College entrance examination volunteer filling business analysis report from the perspective of AI technology

At the critical juncture of volunteering for the college entrance examination, AI technology is quietly reshaping the traditional model. This paper deeply analyzes the application prospects of AI in the field of college entrance examination volunteer filling, and discusses its market opportunities and challenges in the context of policy, economy, population, technology and culture.

Market Analysis

Political policy

At present, China’s college entrance examination volunteer application market is affected by multiple policy factors. First of allNew college entrance examination reformIt is the core driving force for promoting the reform of the volunteer filling mode. Twenty-nine provinces across the country have completed the implementation of the new college entrance examination and implemented the model of “college professional group” or “professional (class) + college”, which has significantly increased the complexity of volunteer application and put forward higher professional and strategic requirements for candidates and parents. The large differences in policies between provinces have further exacerbated the problem of information asymmetry and spawned a huge demand for professional volunteer filling services.

Secondly, the government volunteers for the college entrance examination to fill in the marketStricter supervision。 With the rapid growth of the market size, chaos has also emerged, such as some institutions using false propaganda such as “slipping and withdrawing” to create anxiety, exaggerated publicity, and abnormally high fees. Official media such as People’s Daily and Xinhua News Agency have repeatedly issued articles warning of the service trap of “volunteering for the college entrance examination”, emphasizing that “don’t believe in ‘spending money to buy peace of mind’ when filling in volunteer reports”. This shows that the government is paying close attention and may introduce stricter normative policies to protect the rights and interests of candidates and their families and promote the healthy development of the industry. For AI volunteer filling services, this means that while providing efficient and personalized services, it is necessary to attach great importance to compliance, data security, and information transparency, and avoid algorithmic bias and misleading information.

In addition, the state is rightEducational equity and talent developmentIt also provides policy support for the application of AI technology in the field of college entrance examination volunteer application. Through AI technology, it is expected to break down geographical and information barriers, allowing students in more underdeveloped areas to receive high-quality volunteer application guidance, thereby promoting the balanced distribution of educational resources. At the same time, the country is rightVocational education and integration of industry and educationIt is also required that the volunteer application service can better guide students to choose majors that meet the national strategic needs and industrial development direction, and realize the accurate connection between talent training and social needs.

economic development

The sustainable development of China’s economy, especially the transformation from rapid growth to high-quality development, has had a profound impact on the education and job market, and has also provided new opportunities and challenges for the AI college entrance examination volunteer application business.

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First of allIndustrial structure upgrading and conversion of old and new kinetic energy。 As China’s economy transitions from traditional manufacturing to high-tech, service, and strategic emerging industries, the demand for talent has also changed. For example, the demand for compound and innovative talents in fields such as artificial intelligence, big data, cloud computing, biomedicine, and new energy is increasing, while some positions in traditional industries are facing elimination or transformation. This change makes students not only consider the current employment enthusiasm when choosing a major, but also have a forward-looking attitude and predict the future industrial development trend. The AI volunteer filling system can identify the talent needs of emerging industries through big data analysis, and recommend majors and colleges with more development potential based on students’ interests and abilities, helping students avoid the dilemma of “unemployment after graduation”.

secondlyCompetition in the job market has intensified and employment concepts have changed。 Under the dual effects of downward economic pressure and the continuous growth of the number of college graduates, the competition in the job market is becoming increasingly fierce. At the same time, the employment concept of the younger generation is also changing, they no longer only pursue an “iron rice bowl”, but pay more attention to career development, personal value realization and work-life balance. This makes the college entrance examination volunteer application no longer a simple score matching, but needs to comprehensively consider personal development path, career planning and even life value choices. AI systems can help students understand themselves more clearly and make choices that are more in line with long-term development by simulating career development paths, analyzing industry prospects, and providing personalized career assessments.

againEducation investment and human capital improvement.The development of China’s economy has brought about an increase in the level of residential income, and the willingness and ability of families to invest in education have also increased. Parents are more willing to provide their children with high-quality educational resources and professional guidance for further education, in order to stand out in the fierce competition. This increase in willingness to pay for educational services provides a market foundation for the commercialization of AI volunteer filling services. At the same time, economic development has also promoted the reform of the education system, and vocational education has received unprecedented attention, aiming to cultivate more technical and skilled talents to meet the needs of economic development. The AI volunteer filling system can better integrate the information of general education and vocational education, provide students with diversified options for further education, and help the overall improvement of national human capital.

At lastThe uneven regional economic development also affects education and employment。 The industrial structure and economic development level of different regions are different, resulting in an uneven distribution of talent demand and employment opportunities. The AI volunteer filling system can provide students with cross-regional further education and employment suggestions by analyzing regional economic data and talent flow trends, promoting the rational flow of talents and the coordinated development of the regional economy. All in all, the transformation and upgrading of China’s economy and high-quality development have put forward higher requirements for talent training, and also provide a broad space and internal driving force for the innovative application of AI technology in the field of college entrance examination volunteer filling.

Population development

The changes in the structure of the Chinese population, especially the increasingly severe trend of population aging and declining birthrate, have had a profound impact on the education system, the labor market, and even the entire social and economic development, and have also brought unique opportunities and challenges to the AI college entrance examination volunteer filling business.

First of allChanges in the relationship between supply and demand in education.The aging population and declining birthrate will directly lead to a decrease in the school-age enrollment population, and the relationship between education supply and demand will undergo fundamental changes in the future.

This has made the competition for students among colleges and universities more intense, and also prompted colleges and universities to pay more attention to the rationality of professional settings and employment prospects. For the college entrance examination volunteer filling service, this means that it is necessary to more accurately analyze the enrollment strategies and professional characteristics of each university, help students find the most suitable school and major for themselves in the limited number of students, and also pay attention to the major adjustments and reforms carried out by colleges and universities to attract students.

secondlyThe structural contradictions in the labor market have intensified.The aging population has led to a decline in the proportion of the working-age population, a decrease in labor supply, and an increase in labor costs. At the same time, with the transformation and upgrading of the economy, the demand for high-skilled and compound talents is increasing, while the traditional labor force is facing transformation pressure. This structural contradiction makes the job market put forward higher requirements for the quality and matching of talents. The AI volunteer filling system can guide students to choose majors that are still competitive under demographic changes, such as fields related to elderly care services, health care, and smart technology, by predicting future labor market trends, thereby alleviating the structural imbalance in the labor market.

againStructural adjustment of social security and education spending。 As the elderly population increases, the proportion of social security and employment expenditure in the national budget may continue to rise, even exceeding that of education expenditure. This means that educational resources may be under pressure to be reallocated. In this context, it is particularly important to improve the efficiency and accuracy of educational investment. AI volunteer filling service can help students choose a more cost-effective education path by optimizing resource allocation, and avoid the waste of resources caused by blindly pursuing hot majors. In addition, the burden of family pension has increased and the concept of education has evolved. Under the “4-2-1” or even “4-2-2” family structure, the younger generation faces a heavy burden of old-age care. This may prompt parents to be more rational in investing in their children’s education and pay more attention to the return on investment of education, that is, whether the major they study can bring stable high income and good career development. The AI volunteer filling system can help families make more informed education investment decisions by providing long-term development forecasts and pension security analysis for different occupations.

At lastThe rise of education for the elderly.Although it is not directly related to the college entrance examination volunteer application, the aging population has also given rise to the demand for education for the elderly. This reflects the popularization of the concept of lifelong learning and the diversification of the education system. AI technology can also play a role in the field of elderly education in the future, such as providing personalized learning content recommendations, health management, etc., which may have a certain synergistic effect with the college entrance examination volunteer filling service at the technical and data levels.

All in all, the aging population and declining birthrate have brought severe challenges to China’s social and economic development, but they have also prompted profound changes in the education and job markets. AI college entrance examination volunteer filling services should actively respond to these changes, helping students and families make the best choices in the complex demographic changes through accurate predictions, personalized recommendations, and full life cycle planning.

Technological development

At present, a new round of scientific and technological revolution and industrial transformation represented by artificial intelligence (AI) and big data is profoundly affecting global economic and social development, and has brought unprecedented impacts and opportunities to China’s industrialization process, education system, and job market.

First of allIntelligent upgrading of industrialization process。 China is moving from traditional industrialization to new industrialization, and intelligent manufacturing and industrial Internet have become the focus of development. AI and big data technologies are playing an increasingly important role in production process optimization, quality control, supply chain management, etc., promoting the transformation and upgrading of traditional industries. This means that the demand for compound talents with interdisciplinary knowledge, data analysis capabilities, and innovative thinking will increase significantly in the future. The college entrance examination volunteer application service needs to guide students to pay attention to these emerging industrial fields and choose matching majors, such as intelligent manufacturing engineering, robotics engineering, data science and big data technology.

secondlyThe dual impact of AI on the job market.The development of AI technology has had a substitution effect and a creative effect on the labor market. On the one hand, AI has shown strong substitution capabilities in physical positions such as manufacturing assembly lines, logistics and warehousing, as well as brain scenarios such as data annotation, basic code writing, and customer service consultation, which may lead to the disappearance of some traditional positions or a decrease in demand. On the other hand, AI has also created a large number of new occupations and positions, such as AI trainers, data scientists, algorithm engineers, intelligent system maintainers, etc. At the same time, the popularization of AI has also improved the efficiency and value of existing positions, requiring practitioners to have the ability to collaborate with AI. Therefore, the college entrance examination volunteer filling service must help students recognize this change in employment structure, guide them to choose majors that are not easily replaced by AI or can synergize with AI, and cultivate lifelong learning skills to adapt to the rapidly changing employment environment.

againBig data empowers education and employment.Big data technology provides an unprecedented data foundation for college entrance examination volunteers. Through in-depth mining and analysis of massive education data (such as enrollment and admission data over the years, professional employment data, and college training quality data), industry data (such as talent demand trends, salary levels, career development paths), and personal data (such as academic performance, hobbies, and personality traits), AI systems can achieve more accurate personalized recommendations. This can not only help students find the most suitable majors and colleges for themselves, but also optimize the professional settings of colleges and universities and provide decision-making support for accurate recruitment of enterprises, so as to realize the deep integration of the education chain, talent chain, industrial chain and innovation chain.

At lastAI is a profound change in higher education.Artificial General Intelligence (AGI), as a common technology, is reshaping higher education in unprecedented ways. It is not only an important learning tool, but also promotes the integration of virtual and real teaching spaces, intelligent facilities and resources to improve teaching quality. The informatization construction of colleges and universities is changing from infrastructure construction to ecological construction that deeply empowers teaching, scientific research, management and services, with data as the base and AI as the engine, strengthening cross-departmental collaboration and cultivating compound talents. This means that future education will focus more on the cultivation of practical ability, innovation ability and interdisciplinary knowledge. The college entrance examination volunteer application service needs to keep up with the pace of educational reform and guide students to choose majors and colleges that focus on cultivating future core literacy, rather than just traditional knowledge transfer majors.

All in all, technological developments, especially AI and big data, are accelerating the reshaping of China’s industrialization, education models, and employment patterns. As a bridge connecting education and employment, AI college entrance examination volunteer filling service must make full use of these technological advantages to provide students with forward-looking, personalized and all-round guidance to help them cope with future challenges and seize development opportunities.

Cultural factors

Traditional Chinese culture and social concepts have a profound and complex impact on college entrance examination volunteering and employment choices. These cultural factors, such as the emphasis on family, the pursuit of “face”, the desire for social status, and the consideration of pension, together shape the behavior patterns of students and parents in educational decision-making.

First of allThe educational concept of “hoping for children to grow up, hoping for women to become phoenixes”。 In Chinese families, children’s education is regarded as the top priority of the family, carrying the expectations of parents and the glory of the family. As an important social mobility channel, the college entrance examination has high hopes of “jumping around” and “getting ahead”. This concept makes parents often tend to choose prestigious universities and hot majors when volunteering, even if these majors may not match the students’ interests, or the employment prospects are not as optimistic as imagined. AI volunteer filling service needs to understand this cultural psychology, and while providing personalized recommendations, it is also necessary to guide parents and students to rationally view the aura and enthusiasm of prestigious schools, and pay more attention to students’ interests, potential, and long-term development.

secondly“Face” culture and social recognition.In Chinese society, “face” is an important social capital, which is not only related to personal dignity, but also represents the social status and reputation of the family. Choosing a good university and a “decent” major is often regarded as a performance of “earning face” for the family. This cultural psychology may lead students and parents to overly pursue socially recognized majors, such as doctors, lawyers, civil servants, etc., while ignoring the huge potential of emerging industries or technical majors when volunteering to fill out the application. The AI volunteer filling system can show the real employment prospects, salary levels and career development paths of different majors through data analysis, helping students and parents break the shackles of traditional concepts and make choices that are more in line with reality and future trends.

againThe traditional concept of “raising children to prevent old age” and the pressure of pension。 Although the modern society is becoming more and more diverse, the traditional concept of “raising children to prevent old age” is still deeply rooted. The career development and economic ability of children are directly related to the quality of parents’ future pension. This makes parents tend to choose those occupations with stable income, high social status and security in their children’s professional choices to ensure that their children have the ability to support themselves in the future. For example, industries such as finance, IT, and medicine are favored for their high income and stability. AI volunteer filling service can provide long-term development prediction and pension security analysis for different occupations, helping families balance economic returns and social responsibility in education investment.

furthermoreSocial pressures such as marriage, bride price, and childbirth.In some areas, social phenomena such as high bride price and pressure to buy a house have caused young people to face a huge economic burden. This indirectly affects their consideration of career choices, and they tend to choose careers that can quickly accumulate wealth and provide stable income in order to better cope with these social pressures. This practical consideration may also affect the choice of major when filling in the college entrance examination volunteer application. The AI volunteer filling system can provide more comprehensive career planning, including the income growth curve of different occupations, wealth accumulation potential, etc., to help students find a development path that suits them while facing real pressure.

At lastThe far-reaching impact of the imperial examination system.As the “imperial examination” in modern China, the college entrance examination is still an important way for ordinary people to achieve a leap in social class. This kind of competition mechanism of “thousands of troops crossing the single-plank bridge” has made students and parents attach great importance to the college entrance examination volunteer application, and has also given rise to a huge demand for professional guidance services. AI volunteer filling services meet this demand and help students stand out in the fierce competition by providing more scientific and personalized guidance.

All in all, China’s unique cultural and social concepts profoundly affect the college entrance examination volunteer application and employment choices. While providing technical support, the AI college entrance examination volunteer filling service also needs to fully understand and respect these cultural factors, and help students and families make wise decisions that are both in line with personal development and social reality through more humane and comprehensive analysis and guidance.

conclusion

Based on the above analysis of China’s political policy, economic development, population development (aging), technology (industrialization, AI, big data) and culture, clear conclusions can be drawn: The college entrance examination volunteer application market will not only continue to grow, but also its demand for intelligent and professional services will show explosive growth.

1) The market size has been growing and will continue to expand: Available data shows that the payment scale of China’s college entrance examination volunteer application market has increased from 950 million yuan in 2023 to 1.02 billion yuan in 2024, and is expected to reach 1.09 billion yuan in 2025. This indicates that the market is in a period of rapid growth. Future growth will be driven by:

The complexity of the new college entrance examination reform: The model of “college professional group” or “professional (class) + college”, as well as the differences in policies of various provinces, has significantly increased the difficulty and risk of volunteering, and professional guidance has become a rigid need.
Employment pressure and employment orientation: Economic transformation and intensified competition in the job market have made students and parents have an unprecedented demand for “learning to be useful” and “employment after graduation”, and they are willing to pay for professional guidance that can bring good employment prospects.
Willingness to invest in family education: The accumulation of family wealth brought about by economic development and the traditional cultural concept of “hoping for children to grow up” have made families’ willingness to invest in their children’s education continue to rise, and professional volunteer application services are regarded as an important investment in education.
The long-term existence of information asymmetry is: Although the number of channels for obtaining information has increased, the fragmentation, specialization, and timeliness of information have made it difficult for ordinary families to complete high-quality volunteer applications independently, and there is still a huge market space for professional services.

2) AI technology will become the core driver of market growth:

Enhancing Service Efficiency and Accuracy: AI and big data can process massive amounts of data and provide more accurate and personalized matching solutions than human ones, effectively avoiding the risk of filling in the application and improving the success rate of admission and professional satisfaction.
Reduce service costs and expand inclusiveness: With the maturity and large-scale application of AI technology, the marginal cost of services will be reduced, allowing more low- and middle-income families to enjoy high-quality volunteer filling services, thereby expanding market coverage.
Innovate service models and expand the value chain: AI can not only provide filling solutions, but also extend to full-chain services such as career planning, talent training, and employment docking, creating new business models and growth points.
Respond to market chaos and improve industry standardization: AI is based on the objectivity of data and algorithms, which helps reduce subjective bias and false propaganda in manual consultations, promote the healthy development of the industry, and enhance user trust.

3) Deep support for cultural and social concepts: Chinese society’s emphasis on education and “getting ahead”, as well as the consideration of children’s future career development and pension, will continue to drive the demand for college entrance examination volunteer application services. AI can better meet this deep-seated cultural need and provide solutions that better meet family expectations.

To sum up, the college entrance examination volunteer application market is in a golden period of development driven by multiple factors such as policy, economy, population, technology and culture. The deep integration of AI technology will accelerate the intelligent, personalized and inclusive process of this market, making it a blue ocean market with great potential。

Business analysis

The essence of volunteering

The essence of the college entrance examination volunteer filling requirements is not just to choose a university or a major, its core goal isRealize the unity of personal and social values, and ultimately lead to better employment and income levels.Specifically:

Employment: This is the most direct and common need. Students and parents hope to choose a promising and competitive major in the future job market through the college entrance examination volunteer application, so as to successfully find a job and achieve a good start in their careers. The quality of employment (such as industry, company, position) is directly related to the social status and development space of individuals.
Revenue: Immediately after employment, income is an important measure of career success. Choosing a major with high salary and growth potential is an important consideration for many families to invest in education. High income can not only improve the living standards of individuals and families, but also provide material security for future pensions and children’s education.
Personal Development and Value Realization: In addition to utilitarian employment and income, the essence of volunteer filling also includes the exploration and realization of personal interests and potential. Students hope to choose a major they like, are good at, and can give full play to their strengths, so as to gain a sense of accomplishment and satisfaction in their study and work, and realize their self-worth.
Social class leap and family expectations: In Chinese society, the college entrance examination is an important channel of social mobility. Entering prestigious schools and choosing hot majors through the college entrance examination is often regarded as an important way to achieve social class leap and meet family expectations. Behind this is the embodiment of traditional cultural concepts such as “getting ahead” and “glorifying ancestors”. Avoidance of risks and information asymmetry: Under the new college entrance examination model, the complexity of volunteer application makes students and parents face huge information asymmetry and decision-making risks. They need professional guidance to avoid risks such as “slipping”, “withdrawing”, and “professional adjustment” to ensure that they can smoothly enter their ideal universities and majors.

Therefore, the success of the AI college entrance examination volunteer filling business lies in whether it can accurately grasp and meet these deep-seated needs, rather than just providing a simple score matching tool.

Business Connection and Analysis

The value of the college entrance examination volunteer filling business under the perspective of AI technology far exceeds that of a single filling link, and it can serve as a core hub to connect the entire life cycle of talents from training to employment, forming an efficient and intelligent ecosystem. The following will be a detailed analysis of the connections between each link:

1) Talent training (upstream):

Traditional mode: The talent training of colleges and universities is often based on the discipline system and the existing curriculum, which is out of touch with social needs, resulting in structural contradictions such as difficulty in the employment of graduates and difficulty in recruiting talents by enterprises.

AI Empowerment: Through an in-depth analysis of big data in the job market (enterprise employment needs, industry development trends, and job skill requirements), the AI volunteer filling system can guide colleges and universities to cultivate talents in reverse. For example, AI can identify the demand for compound talents in emerging industries in the future, provide data support to universities, prompt them to optimize professional settings, adjust curriculum content, strengthen school-enterprise cooperation, achieve “customized training on demand”, and cultivate talents that are more in line with market demand. At the same time, AI can also provide students with personalized learning path planning, guiding them to improve their skills in a targeted manner during their college years, bridging the gap between training and needs.

2) College Entrance Examination Selection and Major Selection (Core):

Traditional mode: Candidates and their parents mainly choose based on scores, school rankings, popular majors and other information, and lack an in-depth understanding of professional connotation, employment prospects, personal interests and professional matching, and are easy to blindly follow or passively choose.

AI Empowerment: The AI volunteer filling system is a key link connecting talent training and enterprise employment. It integrates multi-dimensional information such as college entrance examination data (scores, rankings), college enrollment plans, professional employment data, and students’ personal characteristics (interests, abilities, and personalities). Through intelligent algorithms, AI is able to provide candidates with:

Accurate Matching: Based on the candidate’s scores and personal characteristics, the most suitable combination of majors and colleges is recommended to maximize the probability of admission.
Employment orientation: Combined with professional employment prospects, salary levels, career development paths and other data, it helps candidates make more forward-looking choices.
Risk avoidance: Simulate the filling plan, predict the risk of slippage and retirement, and provide optimization suggestions.
Personalized planning: It is not only filled in, but also based on AI-based career interest assessment and ability analysis, guiding students to understand themselves and choose the development direction that truly suits them.

3) College plan (midstream):

Traditional mode:When colleges and universities formulate enrollment plans and major settings, they mainly judge based on historical data and experience, and are slow to respond to changes in market demand.

AI Empowerment:The AI volunteer filling platform has accumulated a large amount of candidate volunteer data and employment data, which can provide accurate market insights for colleges and universities. For example, which majors are favored by candidates, which majors have a high employment rate, and which majors have a large talent gap. Colleges and universities can use these data to more scientifically adjust enrollment plans, optimize professional structures, and enhance professional attractiveness, thereby improving the quality of students and the employment rate of graduates.

4) Enterprise employment (downstream):

Traditional mode:Enterprise recruitment mainly relies on traditional methods such as resume screening and interviews, which are less efficient and difficult to accurately match the most suitable talents.

AI Empowerment:AI volunteer filling business can be seamlessly connected with enterprise recruitment systems (such as BOSS direct recruitment). Through the complete data chain analysis of students’ major choices to university study and internship experience, AI can provide enterprises with more accurate talent portraits. Businesses can use this data to:

Talent portrait construction:Understand the ability characteristics, knowledge structure and career tendencies of graduates of different majors.
Precise recruitment:According to job requirements, AI screens out the most matched candidates to improve recruitment efficiency and quality. Talent pool: Identify potential college students in advance and establish a talent pool.

5) Headhunters and HR (downstream enablers):

Traditional mode:Headhunters and HR mainly rely on experience and limited information for talent search and management, and their efficiency is limited.

AI Empowerment:AI volunteer filling business provides executive search and HR with richer and earlier talent data and analysis tools:
Headhunting:You can use platform data to discover and evaluate potential outstanding talents earlier, understand their professional backgrounds and career development intentions, so as to make more accurate talent recommendations and career planning guidance.
HR：AI tools can be used for talent inventory, career development planning, employee training needs analysis, etc. For example, by analyzing employees’ professional backgrounds and career development paths, we provide personalized career development suggestions to employees and improve employee satisfaction and retention.

Connection of the complete business chain:

The AI college entrance examination volunteer filling business closely connects these seemingly independent links, forming a complete closed loop from “education entrance” to “career exit”:

Data-driven: Job market data (corporate employment, headhunting, HR) feeds back the college entrance examination selection and professional selection, and guides students to make decisions that are more in line with market demand.
Talent customization: Colleges and universities adjust their talent training programs according to market demand to cultivate talents that are more suitable for the needs of enterprises.
Precise Conveying: The AI system accurately transports the cultivated talents to the most suitable positions to achieve job matching.
Continuous Optimization: Data from the entire chain is continuously accumulated and feedback, and AI algorithms are continuously optimized to improve the efficiency and accuracy of each link.

This integration not only improves efficiency and reduces information asymmetry, but more importantly, it builds a dynamic and intelligent talent ecosystem, realizes the deep integration of education chain, talent chain, industrial chain and innovation chain, and creates greater value for individuals, universities, enterprises and society.

Industry analysis

Competitive analysis

At present, the college entrance examination volunteer filling market is in a period of rapid development, and the market size continues to expand, but at the same time, it shows the characteristics of imperfect market, large number of competing products but uneven quality.

Imperfect market:

Serious information asymmetry: Although the Internet provides a large amount of information, there is still a huge information gap for ordinary candidates and their families, such as the complexity of admissions policies (especially the filling method of “college professional group” or “major + college” under the new college entrance examination model), the understanding of professional connotations, and the accurate judgment of employment prospects. The market lacks an authoritative, unified and easy-to-understand information platform.
Lack of standardized services: A unified service standard and evaluation system has not yet been formed in the industry, and the service content, process, and charging standards vary greatly. This makes it difficult for consumers to distinguish the quality of services, and it is easy to fall into “information traps” or “high prices and low quality” services.
Insufficient supervision and frequent chaos: With the increase in market heat, all kinds of institutions are mixed, and chaos such as false propaganda, exaggerated effects, creating anxiety, and abnormally high fees is not uncommon. Government ministries have begun to pay attention to and warn about related risks, but it will still take time for the industry to standardize.

A large number of competitors:

Traditional Consulting Agencies: Mainly offline, one-on-one or small group consulting services are provided, relying on the experience and resources of counselors.
Online Platform/APP: For example, excellent volunteers, perfect volunteers, etc., provide data query, intelligent recommendation, simulated filling and other functions, mostly using SaaS subscription or value-added service models.
Personal IP/Famous Teacher: Represented by Zhang Xuefeng, consulting services or knowledge paid products are provided through personal influence.
Transformation of education and training institutions: After the “double reduction”, large education companies such as Good Future, New Oriental, and Gaotu have expanded their business to the field of further education planning and volunteer application, using their technology, data and brand advantages.
Internet giants enter the game: Internet companies such as Alibaba (Quark) and Zhihu have also launched college entrance examination volunteer services with their traffic and technical advantages, mostly in the form of free tools + value-added services.

Variable quality:

Lack of professionalism: Many institutions and individual consultants lack systematic professional knowledge and data analysis capabilities, and their suggestions may be based on one-sided information or personal experience, making it difficult to provide scientific and comprehensive guidance.
Data lag or inaccuracy: Some platforms do not update data in a timely manner or data sources are unreliable, resulting in biased recommendation results.
Overmarketing: In order to attract users, some institutions overemphasize risks such as “high scores and low scores” and “slippage”, creating anxiety rather than really solving problems.
Service homogenization: Most products converge in function, lack core competitiveness, and are difficult to form differentiated advantages.

Zhang Xuefeng

The business model is immature, the business model is too old-fashioned,
Without growth, the core competitiveness is the quality of the product, that is, [Zhang Xuefeng’s teaching] itself.
Static view of market positions and talent matching, lack of dynamic analysis of market industry and job changes like consulting companies, and cannot predict the development trend of talent employment.

The Zhang Xuefeng phenomenon is a microcosm of the college entrance examination volunteer filling market, and its success lies in accurately grasping the employment-oriented needs and realizing traffic monetization through powerful personal IP. However, from a deeper business and business model, it has the following limitations:

1) Limitations of the business model:

High dependence on personal IP: Zhang Xuefeng’s core competitiveness lies in his personal knowledge, experience and expression skills. The bottleneck of this model is that it is difficult to replicate it on a large scale due to limited personal energy. Once a person’s IP is damaged or their energy is weak, the business will face huge risks.
“Teaching instead of being data-driven: Although Zhang Xuefeng cites data, it is still essentially a “teaching” or “consulting” service based on personal experience and judgment. This model is difficult to deeply mine and cross-verify massive, real-time, and multi-dimensional data like AI, so as to provide more scientific and accurate personalized solutions.
“Still” view of the market: As users said, Zhang Xuefeng’s analysis is more based on current or past market positions and talent matching, and lacks the ability to dynamically analyze and predict industry and job changes like professional consulting firms. It is difficult for him to systematically predict the development trend of talent employment in the next 10-50 years, which is a significant disadvantage in the rapidly changing job market.
Lack of full-chain services: Zhang Xuefeng’s services are mainly focused on the volunteer application process, which fails to effectively connect the entire life cycle of talent training, university learning, career development, etc., and cannot provide continuous value.

2) The “old-fashioned” business model and the bottleneck of growth:

High-priced one-on-one/small class mode: Although the market demand is strong, the high cost limits the inclusiveness of the service, making it difficult to cover a wider range of user groups. The scale of this model is limited by the number and quality of counselors.
Limitations of Knowledge Payment: Despite the expansion of coverage through online courses and lectures, the essence of knowledge payment is still content sales, not ongoing services. After a one-time purchase, it is difficult to guarantee subsequent personalized guidance and data updates.
Lack of ecological integration: Zhang Xuefeng’s business model is relatively independent, and it fails to effectively integrate upstream and downstream resources such as education, employment, and talent training to form a coordinated development ecosystem, which limits the further exploration of its business value.

Summary: Zhang Xuefeng’s success is the product of the combination of market pain points and personal IP, but his business model and business model are relatively “old-fashioned” and “static” in the face of AI technology and market development trends, and lack the power to continue to grow and the ability to deeply integrate. AI technology can make up for these shortcomings, providing more dynamic, accurate, inclusive, and scalable solutions.

Education companies

(Good Future, New Oriental, Gaotu, Ape Tutoring, etc.)

After the “double reduction” policy, traditional education giants such as Good Future, New Oriental, Gaotu, and Ape Tutoring have sought transformation, and regarded AI technology as a new growth point, actively laying out the field of further education planning and volunteer application. Not only do they do, but they are becoming important competitors in this field.

Advantages of the combination of education giants and AI volunteer filling:

Data Benefits: These education companies have accumulated massive amounts of student learning data, exam data, course data, etc., providing a rich foundation for AI model training.
Technical advantages: They have continuous investment in AI, big data, cloud computing and other technical fields, and have the ability to develop and operate complex AI systems.
Brand and User Base: Strong brand recognition and a large user base help it quickly promote AI volunteer filling services. Accumulation of professional knowledge: Years of deep cultivation in the education industry, so that they have a deep understanding of education policies, enrollment rules, professional settings, etc.
Ecological Synergy: AI volunteer filling services can form synergies with its existing learning counseling, career planning and other businesses to build a more complete educational ecosystem.

Challenge:

Data Privacy and Security: Sensitive student data is involved, requiring strict adherence to data privacy regulations.
Algorithmic fairness: Ensure fairness in AI recommendations to avoid exacerbating educational inequities or stereotypes.
Market trust: In the face of the strong influence of personal IPs such as Zhang Xuefeng, it is necessary to win the trust of users through high-quality services and transparent mechanisms.
Policy Compliance: Pay close attention to the supervision and policy of the Ministry of Education on volunteer filling services to ensure the compliance of the business.

Overall, traditional education giants and online education platforms are important participants and competitors in the AI college entrance examination volunteer filling market with their advantages in data, technology, brand, and users. The combination of them and AI technology will promote the development of college entrance examination volunteer filling services in a smarter, more personalized and more inclusive direction

summary

Is the business immature?

But related businesses, such as upstream market analysis, downstream employment choices, and talent training, are fragmented?

On the whole, the current college entrance examination volunteer filling business does have the characteristics of immaturity, and it is “fragmented” with upstream market analysis, downstream employment choice, talent training and other related businesses.

1) Immature business:

Lack of uniform standards and specifications: There is no recognized service standard, charging model and effect evaluation system in the industry, resulting in poor service quality and difficult choice for consumers.
Information silos are serious: The data of various institutions and platforms are relatively independent, and they cannot effectively integrate multi-dimensional information such as education, employment, and industry, resulting in insufficient comprehensive and in-depth analysis.
Over-reliance on human experience: Most services still rely heavily on the personal experience and judgment of counselors, making it difficult to achieve scale, standardization, and intelligence.
Single business model: It mainly focuses on consulting fees and membership fees, and lacks diversified profit models and sustainable development capabilities.

2) Related businesses are “fragmented”:

Upstream Market Analysis: Market analysis such as macroeconomic trends, industrial policies, and demographic changes is often carried out by professional research institutions or government departments, and there is a lack of effective connection with specific volunteer filling services. Volunteer filling agencies usually only can only obtain second-hand information, making it difficult to conduct in-depth analysis and prediction.
Downstream employment options: Students’ major choices are closely related to future employment, but employment information (such as corporate recruitment needs, job salary, and career development paths) is mainly in the hands of recruitment platforms, headhunting companies, and corporate HR, and there are information barriers between educational institutions and volunteer application services.
Talent training: There is a lag between the talent training programs, professional settings, and curriculum content of colleges and universities and the demand of the job market. Although the volunteer application service guides students to choose a major, it cannot directly affect the training process of colleges and universities, and it is difficult to track students’ career development after graduation.

This “fragmented” state leads to:

Inefficient messaging: From market demand to talent training to employment, the flow of information is not smooth, resulting in a misallocation of resources.
Decision chain break: When students volunteer to fill out the application, it is difficult to obtain complete and dynamic guidance throughout their careers.
Limited Service Value: It is difficult to maximize the value of a single link of service and form a synergistic effect.

AI technology is the key to solving this “fragmentation” and “immaturity”. Through AI and big data, information silos can be broken, data from all parties can be integrated, and the whole chain from macro market analysis, to college entrance examination selection, to talent training and employment can be opened, and an intelligent, efficient, and collaborative talent ecosystem can be built. This will be the core direction of the future college entrance examination volunteer filling business.

Forecast of job market and industry trends

The current and future job market is undergoing unprecedented transformation, influenced by a combination of social, political, economic, cultural developments, population ageing and technological developments. These changes not only reshape the demand for talents, but also put forward new thinking on the necessity of the college entrance examination, the changes in positions, and the logic of professional selection.

Prediction of the change trend of the college entrance examination system

As the core mechanism of selecting talents in China, the college entrance examination is necessaryIt will remain highly necessary now and for some time to come, but its form and connotation will continue to evolve.

1) The cornerstone of social equity: The college entrance examination largely guarantees educational fairness and social class mobility. Despite various controversies, it is still the fairest and most transparent talent selection mechanism recognized by Chinese society. In the absence of other fairer and more efficient alternatives, there is no substitute for the social function of the college entrance examination. It provides opportunities for the children of ordinary families to change their destinies through knowledge, and maintains social stability and basic fairness.

2) Efficiency of large-scale talent selection: Millions of candidates in China take the college entrance examination every year, and an efficient and standardized selection system is needed. The college entrance examination can be preliminarily screened among a large number of people, and students with basic learning ability and knowledge reserve can be sent to higher education. While AI technology can assist in assessments, completely replacing such large-scale, unified exams is not realistic in the short term.

3) National strategy and talent reserve: The college entrance examination is an important means for the country to control the direction of talent training. Through the adjustment of college entrance examination policies (such as the new college entrance examination reform, the strong foundation plan, the special plan, etc.), students can be guided to strategic emerging industries and basic disciplines urgently needed by the country, and talents can be reserved for national development.

4) Future evolution trend:

Diversified selection methods: With the deepening of education reform, the college entrance examination may no longer be the only criterion for “one test for life”. Comprehensive quality evaluation, independent enrollment in colleges and universities, professional ability tests, etc. will occupy a more important proportion. AI technology will play a key role in comprehensive quality evaluation and personalized ability assessment, such as providing more comprehensive evaluation reports by analyzing students’ learning process data and project practice results.
Closer integration with career development: The college entrance examination will pay more attention to the connection with future career development. The content of the exam may focus more on examining students’ comprehensive ability, innovative thinking and ability to solve practical problems, rather than simply retaining knowledge. Volunteer filling will also place more emphasis on career planning and career education.
AI-Assisted Decision-Making: AI technology will not replace the college entrance examination, but will be deeply integrated into all aspects of the college entrance examination, including propositions, marking, admissions, volunteer filling, etc., to improve efficiency and fairness.

Conclusion: The college entrance examination will continue to be the “anchor” of the Chinese talent selection system in the foreseeable future, and its fairness, efficiency, and national strategic significance make it indispensable. However, it will no longer be an isolated exam, but will be deeply integrated with AI technology, comprehensive quality evaluation, career planning, etc., and develop in a more diverse, scientific and personalized direction.

The alternation of old and new markets/positions predicts the change trend of talent ability matching

With the progress of science and technology and social development, the job market is undergoing a profound structural change, which is manifested in the shrinkage of the old market, the replacement of old and new positions, and the fundamental change in the requirements for talent ability.

1) The shrinkage of the old market and the elimination of traditional jobs:

Automation and intelligence: Industrial robots, automated production lines, AI customer service, intelligent financial software, etc. are replacing a large amount of repetitive, regular, low-skilled manual labor and some mental labor. For example, the demand for general workers, bank tellers, telephone customer service, data entry clerks and other positions in traditional factories will continue to decrease.
Information Flattening: The Internet and big data have reduced the cost of information acquisition, and the value of traditional information intermediaries (such as partial sales and agents) has been weakened.
Industrial restructuring: Factors such as energy transition and environmental protection policies have led to the transformation or elimination of traditional industries with high pollution and high energy consumption, and the number of related jobs has decreased.

2) The alternation of old and new jobs and the rise of emerging markets:

AI-related positions: Data scientists, machine learning engineers, AI trainers, algorithm engineers, intelligent hardware development engineers, AI ethicists, etc.
Big Data and Cloud Computing: Cloud computing architects, big data engineers, data analysts, data visualization experts, etc.
New energy and intelligent networking: new energy vehicle engineers, intelligent driving system engineers, battery technology engineers, charging pile operation and maintenance, etc.
Digital economy and platform economy: E-commerce operations, live streaming, content creators, platform algorithm recommenders, digital marketing experts, etc.
Life Sciences & Biotechnology: Gene editing engineer, biomedical research and development, precision medicine consultant, health manager, etc.
Compound service industry: Elderly care services, psychological counseling, high-end customized tourism, personalized education, etc., these fields need to combine professional knowledge and humanistic care.

3) Changes in the demand for talent capabilities:

Core competencies: Critical thinking and complex problem-solving skills: Ability to think independently, analyze, and propose innovative solutions in the face of unstructured problems and rapidly changing environments.
Innovation and Adaptability: Be able to quickly learn new knowledge, master new skills, and adapt to new environments and challenges.
Interdisciplinary Integration Ability: Be able to integrate knowledge from different fields, form systematic thinking, and solve cross-disciplinary problems. ditch
Communication Collaboration and Emotional Intelligence: Collaborate efficiently in a team, and have good interpersonal communication skills and emotional management skills.
Lifelong Learning Ability: The speed of knowledge update is accelerating, learning has become a norm, and it is necessary to have self-driven learning ability.

4) Technical literacy:

Data Literacy: The ability to understand, analyze, and make decisions using data, including data collection, cleaning, analysis, visualization, etc.
AI Literacy: Understand the basic principles, application scenarios, and limitations of AI, and be able to work collaboratively with AI tools to improve work efficiency.
Digital tool application capabilities: Proficient in various digital office, collaboration, design, and development tools.

5) Humanistic quality:

Ethics: Adhere to the bottom line of humanity in technological development and have a sense of social responsibility.
Cultural Understanding and Inclusion: Adapt to globalization and multicultural environments, and have the ability to communicate across cultures.

The value of AI college entrance examination volunteer filling business: It is precisely because it can dynamically track these market and job changes, provide students with forward-looking professional and career choice suggestions through big data analysis and AI prediction, and guide them to cultivate the core competencies required by the future society, so as to achieve accurate matching of people and jobs and the sustainable development of talents.

Prediction of the change trend of factors in the selection of majors, colleges and institutions

In college entrance examination volunteer filling and career planning, [test score], [personal interest], [social class], [family background] and [personal ability] are the key factors affecting decision-making. These factors do not exist in isolation, but are intertwined, and their weights vary according to individual circumstances and historical contexts. AI volunteer filling systems need to be able to comprehensively evaluate these factors and provide personalized decision support.

1) Test score (decisive threshold, but gradually decreasing):

Function: Test scores are a hard threshold for admission to universities and specific majors. It directly determines the level of college and the scope of majors that candidates can choose. Under the current college entrance examination system, scores are still the first screening indicator.

Weight changes: With the reform of the new college entrance examination and the implementation of comprehensive evaluation enrollment, although the importance of scores is still high, their decisive weight is relatively decreasing. Colleges and universities are paying more and more attention to students’ comprehensive quality, subject characteristics and innovation potential. Simple high scores are no longer the only pass, and the risks of high scores and low energy are also increasing.

AI Applications: AI can accurately predict the probability of candidates with different scores entering majors in various colleges and universities based on historical admission data, provide the optimal “rush and stability” strategy, and maximize admission opportunities.

2) Personal interests (long-term development and internal driving force, increasing weight):

Function: Interest is an intrinsic driver of learning and career development. Choosing a major that aligns with your interests can stimulate your enthusiasm for learning, improve learning efficiency, and achieve higher satisfaction and accomplishment in your future career. Interest is also the key to meeting career challenges and achieving sustainable growth.

Weight changes: With the advancement of social development and educational concepts, as well as the demand for innovative and compound talents in the job market, the weight of personal interest is increasing. Parents and students are increasingly aware that blindly pursuing passionate majors can lead to lack of motivation to learn, burnout, and even affect long-term development.

AI Applications: AI can identify and evaluate students’ interests through professional interest assessments (such as the Holland Career Interest Test), learning behavior data analysis, and even natural language processing technology to analyze students’ daily expressions, and match them with majors and occupations. For example, recommend interest-related professional courses, career development paths, and industry cases.

3) Personal ability (the core element of career success, the weight continues to increase):

Function: Personal abilities include learning ability, problem-solving ability, innovation ability, communication and collaboration ability, pressure resistance ability, professional skills, etc. These are the core elements of a student’s success in university studies and future career development. Scores represent past learning outcomes, while abilities determine future development potential.

Weight changes: In the rapidly changing job market, the weight of individual ability continues to increase. Corporate recruitment is increasingly focusing on the actual ability and comprehensive quality of candidates, rather than just academic qualifications and majors. In the AI era, talents with the ability to work collaboratively with AI, continuous learning, and innovative problem-solving are more popular.

AI Applications: AI can evaluate students’ ability levels by analyzing data such as learning reports, competition results, project experience, and internship experience. At the same time, AI can provide personalized ability improvement suggestions and learning resources according to the requirements of different majors and occupations to help students make up for their shortcomings and give full play to their strengths.

4) Family background (implicit influencing factors, complex weights):

Function: Family background includes family economic status, parents’ occupation, educational concepts, social resources, etc. It can affect students’ access to educational information, their long-term risk tolerance when choosing a major, and the starting point of their future career development. For example, families with better economic conditions may be more inclined to choose majors (such as medicine) with higher tuition fees and longer learning cycles but high returns, or to support their children to study abroad; Families with extensive social resources may have an advantage in employment referrals.

Weight changes: Despite society’s advocacy for educational equity, the implicit influence of family background still exists. Its weight is complex, with both positive resource support and conceptual limitations. AI volunteer filling should face up to its impact, but not amplify its decisive role, but is committed to helping students maximize the use of existing resources and make up for potential disadvantages through information transparency and scientific planning.

AI Applications: AI needs to be cautious when dealing with family backgrounds to avoid exacerbating educational injustices. It can provide input-output analysis of different majors and occupations, helping families make the best choice within their financial affordability. At the same time, AI can recommend more diverse career development paths, helping students break the limitations of family background and expand their horizons.

5) Social class (long-term goals and social identity, stable weight):

Function: Social class is the position of an individual in the social structure, which is closely related to occupation, income, social prestige, etc. Many students and families want to achieve upward mobility in social classes through education, choosing majors and careers that can bring higher social status and a sense of identity.

Weight changes: As a long-term goal, social class has a relatively stable weight. The college entrance examination is still an important way to achieve class mobility. AI volunteer filling needs to understand this deep-seated social need, but it also needs to guide students to realize that social class mobility is not achieved overnight, but requires continuous personal efforts and ability improvement.

AI Applications: AI can provide students with a more comprehensive career profile by analyzing data such as social prestige, career development paths, and contributions to society of different occupations. At the same time, AI can help students plan a path to achieve their class goals, such as by choosing a specific major, accumulating work experience, and continuing to learn.

Decision support with integrated weights and AI:

The AI volunteer filling system should be used when choosing majors, occupations and collegesDynamic weighting and multi-objective optimizationStrategy:

Base weight: As a hard screening condition, the weight of the test score is the highest in the early stage, but its weight will decrease relatively as the selection range narrows.
Core Weights: Personal interests and abilities should be given higher weight, as they are key to determining students’ long-term development and career satisfaction.
Auxiliary weights: Family background and social class are auxiliary considerations, and AI should provide relevant information and analysis to help students and families make more realistic decisions, but avoid overemphasizing.
Personalized Adjustments: AI systems should allow users to individually adjust the weight of various factors according to their own situation, for example, for students who value special interests, the weight of interest can be appropriately increased.
Multi-objective optimization: AI systems should be able to optimize multiple goals simultaneously, for example, to maximize interest matching, career development potential, and family financial affordability while meeting score requirements.

Through this comprehensive evaluation and dynamic weighting, the AI college entrance examination volunteer filling system can provide more scientific, comprehensive and personalized decision-making support than traditional manual consultation, helping students make the most suitable major, career and college choices in a complex and ever-changing social environment.

Scheme evaluation

Product value assessment

The value of the college entrance examination volunteer filling business under the perspective of AI technology is not only reflected in the commercial level, but also in its huge social value and strategic significance.

Business value

The market size is huge and continues to grow: As mentioned earlier, the market size of the college entrance examination volunteer application has reached billions of yuan, and it continues to grow driven by multiple factors such as policy, economy, population, technology and culture. AI empowerment will further expand market boundaries and increase willingness to pay.
High customer unit price and high profit margin: Volunteer filling service belongs to the field of education consulting, with a relatively high unit price, and AI technology can effectively reduce marginal costs and increase profit margins.
Diversified profit model: In addition to traditional consulting fees and membership fees, diversified profits can also be achieved through C-end personalized training program subscriptions, B-end talent recruitment service fees, university cooperation technology service fees, advertising fees, data service fees, etc.
Data asset value: The massive amount of student data, employment data, and college data accumulated by the platform is a valuable asset in itself, which can be used for deeper data analysis, model training, and product development.
Brand and Ecological Effect: Enterprises that take the lead in building a full-chain ecosystem of “education-employment” will form strong brand barriers and network effects, attract more users and partners, and achieve exponential growth.

Social value

Promoting Educational Equity: AI technology can break down geographical and information barriers, allowing more students in underdeveloped areas and ordinary families to receive high-quality and personalized volunteer filling guidance, narrowing the gap in educational resources.
Optimize talent allocation: Through accurate matching, students are guided to choose majors that are more in line with social needs and personal potential, reduce talent misallocation and waste of resources, and improve the overall human capital efficiency of the country.
Relieve employment pressure: Solve the employment problem from the source (major selection), help students choose promising majors, enhance employment competitiveness, and relieve social employment pressure.
Promote education reform: AI data feedback can inversely promote colleges and universities to optimize their professional settings and reform talent training models, so that education can better meet the needs of social development.
Enhance the happiness of the people: Help students choose majors and careers that truly suit them, improve their satisfaction with study and work, and thus improve their personal happiness and social harmony.

Strategic price

Build an “education version of LinkedIn”: Deeply integrate education and employment, form a full life cycle service platform from students to professionals, create an ecosystem covering education, talent, and employment, and become the core infrastructure of the future talent market.
Seize the future talent highland: In the AI era, talent has become the core of national competition. Through AI-empowered college entrance examination volunteer filling, talents in line with future development trends can be discovered, cultivated and delivered earlier, and seize the talent highland.
Data-Driven Decision-Making: Provide big data-based decision-making support for governments, universities, and enterprises, and help macro talent planning and micro talent management.

Demand value assessment

Solve user pain points

Eliminate information gaps: At present, the market information asymmetry of college entrance examination volunteer filling is serious, and AI can integrate college data, employment trends, and policy orientation to provide accurate recommendations.
Personalized matching: Traditional services rely on human experience (such as Zhang Xuefeng), and AI can provide more scientific decision-making support based on big data analysis (such as industry demand and salary trends).
Reduce costs and increase efficiency: AI can replace some high-priced manual consultations (such as Zhang Xuefeng’s 17,999 yuan course) and reduce the financial burden on parents.

Market demand is strong

Market size growth: In 2025, the college entrance examination volunteer payment market is expected to reach 1.09 billion yuan, and 88.1% of candidates are willing to pay for filling services.
Policy support: The Ministry of Education has launched a free “Sunshine Volunteer” system, but the functions are limited, and AI can supplement in-depth analysis.
Employment-oriented demand: 52.8% of candidates give priority to “employment prospects and salary”, and AI can predict industry trends and optimize major choices.

Business integration potential

Open up the industrial chain: Existing market fragmentation (upstream data analysis, downstream employment services), AI can be integrated:

Market(Population, policy, industry demand)
Professional matching(College, score, career plan)
Employment docking(Corporate HR, headhunting services)
Talent training(Skills training, lifelong learning)

Feasibility analysis

Technical feasibility

1) Mature AI large models: For example, Quark and Baidu have launched volunteer filling AI, but the functions are shallow (only data screening), and prediction and decision-making capabilities need to be enhanced.

2) Reliable data sources:

Public data (Ministry of Education, college enrollment information)
Enterprise recruitment data (BOSS direct recruitment, Zhilian)
Macroeconomic data (industry growth, policy orientation)

3) Algorithm optimization direction:

short term: Provide “stability and guarantee” suggestions based on historical admission data (existing model).

long-term: Dynamically adjust recommendations based on career development models (such as industry needs in 10 years).

Commercial viability

1) Market viability:

Rigid Requirements: The college entrance examination volunteer application is a rigid demand of millions of families every year, and the reform of the new college entrance examination has exacerbated its complexity, and the market demand is strong. pay
High willingness: Parents are willing to invest in their children’s education, and the college entrance examination volunteer application is directly related to the future development of their children, and the willingness to pay is high. Market teaching
Low cost of breeding: The market has a high awareness of volunteer filling services, and there is no need for large-scale market education.
High AI Acceptance: The younger generation is highly receptive to AI technology and is more willing to try intelligent and personalized services.

2) Profit model:

3) Competitive Advantage:

vs Zhang Xuefeng: Lower cost, wider coverage, dynamic data updates.
vs MOE Free System: More in-depth career planning and enterprise docking.

Policy feasibility:

National strategic support: The country vigorously develops emerging technologies such as artificial intelligence and big data, and emphasizes the integration of education and industry, providing policy support for AI-empowered education.
Educational reform orientation: The new college entrance examination reform aims to cultivate innovative talents, and the AI volunteer filling service is consistent with the direction of reform, which will help achieve educational goals.
Standardized development: Despite the current chaos in the market, the government is gradually strengthening supervision and standardizing the development of the industry, which provides a good development environment for AI platforms that operate in compliance.

Risks and challenges

Data Privacy: It is necessary to obtain candidate information in compliance to avoid abuse.
Algorithmic bias: It is necessary to prevent recommendations from biasing towards “popular majors” (such as AI may over-recommend computers and ignore unpopular and high-quality majors).
Market trust: Parents may trust human experts (such as Zhang Xuefeng’s emotional value) more, and need to verify the reliability of AI through cases.

Product planning

1) Core functional modules

Based on the above value assessment and possibility analysis, the product planning of AI college entrance examination volunteer filling business should focus on the core concept of “data-driven, intelligent recommendation, full-chain service, and ecological openness”.

Product Vision: Become an intelligent bridge between education and employment, empowering every student to achieve personalized growth and career success.

Intelligent volunteer recommendation system:

Data integration: Integrate the admission data of the college entrance examination over the years, college enrollment plans, professional employment data, subject evaluation results, industry development trends, salary levels, etc.
Personalized assessment: Provide AI-based interest assessment, ability assessment, personality assessment, and generate personal portraits.
Intelligent Matching Algorithm: Based on the candidate’s scores, personal portraits, and target majors/college preferences, the optimal volunteer filling plan (rush, stability, and guarantee) is generated through the multi-objective optimization algorithm, and the admission probability analysis is provided.
Risk warning: Real-time monitoring of volunteer insurance (such as slippage, withdrawal, professional adjustment of risks) and providing avoidance suggestions.
Mock filling: Provide online simulation filling function, allowing users to familiarize themselves with the process and verify the plan in advance.

Career Planning and Development Platform:

Career map: Establish a detailed vocational knowledge map, including the definition of each occupation, job content, skill requirements, development path, salary range, industry prospects, etc.
Career Path Planning: Based on students’ major choices and personal development goals, we provide personalized career development path suggestions, including study priorities, internship suggestions, certificate examinations, etc. during college.
Skill improvement recommendation: According to career development needs and personal ability shortcomings, recommend relevant online courses, training programs, practical opportunities, etc.
Industry Trend Tracking: Real-time updates on the development trends of various industries and changes in talent demand provide students with forward-looking information.

In-depth analysis of colleges and majors:

College Database: It contains detailed information about colleges and universities across the country, such as historical evolution, faculty, scientific research strength, advantageous disciplines, campus culture, and the destination of graduates.
Encyclopedia: Introduce in detail the learning content, training objectives, employment direction, counterpart occupations, future development trends, etc. of each major.
Alumni Network: Establish an alumni community and provide alumni sharing, career mentor guidance and other functions to help students understand real-world learning and career experience.

Data analysis and decision support system (B-end/G-end):

College enrollment analysis:Provide colleges and universities with student source analysis, professional competitiveness analysis, and enrollment strategy optimization suggestions.
Talent supply and demand report: Provide reports on talent supply and demand forecasting, skill gap analysis, and industrial talent planning for the government and industry associations.
Enterprise talent portrait: Provide enterprises with ability portraits of graduates of specific majors or colleges, career tendency analysis, etc.

Development stage

Stage 1 (0-1 year): MVP basic data + AI recommendation

Target:Covering 80% of college data, providing basic volunteer filling suggestions.

Key Actions:

Access to the Ministry of Education’s Sunshine College Entrance Examination data.
Obtain the latest enrollment policies from cooperative universities.
Launch a free trial version to accumulate users.

Stage 2 (1-3 years): career planning + employment docking

Target:Introduce enterprise HR data to achieve a closed loop of “filling in and employment”.

Key Actions:

Cooperate with the recruitment platform (BOSS Direct Recruitment).
Launched B-end talent matching service (headhunting business).
Pilot customized enrollment models for private colleges.

Phase 3 (3-5 years): Ecological integration + globalization

Target:Become an “education-employment” super platform.

Key actions：

Expand data from overseas institutions (e.g. QS rankings).
Launch of corporate training subscription services (such as AI skills certification).
Government Cooperation (Regional Talent Development Plan).

Business model evolution

early: C-end subscription (such as 98 yuan/year) + advertising (educational institutions).
medium term: B-side commission (enterprise recruitment success fee) + G-end data service.
long-term: Ecological sharing (course sales, certification exams).

Operational Strategy:

C-end: Basic tools are provided free of charge, and value-added services such as advanced reports, one-on-one consultations, and personalized training programs are charged. Acquire users through social media, KOL collaboration, campus promotion, etc.
B-end/G-end: Provide customized solutions and make profits through project cooperation, technical service fees, etc. Expand business through industry conferences, professional exhibitions, government cooperation, etc.

Through clear product planning and phased implementation, the AI college entrance examination volunteer filling business is expected to stand out in the fierce market competition and achieve a win-win situation of commercial success and social value

Analyze and evaluate BOSS direct recruitment

Can BOSS direct hiring be done?

Conclusion: BOSS direct employment can not only be done, but also very suitable to do, and can even be said to have unique advantages.

The core business of BOSS Direct Recruitment is online recruitment, and its pioneering “mobile + intelligent matching + direct chat” model greatly improves recruitment efficiency and user experience. Applying AI technology to the college entrance examination volunteer filling business and connecting it with the existing recruitment business is a natural extension of BOSS Direct Recruitment’s business boundaries and an inevitable choice for it to build a more complete talent ecosystem.

Reasons that can be done:

Technical Foundation: BOSS Zhipin itself is a technology-driven company with mature technology accumulation and teams in AI intelligent matching, big data analysis, natural language processing, etc. These technical capabilities can be directly reused for intelligent recommendations, data analysis and personalized services for college entrance examination volunteer filling.
Data Benefits: BOSS Direct Recruitment has a large amount of corporate recruitment data, job data, and talent data, which are the core and scarce “fuel” for building the AI model for college entrance examination volunteers. Through these data, we can accurately analyze industry trends, job demand, salary levels, and career development paths, so as to provide students with employment-oriented volunteer filling suggestions.
User Base: BOSS Direct Recruitment has a large user base of B-end (enterprise) and C-end (job seeker). Although it is mainly aimed at professionals, its brand awareness and user stickiness can provide a natural traffic inlet for the promotion of new business. The future could attract college and even high school students who are about to graduate.
Mature business model: BOSS Zhipin’s business model (free trial + value-added services) has been verified by the market and can be used as a reference and applied to the college entrance examination volunteer filling business, such as free basic services, advanced reports, one-on-one consultations, personalized training programs and other value-added service charges.
Business Synergy: College entrance examination volunteer application and employment are two closely connected links in the talent life cycle. BOSS direct recruitment can achieve the full chain coverage from “talent entrance” to “career export”, forming a strong business synergy effect.

What are the advantages?

In terms of cutting into the AI college entrance examination volunteer filling business, BOSS Direct Recruitment has the following compared with traditional educational institutions and emerging startupsNotable Benefits:

1) Data Goldmine: The most authentic and cutting-edge employment data,This is the core advantage of BOSS Direct Recruitment.

Job Seeker/Student Data: The platform has accumulated a large amount of job seeker data, including their educational background, major, skills, job intentions, salary expectations, etc. This part of the data can be extended to current students to obtain their academic information and career tendencies through cooperation or guidance.
Enterprise Data: It has massive corporate recruitment data, including job demand, skill requirements, salary ranges, development trends, etc. in various industries. This data is the key to market forecasting, job analysis, and talent demand summary.
Industry data: Based on recruitment and job search data, BOSS Direct Recruitment can provide in-depth insights into the rise and fall of various industries, talent flow, emerging occupations and other trends.
School data docking: Although it may not be fully owned at present, based on its strong influence on the B-side and C-side, it will be relatively easy to establish cooperation with universities and obtain data on enrollment, training, employment, etc.

This is the core competitiveness of BOSS Direct Recruitment. The massive recruitment information, corporate demand, job salary, and talent flow data on its platform are incomparable to any other educational institution or consulting company. This data can help students and parents understand the most authentic job market and make truly “useful” choices, rather than judgments based on outdated or one-sided information.

2) The natural gene of “employment orientation”:

The core goal of the volunteer filling business is “employment and income”.

The core of BOSS Direct Recruitment’s business is “employment”, which gives it an unparalleled professional and data foundation in understanding the job market, corporate needs and career development paths. Directly connecting “filling in volunteers” with the “job search system” is a natural extension of its business.

3) The vision of opening up the whole link is aligned: The original product concept mentions the need to “improve and build a business model: unify four independent businesses: market forecasting, professional selection, employment selection, and talent training”. BOSS Direct Recruitment has the potential to open up these links:

Market: Leverage existing enterprise and industry data.
Professional Options: Based on employment data, popular majors and high-paying majors are inferred.
Employment Options: It is its core business.
Talent training: It can cooperate with online education platforms, or recommend skills courses based on job needs, or even “launch enterprise training subscription services (such as AI skills certification)” as mentioned in the product plan.

4) Direct grafting of business models:

The “B-end service” (finding talents/headhunting business for enterprises) and “C-end: collecting human resource data (HR business)” in product planning are the existing or easily expanded business areas of BOSS Direct Recruitment.

Its profit model (C-end subscription, B-end service commission, G-end cooperation, training business) is highly compatible with BOSS Zhipin’s business model.

5) Improve business efficiency by crossing intermediate links:

“The source student [fill in the volunteer] is directly connected with the terminal [job search system].

It crosses the middle of the selection of majors, colleges, postgraduate entrance examinations, public examinations and other links, reflecting the purpose-oriented [business efficiency]”.

It is the greatest value that BOSS Direct Recruitment can achieve, and it can provide fromThe entrance of the college entrance examination to the exit of the occupationOne-stop, through-type service to truly realize employment-oriented volunteer filling

6) B-end enterprise resources:

BOSS Zhipin has established cooperative relationships with millions of enterprises. This means that it can not only provide employment information, but also directly connect with the needs of enterprise internships, campus recruitment, and customized talent training in the future, forming a seamless connection from “choosing a major” to “finding a job”.

7) AI Technology and Product Experience:

BOSS Zhipin has accumulated rich experience in intelligent matching, recommendation algorithms, and user experience design. These experiences can be directly applied to college entrance examination volunteer application products to provide smarter, more convenient and more personalized services.

8) Talent life cycle management:

Compared with companies that only do volunteer filling or recruitment, BOSS Direct Recruitment has the opportunity to build a full life cycle service platform covering talents from education, training, employment to career development, forming a strong ecological barrier.

9) Brand Credibility and User Trust:

As a well-known online recruitment platform, BOSS Direct Recruitment has established a high brand credibility among job seekers and enterprises. This trust helps it quickly gain user recognition in the field of college entrance examination volunteer filling.

Do you have to do it

Conclusion: For BOSS Direct Recruitment, cutting into the AI college entrance examination volunteer filling business is a “must” rather than an “optional” for its future development strategy. If you don’t do it, you will face serious consequences.

From multiple dimensions such as AI technology, industry development, China’s economy, population aging, market changes and employment situation, this paper provides an in-depth analysis of why BOSS Direct Recruitment “must” carry out AI-driven college entrance examination volunteer filling business.

Reasons to do it:

1) AI technology development: competition and opportunities coexist

BOSS Direct Recruitment must embrace AI and deeply integrate it into its core business, and volunteering is an excellent entry point.

2) Industry development: the inevitability of industrial chain integration

At present, the college entrance examination volunteer filling market is seriously fragmented, and all links are fragmented. BOSS Zhipin is an inevitable choice to achieve industry integration and build a full life cycle service.

3) China’s economy: the challenge of transformation and talent matching

China’s economy is in a period of transition, putting forward new requirements for the talent structure.

4) Population aging: the urgency of optimal allocation of human resources

Population aging has brought about changes in labor structure and a trend of declining labor force.

5) Market changes: intensified competition and escalating user demand

The college entrance examination volunteer filling market is undergoing significant changes, and BOSS direct recruitment must adapt to or lead these changes.

6) Employment situation: accurate matching and efficiency improvement

The current job market is complex and changeable, and accurate matching is the core demand.

7) Expand user lifecycle value:

At present, the users directly hired by BOSS are mainly concentrated in the workplace. By cutting into the college entrance examination volunteer application, the user group can be extended to high school students and college students, locking in future talents in advance, extending the life cycle of users, and cultivating user stickiness. This is equivalent to putting the “entrance” of talent recruitment in front and building a deeper user moat.

8) Build a closed loop of talent ecology:

As mentioned earlier, the college entrance examination volunteer application is the starting point for talent training and employment. If BOSS does not enter this field, its talent ecological chain will be incomplete and cannot achieve a seamless connection from “education entry” to “career exit”. This will limit its long-term development space in the field of talent services.

9) Responding to market competition and innovation:

With the development of AI technology, more and more companies (including education giants and Internet companies) are entering the field of college entrance examination volunteer filling and trying to connect education and employment. If BOSS Direct Recruitment does not actively lay out, it will lose this strategic high ground, be seized by competitors, and may even face competition from the “education + employment” integrated platform in the future recruitment market.

10) Improve data dimension and accuracy:

The introduction of college entrance examination volunteer filling data can greatly enrich the talent portrait dimension of BOSS direct recruitment, making its understanding of talents more comprehensive and in-depth. For example, it can understand a person’s motivation for choosing a major, learning preferences, early career planning, etc., so as to provide more accurate services in subsequent recruitment matching.

11) Social responsibility and brand image:

Participating in the college entrance examination volunteer application, which is an important field related to the national economy, can enhance the sense of social responsibility and brand image of BOSS Direct Recruitment, making it not only a recruitment tool, but also an enabler of talent growth and development.

The consequences of not doing it

Serious consequences of not doing it (sailing against the current, if you don’t advance, you will retreat):

1) Missed strategic opportunities:

Losing its leadership position in the trend of “education + employment” integration, it was seized by other pioneers market share and user minds.

2) Loss of future growth points and market share:

College entrance examination volunteer filling is a huge incremental market. If BOSS does not enter, it will lose this important growth engine and miss the opportunity to seize the front-end market of “career lifecycle management”, and this piece of the cake will be divided by other awakened education or technology companies.

3) Business growth bottlenecks:

The existing recruitment business has limited room for growth, and the college entrance examination volunteer filling is a new growth point. Not entering this field will limit its future business expansion and market capitalization growth.

4) Ecological niche is replaced:

If other platforms successfully build an “education version of LinkedIn” ecosystem, BOSS Direct Recruitment may eventually become a provider of one of the links, rather than a dominant, and even face the risk of being marginalized.

5) Core competitiveness is eroded:

The existing recruitment and job search data is the advantage of BOSS Direct Recruitment, but if other AI platforms enter the field of volunteer filling and accumulate a large amount of student data and employment trend data, they may penetrate the downstream recruitment market and gradually erode the B-end and C-end advantages of BOSS Direct Recruitment.

6) Damage to brand value and loss of users:

In the era of AI empowerment, if BOSS Zhipin does not provide smarter and more forward-looking services, users may think that its products are stagnant and lack innovation capabilities.
As other platforms offer more comprehensive career planning and employment guidance services, BOSS Direct Recruitment may face the risk of users being diverted from an early stage, resulting in a decrease in potential users for its core recruitment business.
In particular, the younger generation of users have higher expectations for AI technology and may turn to platforms that provide intelligent services.

7) Abandoned by the trend of industry integration:

The industry is moving towards industrial chain integration. If BOSS Direct Recruitment sticks to back-end recruitment and does not extend to front-end education and talent training, its position in the entire education-employment ecosystem will be limited, and it may even be marginalized by competitors who provide full-link services.

8) Unable to respond to national strategies and the needs of the times:

In the context of the country’s emphasis on high-quality talent training and optimization of human resource allocation, if BOSS Zhipin fails to use its data advantages to play a role in the early planning of talents, it will lose the opportunity to serve the national strategy and contribute to social value, which may be regarded as a lack of foresight and social responsibility.

9) Increased data barriers:

The inability to obtain talent data on the education side leads to incomplete talent portraits, and may lag behind competitors with full-chain data in the accuracy of AI matching and recommendation.

10) Difficult to maximize data advantages:

Although the existing recruitment data is valuable, if it is not connected with the more front-end education data, it will not be possible to form a complete portrait of the impact of talent flow and major selection on employment. This will limit the further mining and commercial monetization of its data value.

To sum up, BOSS Direct Recruitment has strong genes and significant advantages in carrying out AI college entrance examination volunteer filling business. This is not only a natural extension of its business, but also a strategic necessity for it to maintain a leading position in the future talent service market, build a complete ecology, and achieve sustainable growth. Not actively deploying will mean missing out on huge market opportunities and may be in a passive position in future competition.

had to do

1) AI technology development: seize opportunities and build barriers

The inevitability of technological trends:

The capabilities of AI large models in data analysis, prediction and personalized recommendations are becoming more and more mature, and companies such as Quark and Baidu have launched preliminary volunteer filling AI products.
If BOSS Zhipin does not actively enter, it will miss the critical window period for AI applications and be seized by competitors to seize the user’s mind and data entrance.

Deep Advantages of Data Integration and Analysis:

BOSS Direct Recruitment has a large amount of data on job seekers, companies and industries.
Combined with AI technology, this data can be deeply mined to achieve accurate market forecasting, professional analysis and talent matching, and build unique data barriers and algorithm advantages.
This capability is unmatched by traditional manual counseling models.

Enhancing Efficiency and User Experience:

AI can automatically generate personalized training plans and career path recommendations,
Greatly improving service efficiency and accuracy, and reducing user decision-making costs is the mainstream direction of future services.

2) Industry development: industrial chain integration and ecological construction

Open up the closed loop of education and employment:

At present, the college entrance examination volunteer filling, market analysis, employment selection and talent training business are “fragmented”.
As the leading platform in the field of employment, BOSS Direct Recruitment has the ability and necessary to directly connect the “source student application application” with the “terminal job search system” to open up the whole industry chain from further education to employment.

Building a future talent ecosystem:

By integrating big data, market analysis, business consulting, HR, headhunting, talent training and other businesses, BOSS Direct Recruitment can be upgraded from a recruitment platform to a talent life cycle management platform and build a broader education-employment ecosystem.

Addressing Market Fragmentation:

In the face of the existing market environment of “few products and uneven quality”, BOSS Zhipin’s entry can take AI technology as the core, provide more systematic and professional solutions, and lead the industry towards standardization and intelligence.

3) China’s economic and employment situation: serving national strategies and solving social pain points

Optimize the talent structure and serve economic transformation:

China’s economy is in a critical period of transformation and upgrading, and the demand for high-quality talents is becoming increasingly urgent (13). AI volunteer filling can help students more scientifically choose majors that meet the needs of national development strategies and emerging industries, optimize the talent supply structure from the source, and alleviate structural contradictions in employment.

Dealing with employment stress and mismatch:

Graduates are under great pressure to find employment, and some majors are oversupplied and unusable.
AI can effectively reduce the mismatch between education and employment and improve the efficiency of talent allocation through the prediction of employment trends and talent demand analysis in the next 10-50 years.

Improve the quality of the workforce:

In the context of population aging, the total labor force is decreasing, and it is crucial to improve the quality and matching of the existing labor force.
This business can guide the younger generation to choose a more promising track and deliver talents for high-quality development.

4) Population aging: the strategic need to optimize human resource allocation

Workforce restructuring:

With the intensification of population aging, the demographic dividend of the labor force is gradually disappearing, and the refined allocation of human resources has become particularly important.

Improve talent effectiveness:

AI-powered volunteer filling can help the younger generation make more accurate choices at the beginning of their careers, improving the efficiency and quality of overall human resources to cope with possible labor shortages and structural problems in the future.

Long-term career development management:

This business can be extended to “career life cycle management”, providing continuous skill upgrade and career transformation advice to meet the demand for complex and high-quality talents in an aging society.

5) Market changes: seize opportunities and user demand upgrades

The temptation of market size:

The market size of the college entrance examination volunteer application is growing, and it is expected that the paid market will reach 1.09 billion yuan in 2025, and 88.1% of candidates are willing to pay for services.

This is a huge business blue ocean.

Changes in user needs:

Candidates and parents are no longer satisfied with simple score matching, they are more concerned about “employment prospects and salaries”, and the demand for long-term career planning is becoming increasingly strong.
AI can provide this depth and forward-looking analysis.

Limitations of the traditional model:

The core competitiveness of traditional manual consulting (such as the Zhang Xuefeng model) lies in “teaching quality”, but there are problems such as “the business model is too old-fashioned and there is no growth”, high cost, and limited coverage.
AI can provide services at a lower cost, with wider coverage and dynamically updated data.

summary

To sum up, from multiple perspectives such as AI technology, industry development, China’s economic transformation, population aging, market changes and employment situation, AI-driven college entrance examination volunteer filling business is not only a new growth point for BOSS Direct Recruitment, but also for itConsolidate core competitiveness, expand business boundaries, respond to the needs of the times, and even participate in the national talent strategy。 It represents the strategic upgrade of BOSS Direct Recruitment from “job hunting” to “career planning” and even “management talent ecology”.

Therefore, for BOSS Zhipin, carrying out AI-driven college entrance examination volunteer filling business is not only a “smooth sailing” to capture market opportunities, but also a “must” in the face of future competition and the development trend of the times. If you don’t do it, the consequences will be that you will lose room for growth, lose competitiveness, and even be surpassed by more integrated and innovative opponents, and fall into the dilemma of “sailing against the current, not advancing or retreating”.

BOSS Direct Recruitment is very suitable for carrying out “college entrance examination volunteer filling business from the perspective of AI technology” 。 This is indeed a strong alliance idea, which can give full play to the existing advantages of BOSS Direct Recruitment and achieve business synergy.

If BOSS Direct Hire wants to start this business, you can consider the following strategies:

Independent Sub-Brands/Business Lines: You can consider incubating an independent sub-brand or business line to operate the college entrance examination volunteer filling business to maintain professionalism and focus, and at the same time make better use of BOSS Zhipin’s brand endorsement and data sharing.
Data Security and Privacy: In view of the fact that the college entrance examination volunteer filling involves a large amount of personal sensitive information, BOSS Direct Recruitment needs to attach great importance to data privacy protection and compliance, establish a strict data management system, and dispel user doubts.
Expert Consultant Team: Although AI is the core, in the early and high-end services, combined with the professional experience of education experts and career planners (to make up for the “emotional value” and complex case judgment that AI may lack), it can better build market trust and provide “expert review” functions.
Market Education: In the face of the trust base of traditional consulting such as the “Zhang Xuefeng model”, it is necessary to gradually educate the market through a large number of successful cases, data proofs and user word-of-mouth, so that parents and candidates can accept and trust AI-driven decision-making.
Cooperation and expansion: Actively establish cooperation with the Ministry of Education, provincial examination institutes, and high schools to obtain authoritative data and policy support, and enter school channels for promotion.
Continuous Iteration and Differentiation: Continue to invest in AI research and development to improve the accuracy of market forecasting and career planning, while exploring more differentiated services, such as combining personalized skills training recommendations and even providing value-added services such as “job security” to cope with possible competitor imitation.

conclusion

1. Combining the AI-driven college entrance examination volunteer application business with the existing ecology of BOSS direct recruitment is a direction of great strategic significance and business potential.
2. BOSS Direct Recruitment’s advantages in data, employment genes and business integration capabilities give it a better opportunity than other competitors in the market to build a complete closed loop from “further education entrance” to “career export”“LinkedIn for Education”The grand vision of .