployment candidate output unit 1 04 selects each of the AI ​​agents identified by the access control unit 103. Based on the target business and / or operational performance indicated in the metadata of each AI agent, By doing so, a recommended agent may be extracted that is recommended as a candidate for introduction to a single user. The selection of the recommended agents may be performed on a rule-based basis, in which case the selection rules are required. It is not necessarily limited.

[0053] For example, the expansion candidate output unit 104 may output a list of the jobs that a user is responsible for and the jobs that the user is responsible for. Calculate the degree of compatibility between the target task and the metadata of each AI agent. Then, a recommended agent for one user may be extracted based on the suitability for the job. The job compatibility is calculated based on a comparison table that shows the similarity between jobs. It may be calculated based on the usage history of the AI ​​agent in each task. The calculation method is not particularly limited. The job suitability is categorized as "low, medium, high" The expression format is not particularly limited. 04 is an AI agent whose job suitability is above a predetermined threshold (for example, a job suitability of "medium"). " or more) may be extracted as recommended agents.

[0054] The deployment candidate output unit 104 may also extract recommended agents according to operational performance. For example, the expansion candidate output unit 104 outputs the candidate for expansion indicated by the metadata of each AI agent. Prioritize AI agents based on KPI improvement rates or ROI included in the operational performance data. The priority is the order in which the AI ​​agents are recommended to the user, and is set by the KP The ranking is determined based on the implementation effect shown by the improvement rate or ROI. For example, priority The AI ​​agent with a rank higher than a certain level is selected as the recommended agent. The complementary output unit 104 extracts recommended agents based on the set priorities. The method of extracting agents is not limited to the above examples. For example, in addition to the above, The recommended activity is determined based on the number of users in the organization or the trend in the number of users over the most recent specified period. In addition, the number of users in the user's organization, Recommended agents are extracted based on the number of users of the same position as the user. Alternatively, we can extract AI agents with reported successful implementation cases as recommended agents. That's fine.

[0055] After extracting the recommended agents, the deployment candidate output unit 104 outputs the AI In the list of agents, the recommended agent may be displayed in an identifiable manner. For example, in Figure 4, a flag indicating a recommended agent is added. You may sort the order of the AI ​​agents so that the Alternatively, the development candidate output unit 104 may display the agent in a highlighted manner. You can filter and display only the recommended agents on the UI.

[0056] The development candidate output unit 104 displays the AI ​​agents in a list format as shown in FIG. In addition, you can also output a UI that displays the analysis results of operational performance in a dashboard format. For example, the deployment candidate output unit 104 may output the AI ​​entries by users of each organization from among the operational performance information. The heat map may be output by referring to statistical information showing the introduction status of the agent. The deployment candidate output unit 104 outputs the introduction state indicated by the metadata of each AI agent. Based on the situation, the introduction status is output as a heat map color-coded by organization. ,An example of a heat map color-coded by organization, showing the AI ​​agent's,introduction in each organization. The intensity of each AI in each organization is shown by the color shading. The deployment status of agents can be visually and intuitively grasped.

[0057] It is also possible to output a chart plotting the operational performance of the AI ​​agent on multiple axes. For example, the development candidate output unit 104 may output a list of the roles of one user for each AI agent. Business compatibility with this business, security classification, implementation status, frequency of use, implementation effects, and evaluation Two or more of the scores may be plotted on multiple axes in a chart. The evaluation score for each AI agent, the implementation status, frequency of use, and implementation effect (KPI improvement rate) An example of a radar chart based on ROI, security classification, and business suitability is shown below. Such charts allow users to intuitively identify the strengths and weaknesses of each agent. It can be compared and considered.

[0058] The method for visualizing the implementation results on the UI is not limited to the above example. 4 is a graph presented on the dashboard that shows the adoption trends of each AI agent over time. A line graph showing the series, a bar graph showing the frequency of use by user, and a distribution of evaluation scores It is also possible to output histograms and bubble charts that compare the implementation effects for each target business. The expansion candidate output unit 104 receives an input operation specifying a display condition from the user, and outputs the input Depending on the input, the display format of the graphs displayed on the dashboard is changed. You may do so.

[0059] The usage application receiving unit 105 receives a selection operation of an AI agent that the user wishes to use. Accepting the application and processing the application to start using the selected AI agent The "application for use" here refers to the application for the target AI agent selected by the user. This refers to the procedures involved in starting use.

[0060] The usage application receiving unit 105 receives the usage application via the UI output by the deployment candidate output unit 104. The selection of the target AI agent may be accepted. For example, the AI ​​agent shown in Figure 4 On the event list screen, there are operation buttons such as "Apply" in the display column of each AI agent. Then, the user can input the operation button. The system may be configured to execute a process for accepting a usage application. In the dashboard, there is an operation area for requesting use of each AI agent. In the UI output by the deployment candidate output unit 104, The operation area for attaching the image is determined by the access control unit 103 as accessible to the user. The AI ​​agent may be controlled to be active only for the selected AI agent.

[0061] The usage application receiving unit 105 receives a usage application for the selected AI agent. After that, a predetermined approval flow may be executed. For example, The system then sends an approval request for the selected AI agent's use application. The accessible AI agent determined by the access control unit 103 may be Even if the application is accepted, a process to determine whether or not the application can be used may be required before the first use. The attachment section 105 mediates the selection of a plan and the use contract when starting to use the AI ​​agent. The processing may be performed as follows.

[0062] The aggregation unit 106 executes a process for generating operational performance information of the AI ​​agent. For example, The aggregation unit 106 collects statistics and / or analyzes the usage logs of the AI ​​agents by each user. By doing so, we can obtain information on the status of adoption, frequency of use, effects of adoption, and evaluation of the AI ​​agent. This data is used to calculate various performance data such as scores. The metadata is added to each AI agent through the metadata addition process described below. .

[0063] For example, the counting unit 106 may count the number of calls made to the AI ​​agent within a predetermined period, By collecting information such as frequency of use by user, number of users who have already implemented the system, and implementation status by department, Statistical information on the frequency of use and KPI improvement rate and business performance may also be calculated. The cost-effectiveness (ROI) and other implementation effects are obtained from other systems for business management. Analyzing performance data generated and / or input by users Furthermore, the evaluation input by the user after using the AI ​​agent may be calculated as follows: The scores may be tallied and a statistical value may be calculated.

[0064] The process of generating the operational performance information may be automatically executed by the aggregation unit 106, or may be partially executed by the aggregation unit 106. Alternatively, the user may edit or correct the entire log data. For information that cannot be obtained by analysis, etc., we will receive the results of analysis by external tools. The operational performance information may be registered manually by the user. The information may be updated as appropriate in response to an instruction operation.

[0065] In addition, operational performance information is automatically re-collected at a predetermined update interval or when a predetermined event occurs. The update period may be a regular schedule such as daily, weekly, or monthly. The predetermined event may be a specific AI agent. If the number of uses of an event exceeds a predetermined threshold, if the operational rules are revised, or if new targets are added, Examples include, but are not limited to, cases where additional work is added. An event-triggered method is adopted, which triggers the re-aggregation of operational performance information when an event occurs. In the process of updating the operational performance information, the acquired log data and the external system Verify the consistency of performance data received from the supplier and re-collect it after correcting missing and / or outlier values. In this way, the operational performance information can be updated periodically or when a certain condition occurs. This ensures that the operational results given as metadata are always up-to-date and highly reliable. The accuracy of the judgment by the access control unit 103 and the presentation by the expansion candidate output unit 104 is improved. It can be improved.

[0066] In the above, the setting processing unit 101 shown as a functional unit of the management server 1, the metadata assigning unit unit 102, access control unit 103, expansion candidate output unit 104, use application acceptance unit 105, and aggregation A part or all of the functions of the unit 106 are realized by the processor 20 of the user terminal 2. It may be composed of

[0067] The UI operation reception unit 201 receives various user interfaces displayed on the display unit of the user terminal 2. (For example, the UIs shown in FIGS. 4 and 5 output by the expansion candidate output unit 104) The UI operation receiving unit 201 has a function of receiving input operations from the user via the touch panel. The user terminal 2 includes a touch panel, a mouse, a keyboard, a pointing device, etc. The operation signal is acquired through various input means, and the operation signal is transmitted via the transmitting / receiving unit 23. The process of sending the data to the management server 1 is executed.

[0068] <Example of information processing method> Next, referring to the flowchart illustrated in FIG. 6, the information processing system of this embodiment An example of an information processing method executed by the above will be described.

[0069] First, the setting processing unit 101 of the management server 1 sets up an AI agent to be applied to the organization from which the AI ​​agent is introduced. The process of registering various setting information is executed (step SQ101). It may be defined based on input operations by users such as administrators or AI agents. It may also be obtained from an external provider that provides AI agents through API integration or other means. The agent configuration process involves determining the target business of the AI ​​agent, the usage policy, operational constraints, and implementation. In addition to specifying information such as the purpose, target users are specified according to their positions in the introducing organization. User range information may be set.

[0070] Next, the metadata providing unit 102 provides predetermined information about the AI ​​agent between organizations. Executes a process to assign the data to the AI ​​agent as sharable metadata (step Specifically, for each AI agent, information indicating the organization from which it was introduced, Information indicating operational constraints of the AI ​​agent (security of data used by the AI ​​agent) Other information such as the AI ​​engine's security classification, the target user range, etc. will be added as metadata. Information indicating the target tasks performed by the AI ​​agent and the operational performance of the AI ​​agent The information to be displayed may be associated as metadata.

[0071] Next, the access control unit 103 controls the access control for each user based on the personnel information of the user. A process is performed to identify AI agents that can be used (step SQ103). In this case, the user's The user selects the AI ​​agents that are installed in a different organization from the user's own organization. The accessibility decision is made based on operational constraints. It may be rule-based, using predefined decision rules. The control unit 103 detects whether the security classification of the data used by the AI ​​agent is equal to or greater than a predetermined threshold. If the user has access rights based on their job title, the AI ​​agent If the security classification is not met, it may be determined that the user is not allowed to access the device. , the target user range set in the introducing organization (the range of users who can use the AI ​​agent) The settings that define the access range may be used by other organizations to determine whether or not a user can access the system.

[0072] Thereafter, the expansion candidate output unit 104 outputs the A that was identified as accessible in step SQ103. Extract recommended agents from the I-agents to recommend to the user. In this recommended process, the meta of each AI agent is Based on the compatibility of the target task shown in the data with the task the user is in charge of, the recommended agent Alternatively, recommendations can be made based on operational performance such as KPI improvement rate and ROI. Set a priority to indicate the order of AI agents to be recommended. The agent may be extracted.

[0073] Next, the deployment candidate output unit 104 generates a user interface for presenting accessible AI agents. The process of outputting the user interface (UI) is executed (step SQ105). The UI is a list display screen, such as that shown in Figure 4, which displays the introduction information of each AI agent, the target industry, Metadata including tasks, recommendation flags, etc. are presented in a viewable format. The power output unit 104 displays a heat map (FIG. 5(a)) that visualizes the installation status, and operational performance data in multiple formats. The operational performance can be visualized visually, for example, by plotting the performance on the evaluation axis of the In the UI output by the deployment candidate output unit 104, It may be possible to apply for new use of AI agents.

[0074] The flowchart in FIG. 6 is merely an example, and the information processing method of this embodiment The process is not limited to the example in Figure 6. Steps can be added, deleted, changed, or their order can be changed as needed. You may go.

[0075] In the information processing system of this embodiment, A By providing metadata such as operational constraint information to I-agents, This enables unified management of AI assets. and selects accessible AI agents based on the user's personnel information (affiliated organization, position, etc.). By controlling the AI ​​agent, each organization within the business can make appropriate decisions based on the AI ​​agent of other organizations. This will enable the safe and efficient deployment of the system.

[0076] In addition, the operational track record and / or business suitability of AI agents operated by other organizations By suggesting recommended agents to users based on the above, it is possible to promote AI agent sharing across organizations. This will allow for more effective promotion of the use and deployment of AI agents. Operational results such as usage status and implementation effects are displayed in visual UI such as heat maps and radar charts. By presenting it in I, it becomes easier to understand the uneven distribution of AI agent utilization within a business entity. This is expected to promote the strategic reallocation of AI resources and the expansion of their use.

[0077] The above-described embodiments are merely examples for facilitating understanding of the present disclosure and do not limit the present disclosure. This disclosure is not intended to be construed as limiting the scope of the present invention. It goes without saying that the present disclosure includes equivalents thereof.

[0078] For example, the access control unit 103 determines whether or not access is permitted based on not only the personnel information of the user but also the We will take into consideration the user's business performance status, participation history in recent projects, and other performance information. In addition, the dashboard output by the expansion candidate output unit 104 may be However, the display format is not limited to the example shown in FIG. 5, and the user can arbitrarily select the graph type (pie chart, , stacked bar graph, scatter plot, etc.) can be switched. Visualize operational results with a matrix display that allows you to compare the implementation effects of multiple organizations. In addition, when a user requests to use an AI agent, Regarding this, it does not necessarily involve an explicit "application operation" and is the first time the AI ​​agent is called. Alternatively, the approval of the application for use may be handled by the administrator. Instead of manual approval by the administrator, the system is based on predefined conditions (suitability for the target business, evaluation score, etc.). It may also be configured to automatically approve if certain conditions (e.g., operational risk) are met.

[0079] Furthermore, the series of processes performed by the information processing system described in this specification are implemented by software. , hardware, or a combination of software and hardware. A computer program for realizing each function of the management server 1 according to this embodiment may be It is also possible to create a program and install it in a PC, etc. A computer-readable recording medium having the program stored thereon may also be provided. The recording medium may be, for example, a magnetic disk, an optical disk, a magneto-optical disk, a flash memory, etc. The computer program can be installed without using a recording medium, for example, over a network. It may also be distributed via the network.

[0080] Furthermore, the effects described in this specification are merely illustrative or exemplary and are not limiting. In other words, the technology according to the present disclosure has the above-mentioned effects in addition to or instead of the above-mentioned effects. In addition, other effects that will be apparent to those skilled in the art from the description of this specification may be achieved.

[0081] The information processing system, the information processing method, and the program of the present disclosure have the following configuration: It may also be provided. [Item 1] Agent information recorder that stores information about AI agents deployed in each organization Memories and a user information storage unit that stores personnel information of each user; Information indicating the organization from which the AI ​​agent was introduced, and the operational system of the AI ​​agent The information indicating the contract is assigned to the AI ​​agent as metadata that can be shared between organizations. a metadata assigning unit for assigning the metadata to the metadata; Based on the operational constraints set in the metadata of each of the AI ​​agents, Based on this, among the AI ​​agents whose original organization is different from the organization to which a user belongs, From the information, an accessible AI agent is identified according to the personnel information of the user. and an access control unit configured to: [Item 2] The information indicating the operational constraints is used to secure the data used by the AI ​​agent. information indicating the type of The access control unit is configured to access the previous information indicated in the metadata corresponding to one AI agent. If the security classification is equal to or greater than a predetermined threshold, or if the personnel information of the user indicates The access rights to data specified by the position to be accessed are If the security classification is not met, the AI ​​agent is not accessible by the user. Item 1. The information processing system of item 1, wherein the AI ​​agent is excluded from among the possible AI agents. [Item 3] The information indicating the operational constraints is information that can be used by the AI ​​agent specified by the introducing organization. The information includes information on the range of users who will be introduced to the software. The access control unit is indicated in the metadata of each of the AI ​​agents. The introduction source target user range information is diverted to the organization to which the one user belongs, and The information processing system of claim 1, wherein the system identifies accessible AI agents. [Item 4] The access control unit is configured to allow an administrative user who manages a predetermined organization to access the predetermined organization. Presents a list of organizations showing the AI ​​agents that each user can access. ,The access permission of each user to each AI agent is ,determined through the organization list. The information described in any of items 1 to 3 that accepts editing operations by an administrative user who edits Processing system. [Item 5] The metadata providing unit provides the AI ​​agent with The source organization information indicating the source organization that introduced the software and the terms of use stipulated by the source organization and assigning the information in association with operational constraint information indicating the condition, The access control unit transmits the operational constraint information corresponding to the source organization information to the introduction unit. The personnel information of a user who belongs to an organization different from the original organization is diverted and compared, and based on the comparison results, Item 1, the information processing system according to item 1, which identifies the AI ​​agent that the user can access. Stem. [Item 6] The metadata assigning unit further assigns the metadata that can be shared between organizations to the AI Information indicating the target task to be performed by the agent, and the operation of said AI agent Item 1. The information processing system according to item 1, wherein information indicating achievements is given to the AI ​​agent. Stem. [Item 7] The AI ​​agent identified as accessible to the one user is the AI ​​agent and a development candidate output unit for presenting the development candidate to the one user together with the metadata of the event. Item 7. The information processing system according to item 6. [Item 8] The expansion candidate output unit outputs the AI ​​agent identified by the access control unit. The target task indicated in the metadata of each of the AI ​​agents is selected from the above. and / or recommending the system to the user as a candidate for introduction based on the operational performance. 8. The information processing system according to item 7, wherein the information processing system extracts a recommended agent. [Item 9] The expansion candidate output unit outputs the job responsibilities indicated in the personnel information of the one user and the job responsibilities indicated in the personnel information of the one user. The degree of suitability between the target task indicated in the metadata of each of the AI ​​agents and recommending the agent to the user based on the suitability for the job. 9. The information processing system according to item 8, wherein the information processing system extracts the information. [Item 10] The expansion candidate output unit is indicated in the metadata of each of the AI ​​agents. Prioritizing the AI ​​agents based on the KPI improvement rate or ROI included in the operational performance extracting the recommended agent for the one user by setting a ranking; Item 9. The information processing system according to item 8. [Item 11] The information showing the operational performance includes the status of the introduction of the AI ​​agent by users of each organization. Includes statistics showing The expansion candidate output unit is indicated in the metadata of each of the AI ​​agents. Based on the introduction status, the introduction status is output as a heat map color-coded by tissue. 11. The information processing system according to any one of items 7 to 10. [Item 12] The information indicating the operational constraints is used to secure the data used by the AI ​​agent. information indicating the type of The information showing the operational performance includes the status of the introduction of the AI ​​agent by users of each organization. statistical information showing the frequency of use of the AI ​​agent, KPI improvement rate or RO The information showing the introduction effect represented by I and the evaluation results of the AI ​​agent by users are shown. At least one of the following evaluation scores is included: The development candidate output unit outputs the one user's role for each of the AI ​​agents. Degree of business compatibility with this business, the security classification, the implementation status, the frequency of use, the implementation The effect and two or more of the evaluation scores are plotted on multiple axes in a chart. The information processing system according to any one of items 7 to 10. [Item 13] Storing information about the AI ​​agents deployed in each organization; storing personnel information of each user for each user; Information indicating the organization from which the AI ​​agent was introduced, and the operational system of the AI ​​agent The information indicating the contract is assigned to the AI ​​agent as metadata that can be shared between organizations. To do, Based on the operational constraints set in the metadata of each of the AI ​​agents, Based on this, among the AI ​​agents whose original organization is different from the organization to which a user belongs, From the information, an accessible AI agent is identified according to the personnel information of the user. and an information processing method executed by a computer. [Item 14] Storing information about the AI ​​agents deployed in each organization; storing personnel information of each user for each user; Information indicating the organization from which the AI ​​agent was introduced, and the operational system of the AI ​​agent The information indicating the contract is assigned to the AI ​​agent as metadata that can be shared between organizations. To do, Based on the operational constraints set in the metadata of each of the AI ​​agents, Based on this, among the AI ​​agents whose original organization is different from the organization to which a user belongs, From the information, an accessible AI agent is identified according to the personnel information of the user. and a program to make a computer execute the above. [Explanation of symbols]

[0082] 1 Management Server 121 Agent information storage unit 102 Metadata assignment unit 103 Access control section

Claims

1. an agent information storage unit that stores information about AI agents introduced in each organization; a user information storage unit that stores personnel information of each user; a metadata assigning unit that assigns information indicating an organization from which the AI ​​agent was introduced and information indicating operational constraints of the AI ​​agent, including usage conditions stipulated in the organization from which the AI ​​agent was introduced, to the AI ​​agent as metadata that can be shared between organizations; and an access control unit that identifies AI agents that can be accessed by a single user from among AI agents whose source organization is a different organization from the organization to which the single user belongs, by translating the operational constraints in the source organization into personnel information of the single user who belongs to an organization different from the source organization and comparing the operational constraints in the source organization based on the metadata of each of the AI ​​agents.

2. The information indicating the operational constraints includes information indicating a security classification of data used by the AI ​​agent, 2. The information processing system of claim 1, wherein the access control unit excludes a single AI agent from among the AI ​​agents accessible by the single user if the security classification indicated in the metadata corresponding to the single AI agent is equal to or greater than a predetermined threshold, or if the access authority to data defined by the position indicated in the personnel information of the single user does not meet the security classification indicated in the metadata.

3. The information indicating the operational constraints includes introduction source target user range information indicating the range of users who can use the AI ​​agent specified by the introduction source organization, 2. The information processing system according to claim 1, wherein the access control unit diverts the introduction source target user range information indicated in the metadata of each of the AI ​​agents to the organization to which the one user belongs, thereby identifying AI agents that the one user can access.

4. The information processing system according to any one of claims 1 to 3, wherein the access control unit presents an organizational list to an administrative user who manages a specified organization, showing the AI ​​agents that can be accessed by each user belonging to the specified organization, and accepts editing operations by the administrative user to edit the accessibility of each user to each AI agent via the organizational list.

5. 2. The information processing system according to claim 1, wherein the metadata assignment unit further assigns to the AI ​​agent, as the metadata that can be shared between organizations, information indicating a target task to be performed by the AI ​​agent and information indicating an operational performance of the AI ​​agent.

6. The information processing system according to claim 5 , further comprising an expansion candidate output unit that presents the AI ​​agent identified as accessible to the one user to the one user together with the metadata of the AI ​​agent.

7. 7. The information processing system according to claim 6, wherein the deployment candidate output unit extracts recommended agents to be recommended to the one user as candidates for introduction from among the AI ​​agents identified by the access control unit, based on the target business indicated in the metadata of each of the AI ​​agents and / or the operational performance.

8. 8. The information processing system according to claim 7, wherein the deployment candidate output unit calculates a degree of business compatibility between the work assigned to the one user indicated in the personnel information and the target work indicated in the metadata of each of the AI ​​agents, and extracts the recommended agent for the one user based on the degree of business compatibility.

9. 8. The information processing system according to claim 7, wherein the deployment candidate output unit extracts the recommended agent for the one user by setting a priority order for the AI ​​agents based on a KPI improvement rate or ROI included in the operational performance indicated in the metadata of each of the AI ​​agents.

10. The information indicating the operational performance includes statistical information indicating the adoption status of the AI ​​agent by users of each organization, The information processing system according to any one of claims 6 to 9, wherein the deployment candidate output unit outputs the introduction status as a heat map color-coded by organization based on the introduction status indicated in the metadata of each of the AI ​​agents.

11. The information indicating the operational constraints includes information indicating a security classification of data used by the AI ​​agent, The information indicating the operational performance includes at least one of statistical information indicating the introduction status of the AI ​​agent by users of each organization, statistical information indicating the frequency of use of the AI ​​agent, information indicating the introduction effect expressed by a KPI improvement rate or ROI, and an evaluation score indicating the evaluation result of the AI ​​agent by users; The information processing system according to any one of claims 6 to 9, wherein the deployment candidate output unit outputs a chart in which two or more of the suitability of each of the AI ​​agents for the user's work, the security classification, the implementation status, the frequency of use, the implementation effect, and the evaluation score are plotted on multiple axes.

12. storing information about AI agents deployed in each organization; storing personnel information of each user for each user; Assigning information indicating the organization from which the AI ​​agent was introduced and information indicating operational constraints of the AI ​​agent, including terms of use specified in the organization from which the AI ​​agent was introduced, to the AI ​​agent as metadata that can be shared between organizations; and identifying an AI agent accessible to a user from among AI agents whose source organization is a different organization from the organization to which the user belongs by translating the operational constraints in the source organization into personnel information of the user who belongs to an organization different from the source organization based on the metadata of each of the AI ​​agents.

13. storing information about AI agents deployed in each organization; storing personnel information of each user for each user; Assigning information indicating the organization from which the AI ​​agent was introduced and information indicating operational constraints of the AI ​​agent, including terms of use specified in the organization from which the AI ​​agent was introduced, to the AI ​​agent as metadata that can be shared between organizations; A program for causing a computer to execute the following steps: based on the metadata of each of the AI ​​agents, the operational constraints in the source organization are applied to personnel information of a user who belongs to an organization different from the source organization, and then the operational constraints are compared with the personnel information of the user who belongs to an organization different from the source organization, thereby identifying an AI agent that can be accessed by the user from among AI agents whose source organization is an organization different from the organization to which the user belongs.

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