AI-based leadership scene simulation partner training intelligent system

Abstract

The invention belongs to the technical field of intelligent AI, and discloses an AI-based leadership scene simulation partner training intelligent system, which simulates a real leadership scene through the AI technology, helps a user to carry out leadership training in a virtual environment, and comprises a drilling scene setting module, a scene simulation module and an evaluation feedback module. Through a highly-simulated virtual scene and dynamic interaction, the effectiveness of leadership training is remarkably improved, meanwhile, the behavior and response of a real subordinate are simulated through an AI training partner, the dialogue strategy is dynamically adjusted in combination with emotion calculation and trust value management, immersive training experience is provided for a user, and the training efficiency is improved. The method comprises the following steps of: obtaining a multi-dimensional scoring system, immediately reminding and providing verbal skill guidance to help a user to adjust a communication strategy through an AI coach when the user speaks and deviates from a target, and finally quantitatively evaluating the performance of the user through an AI scorer based on the multi-dimensional scoring system, and generating a visual report to meet the requirement of large-scale training of an enterprise.

Description

Technical Field

[0001] The present invention belongs to the technical field of intelligent AI, and specifically relates to an intelligent system for leadership scenario simulation and coaching based on AI. Background Art

[0002] In recent years, the rapid development of artificial intelligence technology has provided new possibilities for leadership training. The maturity of natural language processing (NLP) technology, especially the application of large language models such as GPT-4 and BERT, enables AI to generate high-quality, context-appropriate conversations, simulating real work scenarios and interpersonal interactions. At the same time, the current business environment is full of complexity and uncertainty. Factors such as globalization, technological progress, market fluctuations, and emergencies have made the challenges faced by enterprises increasingly diverse. In this environment, enterprises need managers with strong leadership skills who can quickly adapt to changes, make effective decisions, and lead teams to cope with uncertainties. Therefore, leadership training has become one of the core needs of enterprise development.

[0003] However, when conducting leadership training at present, although training in the form of classroom lectures and case analyses can impart theoretical knowledge, it is difficult to reproduce the complex situations in real work. Trainees cannot experience and adjust their leadership behaviors in practice. In addition, the feedback of traditional training usually relies on the subjective evaluation of coaches or colleagues, lacking real-time and objectivity, and is costly, making it difficult to cover a large number of employees, especially large enterprises across regions. Therefore, an intelligent system for leadership scenario simulation and coaching based on AI is needed to evaluate the leadership level of managers in a data-driven manner and formulate improvement plans to help enterprises quickly cultivate leaders who can adapt to future challenges. Summary of the Invention

[0004] The purpose of the present invention is to provide an intelligent system for leadership scenario simulation and coaching based on AI to solve the problems raised in the above background art.

[0005] To achieve the above purpose, the present invention provides the following technical solution: An intelligent system for leadership scenario simulation and coaching based on AI, which simulates real leadership scenarios through AI technology to help users conduct leadership training in a virtual environment, and the system includes a drill scenario setting module, a scenario simulation module, and an evaluation and feedback module;

[0006] The drill scenario setting module includes a personalized customization unit and a database. The scenario simulation module is implemented based on an AI coach, and the evaluation and feedback module is implemented based on an AI coach and an AI scorer.

[0007] Preferably, the personalized customization unit can set the simulated company background, the role to play, and the task objectives, and the background information, role information, and task objective information are all stored in the database uniformly.

[0008] Preferably, the AI sparring partner has functions of answering questions and reporting, topic inheritance, emotional transmission management, intelligent confrontation, and trust value management;

[0009] Among them, the function of answering questions and reporting can report the work situation according to the user's questions, and make explanations and defenses. The topic inheritance function can ensure the coherence of the conversation and associate with the user's questions when responding. The emotional transmission management function can prevent emotions from overly affecting communication and defend against the gradual attenuation of emotions in continuous conversations. The intelligent confrontation function can trigger technical, strategic, and systematic confrontations according to the user's answers. The trust value management function can dynamically adjust the trust value of the AI sparring partner according to the user's performance, affecting the intensity of the conversation.

[0010] Preferably, when the user answers with a poor attitude, repeats the same specific question without factual basis, a technical confrontation is triggered. When triggering this confrontation, the response of the AI sparring partner is defensive and justifying, with relatively intense words, aiming to question the reasonableness of the user's view and require the user to provide more evidence and specific details;

[0011] When the user asks a question but does not analyze the reasons in depth, ignores resources and external factors, simply attributes the problem to personal and team capabilities, and also puts forward unrealistic improvement requirements, a strategic confrontation is triggered. When triggering this confrontation, the AI sparring partner will question the reasonableness of the current strategy, aiming to guide the user to focus on the root cause of the problem rather than the surface phenomenon;

[0012] When the user shows doubts about the overall working mode but does not put forward a specific improvement direction, a systematic confrontation is triggered. When triggering this confrontation, the AI sparring partner will question the working mode of the entire department system, aiming to guide the user to think about the problem from a higher level rather than being limited to local adjustments.

[0013] Preferably, after each confrontation is triggered by the trust value management function, the AI sparring partner will adjust the trust value according to the user's performance. When the trust value is lower than 30%, the words of the AI sparring partner will become more intense. When the trust value is zero, the task goal fails and the simulation ends.

[0014] Preferably, the AI coach provides real-time feedback to the user, and when the user's speech deviates from the communication goal, the AI coach will give a reminder of getting off-topic and speech guidance. The conditions for deviating from the communication goal include excessive focus on personal issues, excessive criticism and blame, providing irrelevant suggestions and solutions, ignoring listening and jumping to conclusions prematurely, excessive focus on the past rather than the future, deviating from the communication goal and discussing irrelevant topics, and the speech content being unclear.

[0015] Preferably, the AI rater scores according to the user's speech content and gives suggestions on areas where the user needs improvement based on the scoring results.

[0016] Preferably, the scenario simulation module includes an individual leadership simulation unit, a business leadership simulation unit, and a team leadership simulation unit;

[0017] The team leadership simulation unit includes team cooperation training, team member improvement training, communication skills training, task assignment training, team member motivation training, meeting management training, and task execution training; the business leadership simulation unit includes goal management training, customer orientation training, decision-making training, project management training, business innovation training, business risk assessment training, and performance orientation training; the individual leadership simulation unit includes self-awareness training, thinking mode training, presentation skills training, time management training, stress management training, writing skills training, and learning ability training.

[0018] Preferably, the AI practice partner, AI coach, and AI rater adopt the React / Vue + WebSocket framework and use Hugging Face Transformers and Apache Flink to process the emotions in the conversation flow.

[0019] The beneficial effects of the present invention are as follows:

[0020] Through highly realistic virtual scenarios and dynamic interactions, the present invention significantly improves the effectiveness of leadership training. At the same time, the AI practice partner simulates the behaviors and reactions of real subordinates, combines emotion computing and trust value management, dynamically adjusts the conversation strategy, and provides an immersive training experience for users. Then, through the AI coach, when the user's speech deviates from the goal, it immediately reminds and provides speech guidance to help the user adjust the communication strategy. Finally, through the AI rater, based on a multi-dimensional scoring system, the user's performance is quantitatively evaluated and a visual report is generated. This not only helps users better understand and apply leadership theories, but also quickly improves communication, decision-making, and problem-solving abilities in practice, and can continuously enhance leadership, meeting the needs of large-scale enterprise training. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] Figure 1 It is a framework diagram of the simulation practice intelligent system of the present invention. DETAILED DESCRIPTION OF THE INVENTION

[0022] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0023] As Figure 1 shown, the embodiment of the present invention provides an AI-based leadership scenario simulation and coaching intelligent system. This system simulates real leadership scenarios through AI technology to help users conduct leadership training in a virtual environment. The system includes a rehearsal scenario setting module, a scenario simulation module, and an evaluation and feedback module.

[0024] The rehearsal scenario setting module includes a personalized customization unit and a database. The scenario simulation module is implemented based on an AI coach, and the evaluation and feedback module is implemented based on an AI coach and an AI scorer.

[0025] Through highly realistic virtual scenarios and dynamic interactions, the effectiveness of leadership training is significantly improved. At the same time, an AI coach is used to simulate the behaviors and reactions of real subordinates. Combining emotional computing and trust value management, the dialogue strategy is dynamically adjusted to provide users with an immersive training experience. Then, through the AI coach, when the user's speech deviates from the target, it immediately reminds and provides speech guidance to help the user adjust the communication strategy. Finally, through the AI scorer, based on a multi-dimensional scoring system, the user's performance is quantitatively evaluated and a visual report is generated. This not only helps users better understand and apply leadership theories, but also can quickly improve communication, decision-making, and problem-solving abilities in practice, and can also achieve continuous improvement of leadership, meeting the needs of large-scale enterprise training.

[0026] Among them, the personalized customization unit can set the simulated company background, the role played, and the task objectives. The background information, role information, and task objective information are all stored in the database uniformly.

[0027] For example, the company background: The enterprise training department of Company S undertook a series of training projects last quarter. After the training projects ended, the feedback effect was not good. After the department analyzed the responsible persons in detail, it was found that employee Li did not achieve the training project performance.

[0028] The user plays the role of Director Wang: The person in charge of the enterprise training department of Company S, responsible for overall training planning, demand analysis, curriculum system construction, resource management, project management, and effect evaluation, etc.

[0029] The AI co-trainer acts as the subordinate Li: a key business figure in enterprise training, with consistently excellent performance, but the performance of multiple consecutive training projects has recently fallen short of the mark; he has a sensitive personality and a strong sense of self-esteem, and has developed a defensive mentality in the face of pressure and declining performance.

[0030] Task objective: Conduct a performance communication simulation training to understand the reasons for the decline in the subordinate's performance, provide improvement suggestions, and enhance one's own performance communication ability.

[0031] Among them, the AI co-trainer has functions of responding to questions and reporting, topic inheritance, emotional transmission management, intelligent confrontation, and trust value management;

[0032] Among them, the function of responding to questions and reporting can report work situations according to user questions, and provide explanations and justifications. The topic inheritance function can ensure the coherence of the conversation and associate with the user's questions when responding. The emotional transmission management function can prevent emotions from overly affecting communication, and at the same time prevent emotions from gradually decaying in continuous conversations. The intelligent confrontation function can trigger technical, strategic, and systematic confrontations according to the user's answers. The trust value management function can dynamically adjust the trust value of the AI co-trainer according to the user's performance, affecting the intensity of the conversation.

[0033] Among them, when the user's answer is in a bad attitude, and the same specific question is repeatedly mentioned and the question lacks factual basis, a technical confrontation is triggered. When this confrontation is triggered, the response of the AI co-trainer is defensive and justifying, and the words are relatively intense. The purpose is to question the reasonableness of the user's view and require the user to provide more evidence and specific details;

[0034] For example, when the director's attitude is bad, or when "the quality of the course content is not good" and other similar situations are repeatedly mentioned, an adversarial response is entered, and the words should be intense, defensive and justifying. For example: If the director points out the problem of the course content quality, the response can question "Do you have extensive and reliable customer feedback information to support the problem of the course content quality you mentioned?"

[0035] When the user asks a question but does not analyze the reasons in depth, ignores resources or external factors, simply attributes the problem to personal and team capabilities, and also puts forward unrealistic improvement requirements, a strategic confrontation is triggered. When this confrontation is triggered, the AI co-trainer will question the reasonableness of the current strategy. The purpose is to guide the user to focus on the root cause of the problem, rather than the surface phenomenon;

[0036] In the scenario involving strategic confrontation, for example, when the user mentions that the performance is not ideal and suddenly proposes to re-evaluate the priority of performance indicators, it can be answered "I think the current priority of performance indicators is unreasonable. We should first properly solve the resource problem and then discuss performance improvement, otherwise the work simply cannot be carried out smoothly."

[0037] When the user shows doubts about the overall working mode but does not propose a specific improvement direction, a systematic confrontation is triggered. When triggering this confrontation, the AI co-trainer will question the working mode of the entire department or system, aiming to guide the user to think about problems from a higher level rather than being limited to local adjustments.

[0038] When the user mentions the unsatisfactory performance multiple times, corresponding systematic confrontations are carried out. For example: raising doubts about the working mode of the entire department and demanding a comprehensive reform, such as "The current working mode of the department has completely failed to adapt to the rapid changes in the market. It is necessary to re-plan the department structure and work processes, otherwise the performance problem will never be effectively solved."

[0039] Among them, in the trust value management function, after each confrontation is triggered, the AI co-trainer will adjust the trust value according to the user's performance. When the trust value is lower than 30%, the words used by the AI co-trainer will become more intense. When the trust value is zero, the task goal fails and the simulation ends.

[0040] Among them, the AI coach provides real-time feedback to the user, and when the user's speech deviates from the communication goal, the AI coach will give a reminder of getting off-topic and speech guidance. The conditions for deviating from the communication goal include excessive focus on personal issues, excessive criticism and blame, providing irrelevant suggestions and solutions, ignoring listening and jumping to conclusions prematurely, excessive focus on the past rather than the future, deviating from the communication goal and discussing irrelevant topics, and the speech content being unclear.

[0041] Excessive focus on personal issues: The off-topic performance is asking too many questions about private life. The correct approach is to appropriately care about emotions and focus on work performance. Excessive criticism or blame: The off-topic performance is focusing on criticizing mistakes. The correct approach is to ask questions to guide reflection and find solutions together. Providing irrelevant suggestions or solutions: The off-topic performance is that the suggestions are irrelevant or vague to the actual problem. The correct approach is to provide feasible suggestions according to the specific situation. Ignoring listening and jumping to conclusions prematurely: The off-topic performance is jumping to conclusions prematurely and not giving the other person a chance to express. The correct approach is to use open-ended questions to guide expression, listen and then analyze and summarize. Excessive focus on the past rather than the future: The off-topic performance is discussing past mistakes too much. The correct approach is to appropriately mention past performance and focus on improvement and setting future goals. Deviating from the communication goal and discussing irrelevant topics: The off-topic performance is discussing topics irrelevant to performance. The correct approach is to always focus on the communication goal and avoid introducing irrelevant topics. The speech content is unclear: The off-topic performance is that the text is unclear and cannot form or show the meaning. The correct approach is to always focus on the communication goal and avoid introducing irrelevant topics.

[0042] Among them, the AI scorer scores according to the user's speech content and gives suggestions for improvement based on the scoring situation.

[0043] The evaluation and analysis criteria are as follows:

[0044] Excellent (8 - 10 points): The opening is natural and amiable, quickly eliminating employees' nervousness and establishing a good environment for trust-based communication; Good (6 - 7 points): The opening is relaxed and friendly, relieving employees' nervousness and basically smoothly initiating communication; Average (4 - 5 points): The opening is normal, but the atmosphere creation is average and employees still have a sense of nervousness; Poor (1 - 3 points): The opening is rigid, increasing employees' nervousness and seriously affecting the communication atmosphere; Excellent (8 - 10 points): Effectively guiding employees to report, listening attentively and delving deeply into questions to fully understand the problems; Good (6 - 7 points): Relatively successfully guiding the report, being focused most of the time and able to delve into the main questions; Average (4 - 5 points): The effect of guiding and listening is average and the follow-up questions are not in-depth; Poor (1 - 3 points): Poor at guiding the report, often interrupting employees and rarely following up on key information; Excellent (8 - 10 points): Skilled at guiding employees to analyze the root causes of problems, identifying at least 5 key factors and accurately distinguishing between internal and external causes; Good (6 - 7 points): Guiding the analysis of problems, finding 3 - 4 key factors and relatively accurately distinguishing between internal and external causes; Average (4 - 5 points): The ability to dig out key factors is average and there are deviations in distinguishing between internal and external causes; Poor (1 - 3 points): Difficult to guide the analysis of problems, unable to find or only finding 1 key factor and unable to distinguish between internal and external causes; Excellent (8 - 10 points): Providing positive feedback in a timely and sufficient manner, eliminating employees' defensive psychology and stimulating their motivation to solve problems; Good (6 - 7 points): The positive feedback is effective, reducing employees' defensiveness and stimulating a certain degree of enthusiasm; Average (4 - 5 points): The feedback effect is average and has no obvious effect on stimulating employees' motivation; Poor (1 - 3 points): Insufficient positive feedback, employees have a serious defensive psychology and lack the willingness to solve problems; Excellent (8 - 10 points): The plan formulated with employees is perfect and operable, fully considering the actual situation and the responsibilities of employees are clear; Good (6 - 7 points): The plan is relatively systematic and operable, but there are deficiencies in details and the responsibilities of employees are relatively clear; Average (4 - 5 points): The plan is simple, lacks systematicness, is poorly operable and the responsibilities of employees are not clear; Poor (1 - 3 points): No effective plan is formulated, lacking key elements and not considering the actual situation; Excellent (8 - 10 points): Clearly summarizing at the end of the communication, both parties are clear about the improvement direction and the follow-up is timely and effective; Good (6 - 7 points): The summary is relatively clear, both parties basically know the improvement direction and the follow-up is relatively timely; Average (4 - 5 points): The summary is vague, both parties have an unclear understanding of the improvement direction and the follow-up is delayed; Poor (1 - 3 points): The summary is chaotic, both parties do not know the improvement direction and rarely follow up.

[0045] The improvement suggestions are as follows:

[0046] Short term (1 - 2 weeks): Master 3 easy ways to start a conversation, such as talking about hot topics or sharing small interesting stories; practice caring words for daily communication and observe employees' reactions; Medium term (1 - 2 months): Understand employees' characteristics and choose appropriate opening and caring words; collect feedback for optimization and strive to relieve employees' tension within 5 minutes; Long term (3 - 6 months): Develop a unique style, eliminate employees' tension within 1 - 2 minutes, and establish a communication environment of deep trust; Short term (1 - 2 weeks): Make a reporting outline, learn listening skills and practice; guide according to the outline during communication and pursue key information; Medium term (1 - 2 months): Flexibly guide employees to express, summarize listening and pursuing questions every week; sort out cases to improve the depth of pursuit; Long term (3 - 6 months): Naturally guide the report, keenly capture information, deeply pursue to form an analysis report; Short term (1 - 2 weeks): Learn problem - analysis methods and analyze cases; guide employees to distinguish between internal and external causes during communication; Medium term (1 - 2 months): Use various skills to find key factors, distinguish between internal and external causes and put forward ideas; review cases to summarize skills; Long term (3 - 6 months): Accurately guide the analysis of problems, clarify key factors, formulate effective solutions and share experiences; Short term (1 - 2 weeks): Learn positive - feedback words and collect cases; give more positive feedback during communication and observe employees' emotions; Medium term (1 - 2 months): Provide flexible feedback according to employees' situations, share cases to stimulate enthusiasm and guide employees to put forward improvement ideas; Long term (3 - 6 months): Form an incentive style, eliminate employees' defensiveness, stimulate internal motivation and develop good habits; Short term (1 - 2 weeks): Learn the method of making plans and make a simple performance - improvement plan with employees; Medium term (1 - 2 months): Skilledly use the method to make a detailed plan and check and adjust it every week; Long term (3 - 6 months): Form a perfect plan system, ensure implementation and promote experience; Short term (1 - 2 weeks): Learn the summary method and make a follow - up plan; summarize key points after communication and inform employees; Medium term (1 - 2 months): Accurately summarize to form a written record, strictly follow up and summarize and analyze monthly; Long term (3 - 6 months): Form an efficient mechanism, quickly summarize key points, continuously follow up to solve problems and promote work improvement.

[0047] Among them, the scenario - simulation module includes an individual - leadership simulation unit, a business - leadership simulation unit and a team - leadership simulation unit;

[0048] The team - leadership simulation unit includes team - cooperation training, team - member improvement training, communication - ability training, task - assignment training, team - member motivation training, meeting - management training and task - execution training; The business - leadership simulation unit includes goal - management training, customer - orientation training, decision - making - ability training, project - management training, business - innovation training, business - risk - assessment training and performance - orientation training; The individual - leadership simulation unit includes self - awareness training, thinking - mode training, speech - ability training, time - management training, stress - management training, writing - ability training and learning - ability training.

[0049] Among them, the AI sparring partner, AI coach, and AI grader adopt the React / Vue + WebSocket framework and use Hugging Face Transformers and Apache Flink to process the emotions in the conversation flow.

[0050] It should be noted that in this article, relational terms such as first and second are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the term "comprising", "including" or any other variation thereof is intended to cover non-exclusive inclusion, so that a process, method, article or device comprising a series of elements not only includes those elements, but also includes other elements not expressly listed, or also includes elements inherent to such process, method, article or device.

[0051] Although the embodiments of the present invention have been shown and described, those of ordinary skill in the art can understand that various changes, modifications, substitutions and variations can be made to these embodiments without departing from the principle and spirit of the present invention. The scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. An AI-based intelligent system for leadership scenario simulation and coaching, characterized in that: The system simulates real leadership scenarios through AI technology to help users conduct leadership training in a virtual environment. The system includes a drill scenario setting module, a scenario simulation module, and an evaluation and feedback module; The drill scenario setting module includes a personalized customization unit and a database. The scenario simulation module is implemented based on an AI co-trainer, and the evaluation and feedback module is implemented based on an AI coach and an AI scorer.

2. The AI-based leadership scenario simulation coaching intelligent system according to claim 1, wherein: The personalized customization unit can set the simulated company background, the persona to play, and the task objectives. The background information, persona information, and task objective information are all stored in the database uniformly.

3. The AI-based leadership scenario simulation coaching intelligent system according to claim 1, wherein: The AI co-trainer has functions of responding to questions and reporting, topic inheritance, emotional transfer management, intelligent confrontation, and trust value management; Among them, the function of responding to questions and reporting can report work situations according to users' questions, and give explanations and defenses. The topic inheritance function can ensure the coherence of the conversation and associate with users' questions when responding. The emotional transfer management function can prevent emotions from overly affecting communication and defend against the gradual attenuation of emotions in continuous conversations. The intelligent confrontation function can trigger technical, strategic, and systematic confrontations according to users' answers. The trust value management function can dynamically adjust the trust value of the AI co-trainer according to users' performances, affecting the intensity of the conversation.

4. The AI-based leadership scenario simulation coaching intelligent system according to claim 3, wherein: When the user's answer is in a bad attitude, repeats the same specific question without factual basis, a technical confrontation is triggered. When this confrontation is triggered, the response of the AI co-trainer is defensive and justifying, and the words used are relatively intense, aiming to question the reasonableness of the user's view and require the user to provide more evidence and specific details; When the user asks a question but does not analyze the reasons in depth, ignores resources and external factors, simply attributes the problem to personal and team capabilities, and also puts forward unrealistic improvement requirements, a strategic confrontation is triggered. When this confrontation is triggered, the AI co-trainer will question the reasonableness of the current strategy, aiming to guide the user to focus on the root cause of the problem rather than the surface phenomenon; When the user shows doubts about the overall work mode but does not put forward a specific improvement direction, a systematic confrontation is triggered. When this confrontation is triggered, the AI co-trainer will question the work mode of the entire department system, aiming to guide the user to think about the problem from a higher level rather than being limited to local adjustments.

5. The AI-based leadership scenario simulation coaching intelligent system according to claim 3, wherein: In the trust value management function, after each confrontation is triggered, the AI co-trainer will adjust the trust value according to the user's performance. When the trust value is lower than 30%, the words used by the AI co-trainer will become more intense. When the trust value is zero, the task objective fails and the simulation ends.

6. The AI-based leadership scenario simulation coaching intelligent system according to claim 1, wherein: The AI coach provides real-time feedback to the user. When the user's speech deviates from the communication goal, the AI coach will give a reminder of going off-topic and speech guidance. The conditions for deviating from the communication goal include over-focusing on personal issues, over-criticizing and accusing, providing irrelevant suggestions and solutions, ignoring listening and jumping to conclusions prematurely, over-focusing on the past rather than the future, deviating from the communication goal and discussing irrelevant topics, and the speech content being unclear.

7. The AI-based leadership scenario simulation coaching intelligent system according to claim 1, characterized in that: The AI scorer scores according to the user's speech content and gives suggestions for improvement based on the scoring situation.

8. The AI-based leadership scenario simulation coaching intelligent system according to claim 1, wherein: The scenario simulation module includes an individual leadership simulation unit, a business leadership simulation unit, and a team leadership simulation unit; The team leadership simulation unit includes team cooperation training, team member improvement training, communication ability training, task assignment training, team member motivation training, meeting management training, and task execution training; the business leadership simulation unit includes goal management training, customer orientation training, decision-making ability training, project management training, business innovation training, business risk assessment training, and performance orientation training; the individual leadership simulation unit includes self-awareness training, thinking mode training, speech ability training, time management training, stress management training, writing ability training, and learning ability training.

9. The AI-based leadership scenario simulation and practice intelligent system according to claim 1, characterized in that: The AI sparring partner, AI coach, and AI grader adopt the React / Vue + WebSocket framework and use Hugging Face Transformers and Apache Flink to process the emotions in the conversation flow.

Images