The competition for talent within the fund management sector is escalating, with a notable trend towards embedding artificial intelligence capabilities across various business functions, drawing significant market attention.
As the wave of artificial intelligence sweeps through every corner of the financial industry, the battle for talent among fund companies is quietly intensifying.
Recently, leading public fund managers, including E Fund Management Co., Ltd., have posted a series of novel job openings. Unlike traditional financial technology roles, these positions—such as "Institutional Sales Support Specialist (AI and Data Analytics Direction)," "Fund Operations AI Engineer," and "Brand Communications AI Engineer"—bear distinct AI characteristics, directly embedding AI capabilities into non-technical business lines like marketing and operations.
Industry insiders view this round of AI-focused recruitment by top-tier fund houses as an attempt to intelligently re-engineer entire business processes. This move serves as a vivid footnote to the digital transformation of leading institutions and could become a key action in widening the competitive gap within the industry.
Accelerated Recruitment for AI Roles
Lately, when fund industry professionals browse the recruitment websites of leading fund companies, the term "AI" is appearing with increasing frequency.
Taking the Institutional Sales Support Specialist (AI Direction) position posted by E Fund Management Co., Ltd. as an example, the role requires candidates to delve into the full spectrum of institutional business scenarios. From client profiling and product analysis to marketing effectiveness, they must build a data monitoring system and proactively identify high-value AI application scenarios, such as intelligent marketing assistance, automated report generation, and personalized product recommendations.
Similarly, the "Brand Communications AI Engineer" role at E Fund requires candidates to have a deep understanding of scenarios like promotional planning, media placement, and public sentiment monitoring. They are expected to lead initiatives in intelligent copy generation, AI-assisted production of posters and short videos, and continuously track the latest technologies like large language models, text-to-image/text-to-video generation, RAG, and Agents to assess their application potential in promotional and marketing work.
The "Fund Operations AI Engineer" position requires the candidate to oversee the development and design of accounting systems, use tools like Python and SQL to address urgent business needs, and manage the complete lifecycle of AI projects from validation to production deployment.
Furthermore, in recent years, several leading public fund managers have established dedicated "AI Talent Special Sessions" or "AI Talent Special Projects" in their recruitment efforts, which has also attracted market attention.
An industry insider based in southern China believes that this multi-dimensional recruitment of AI talent serves two purposes: first, to gain a head start in forming certain AI application capabilities through internal cultivation and specialized investment; second, to attempt to embed AI into the front-end of business operations to enhance the speed of decision support and customer service response.
An industry professional in Shanghai also noted that the underlying motivation is to leverage AI technology to achieve comprehensive digital transformation across all links—from investment research and product design to customer service and operations management—thereby improving overall operational efficiency and service quality. Simultaneously, it aims to enhance core competitive advantages by establishing AI talent specializations and launching AI application roles to seize the development opportunities presented by AI technology and drive business innovation and model transformation.
Trend Towards 'AI-ization' of Roles Draws Scrutiny
In reality, as the AI wave sweeps the globe, the entire fund industry is actively embracing this technological shift. AI is reshaping the ecosystem of the public fund industry, from investment research and trading to client services. The trend of AI penetrating various roles, leading to a "pan-AI-ization" of job functions, is also drawing industry focus.
A fund industry professional in Beijing stated that the current trend towards "pan-AI-ization" in talent deployment within the fund industry reflects the deep integration and broad application of technology in the financial sector. The main advantages include: firstly, improving efficiency and precision, as the application of AI technology can help fund companies enhance work efficiency and decision-making accuracy in multiple areas such as sales, operations, and brand communication; secondly, innovating service models, as the introduction of AI technology enables fund companies to innovate service models, offering more intelligent and personalized client services.
However, the same source also noted that while "pan-AI-ization" brings many opportunities, it also poses certain challenges for fund companies. For instance: how to reasonably arrange the division of labor and collaboration between AI and human workers to avoid operational risks from over-reliance on AI technology; and how to cultivate employees' AI skills to help them adapt to new working modes.
Discussing the current wave of AI-related recruitment, other industry insiders believe it reflects fund companies' active exploration of technology-driven operational efficiency improvements. On one hand, integrating AI capabilities into scenarios like sales, operations, and branding does have the potential to optimize processes, free up human resources, and improve the precision and responsiveness of decisions. On the other hand, not all roles are suitable for "pan-AI-ization," and the actual implementation effects require longer-term observation.
"The pace and focus also differ among companies. For example, some choose to pilot AI in their institutional sales divisions first, as this area has a solid data foundation and clear client needs; others start from middle and back-office operations, attempting to use AI to handle large volumes of repetitive accounting and review tasks," the source added. Overall, this trend warrants close attention, but given the differing resource endowments and business structures of each institution, widespread replication is challenging.
In reality, a practical issue is the relative scarcity of "business-savvy + AI-savvy" composite talent in the current market. Therefore, major fund companies face numerous challenges: intense external recruitment competition, long internal training cycles, and the fact that deep integration of "business understanding" and "AI understanding" is not something simple training can solve, involving certain磨合 costs. Consequently, various industries are competing for the limited pool of talent, leading to exceptionally fierce competition, a situation likely to persist for the next year or two.
Anxiety Over 'AI Replacement' Among Fund Industry Professionals
As AI-related job postings proliferate on recruitment pages, the group most concerned is arguably front-line fund industry employees. One fund company staff member exclaimed feeling "rolled over by AI."
Another professional from a fund company's branding department reported purchasing a new computer at the beginning of the year to experiment with "raising lobsters" (a metaphor for learning AI skills) to enhance their AI capabilities. According to their feedback, about 90% of the company's related brand videos are now produced using AI, significantly saving on manpower and material costs. Simultaneously, due to the rapid pace of AI development, they themselves are in a state of deep anxiety, worried about being replaced by AI one day. "You must keep up with the latest AI technology," they repeatedly emphasized.
Furthermore, they revealed that senior management at their company now requires department heads to justify, before initiating external recruitment, whether their current staff's workload is already saturated and whether work efficiency has been effectively improved.
"Anxiety over technological replacement and pressure for skill upgrades are long-standing. This stems partly from the rapid pace of external technological change, which is difficult for the average person to keep up with, and partly from an 'involution' culture. The source of this 'involution' largely comes from the anxiety of 'improve or fall behind' and the potential 'dimensional reduction attack' technology may pose to one's future career development," commented an industry insider from southern China.
Looking ahead 3 to 5 years, which roles might face relatively greater pressure to transform? One industry professional believes positions focused on standardized functions like data collation and basic report generation face the most pressure. Data that previously required manual line-by-line checking can now be completed in seconds by AI models. For roles requiring high levels of interpersonal interaction, complex judgment, and creative thinking, the pressure is more about how to enhance skills and work collaboratively with AI. For example, employees in brand communication roles may not need to overly worry about AI completely replacing text creation, but if they do not know how to use large language models, their work efficiency could lag far behind colleagues proficient in AI techniques.
Regarding future career development for professionals in the field, some insiders offer the following advice: maintain curiosity and basic learning capabilities regarding AI tools—one doesn't need to become a technical expert but should understand the boundaries of AI's capabilities; proactively seek scenarios within one's area of expertise where AI can add value; and strengthen abilities that AI finds difficult to replace, such as interpersonal communication and cross-departmental collaboration.
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