AI Talent Flooding into Traditional Automakers
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After six months of communication with candidate Wang Ming, veteran automotive industry headhunter Li Yuan finally closed the deal.
Wang Ming joined a top internet company upon graduation and spent over a decade playing pivotal roles in its autonomous driving division. When Li Yuan received a recruitment request from a new energy vehicle brand under a traditional automaker, Wang immediately came to mind. "What ultimately convinced him was his proactive mindset for change," Li told Tech Planet.
Wang isn't alone. A notable talent migration trend has emerged in recent years, with increasing numbers of professionals in AI and autonomous driving fields showing interest in opportunities from traditional automakers.
Previously, according to 21st Century Business Herald citing industry sources, Tao Ji, former CEO of L4 autonomous trucking company QianGua Technology, is set to join Changan Automobile to lead its intelligent driving technology, reporting directly to President Wang Jun. Tao joined Baidu in 2010 and participated in building Baidu's autonomous driving project from scratch.
Tao isn't an isolated case. In February, former XPeng VP of autonomous driving R&D Gu Junli became deputy general manager at Chery Auto. In August, former Horizon Robotics autonomous driving R&D director Liao Jie joined BYD to lead its Shanghai intelligent driving team. Jiang Jun, former core team lead of Huawei's autonomous driving product line, also joined Zeekr to oversee intelligent cockpit operations.
An automotive industry analyst told Tech Planet that from a commercialization perspective, automobiles represent one of the most viable landing scenarios for AI. Meanwhile, the cooling L4 autonomous driving market has created talent surpluses in related fields.
As traditional automakers increasingly dive into intelligent electrification transformations, a new wave of talent-market realignment is underway.
On June 10, 2020, Tesla surpassed Toyota for the first time to become the world's most valuable automaker. According to data from the China Machinery Industry Federation, in the first half of this year, China's new energy vehicle production and sales reached 3.788 million and 3.74 million units, respectively, with year-on-year growth exceeding 40%.
This has made traditional automakers feel the competitive threat from electrification and smart technologies. At the 2022 China EV100 Forum, Zhu Huarong, Chairman of Changan Automobile, made a striking statement: "I believe that in the next 3-5 years, 80% of Chinese (fuel-powered) brands will shut down, merge, or transform."
Against this backdrop, traditional automakers have accelerated their transformation efforts in recent years. In November 2020, GAC Aion began operating independently and later initiated mixed-ownership reforms. That same year, Dongfeng Motor established its independent new energy brand, Voyah. In 2021, Changan Automobile, in collaboration with CATL and Huawei, launched Avatr, while Geely introduced its high-end smart EV brand, Zeekr.
"Competing in electrification and smart technologies has long been an industry consensus," an automotive analyst told Tech Planet. Compared to new EV makers, traditional automakers' 'new generation' brands have capital and manufacturing experience but often lag in internet-driven thinking and software development capabilities, putting them at a disadvantage in the smart vehicle race.
This trend has also shifted traditional automakers' hiring needs. Li Yuan told Tech Planet, "Previously, traditional automakers mostly recruited graduates in mechanical engineering, automotive engineering, and transportation. Now, the industry is increasingly focusing on software engineering and AI-related talent in campus recruitment."
In 2023, BYD significantly expanded its recruitment. Public data shows that BYD hired 31,800 fresh graduates, with master's and doctoral degree holders accounting for 61.3% of the total. Among these new hires, 80.8% will be assigned to R&D roles.
Meanwhile, at the social recruitment level, AI and autonomous driving talent from the internet industry are beginning to flow into traditional automakers. However, multiple headhunters consulted by Tech Planet noted that traditional automakers have specific experience requirements for such talent.
"We've always emphasized that talent transitioning from internet giants to traditional or new energy vehicle companies must have relevant automotive project experience and the ability to transfer their knowledge," said Li Yuan. Professionals with only internet company experience but lacking automotive project background don't meet the requirements in this talent war initiated by traditional automakers.
Behind this requirement lies traditional automakers' urgency in the new energy market competition. As the intelligent technology race enters its second half, they're trying to enhance R&D and technical forecasting capabilities by expanding their teams of software algorithm engineers.
"They want to rapidly strengthen autonomous driving capabilities, especially in AI algorithms," said the analyst. External recruitment of experienced talent is clearly faster than internal training. "The industry is highly competitive now - falling behind by just 1-2 years could mean significant lag," Li Yuan noted.
Wang Ming was invited to lead the autonomous driving division of a traditional automaker's "new generation" business. Li Yuan revealed to Tech Planet that Wang spearheaded the company's autonomous driving system development.
Wang's total annual compensation package exceeds 3 million yuan, a high salary in traditional automakers. However, compared to his previous internet company's benefits and stock options, it's not exceptionally high. "Moreover, he has to take on more responsibilities and deliver greater results in this new environment."
In terms of compensation, traditional automakers don't have significant advantages over internet companies in this AI talent war. "To some extent, this represents internet talent making choices due to temporary oversupply," the analyst commented.
Financial reports show in 2022: SAIC Group's total compensation was 28.35 billion yuan (average 131,000 yuan/person); GAC Group 8.85 billion (88,000 yuan/person); Changan 6.94 billion (165,000 yuan/person). In contrast, Tencent's average annual salary reached 1.0253 million yuan.
"High salaries may attract talent, but traditional automakers can't match the pay scales of internet companies," headhunter Yuan Yuan told Tech Planet. She noted that traditional automakers have different compensation structures: "Internet companies offer year-end bonuses and stock options, while traditional automakers—even new energy vehicle startups—primarily provide cash."
Additionally, Li Yuan mentioned that compared to high-level talents like Wang Ming, traditional automakers currently focus their recruitment on professionals with five to eight years of experience. "They can lead projects, manage teams, and their overall compensation demands are relatively lower."
Among the candidates he recruits with five to eight years of experience, traditional automakers typically offer annual compensation packages ranging from 500,000 to 800,000 yuan. In contrast, Lin Lin, a 2021 master's graduate from a top-tier Beijing university, shared that his offer from a mid-sized internet company upon graduation already reached 500,000 yuan annually.
Most of these professionals join traditional automakers as technical experts, usually overseeing one or two projects, with job levels equivalent to P7 or P8 in the internet industry.
Li Yuan told Tech Planet that in this cross-industry talent flow, salary considerations involve multiple factors, such as regional cost of living, additional benefits from traditional automakers, and job stability.
He emphasized that when facing market choices, these professionals should focus less on direct salary comparisons and instead observe market trends and embrace change proactively.
Amid this talent migration from internet companies to traditional automakers, instances of 'mismatch' have also emerged.
Many of the talents recruited by Li Yuan have shared with him the differences between traditional automakers and internet companies, often accompanied by complaints such as "Why is the efficiency so low?" and "We've repeated this many times, but many issues remain unresolved."
Compared to internet companies, the automotive manufacturing industry has longer reporting chains, which naturally leads to longer decision-making cycles. "In the past, a major product cycle was three years, now it's been compressed to a year and a half, but it's still much longer than the product cycles in the internet industry," Li Yuan explained.
Li Yuan told Tech Planet that under these circumstances, everything from work culture to reporting chains presents a new challenge. However, he believes this "discomfort" is normal, as any industry transition comes with an adjustment period.
"In the early years, when we recruited for foreign companies, everyone thought working for a foreign company was ideal. But once they hit a ceiling in their career development, many still chose to move to domestic internet companies with different work models," Li Yuan added.
Meanwhile, new energy vehicle companies have been seen as a middle ground for such talents. An autonomous driving industry professional told Tech Planet, "New energy vehicle companies like NIO and XPeng have a work atmosphere closer to internet companies compared to traditional automakers."
However, Yuan Yuan pointed out that unlike traditional automakers, new energy vehicle companies urgently need talent not in the autonomous driving field but in supply chain and smart manufacturing. "This is essentially a mismatch between supply and demand," she said.
This year, as price wars in the automotive industry intensify, both traditional automakers and new energy vehicle companies have shown a declining demand for AI and autonomous driving-related talent.
"At this time last year, the recruitment frenzy was at its peak. Candidates with experience in autonomous driving algorithms or AI typically had five to six, if not seven or eight, job offers," said Li Yuan.
However, as competition intensified, the demand for related talent in traditional automakers has been largely met. "This year, the overall demand for autonomous driving has completely dropped," Li Yuan noted, citing a two-thirds reduction in hiring demand compared to the previous year based on his recruitment experience.
"Unlike the previous talent expansion frenzy led by the 'AI Four Giants' (SenseTime, Megvii, Yitu, and CloudWalk), traditional automakers are more cautious due to cost and management constraints," said Yuan Yuan.