Analysis of the Impact of Zhou Guorui's Resignation on Kuaishou's Technical Strategy and Recommendation Algorithm Capabilities

Based on the latest market data and public information, I will systematically evaluate the potential impact of the resignation of Zhou Guorui, head of Kuaishou’s AI large model, from multiple dimensions.

As the

, Zhou Guorui oversees two core technical engines of Kuaishou:

• Recommendation algorithm system
  : The core competitiveness of content distribution for short video platforms, directly determining user dwell time, advertising monetization efficiency, and commercial growth
• AI large model capability
  : A key infrastructure supporting next-generation product experiences such as content understanding, user profiling, and intelligent search

Kuaishou’s technical DNA is built on the concept of “inclusive algorithm”, achieving differentiated competition through decentralized content distribution [1]. This core capability directly supports Kuaishou’s daily active user (DAU) scale (reaching 408 million in Q3 2024, a year-on-year increase of 5.4%) [2].

The recommendation system of short video platforms is the core channel for traffic monetization:

• Advertising efficiency
  : Precise recommendations directly affect CTR (Click-Through Rate) and eCPM (Effective Cost Per Mille)
• User retention
  : Personalized content distribution is a determinant of the DAU/MAU (Daily Active Users/Monthly Active Users) ratio
• E-commerce conversion
  : Live-streaming e-commerce GMV is highly dependent on algorithm matching efficiency

From the financial data perspective, Kuaishou’s Q3 2025 revenue reached HK$42.46 billion [0], and

.

Dimension	Impact Level	Specific Performance
Team Stability	⚠️ Medium-High	Core technical personnel may experience “unstable morale”, and the non-compete period may trigger team turbulence
Project Continuity	⚠️ Medium	Ongoing large model upgrade projects may face schedule delays or direction adjustments
Business Operations	✅ Limited Impact	The existing recommendation system is based on a mature architecture, and no functional gaps will occur in the short term

: Is Zhou Guorui’s resignation a personal choice or a systemic issue? From the information that his status changed from “on leave” to “Log Out”, , which increases the risk of team turbulence.

1. Slowdown in large model iteration rhythm
   : Kuaishou is catching up with the AI capabilities of leading companies such as ByteDance (Doubao 1.8) and Tencent [3], and the vacancy of the core leader may widen the technical gap

2. Stagnation in recommendation algorithm optimization
   : The industry is evolving toward multimodal understanding, real-time personalization, and cross-scenario recommendation; the lack of a leader may cause Kuaishou to miss the technical window

3. Decline in talent attraction capability
   : There is a “star effect” in the AI field; the resignation of top technical experts will weaken Kuaishou’s attractiveness to high-end talents

• User growth
  : The optimization speed of the recommendation algorithm directly affects user growth efficiency (e.g., customer acquisition cost CAC, retention rate)
• Commercialization efficiency
  : Balancing ad load rate and user experience requires refined algorithm tuning
• Emerging businesses
  : Innovative businesses such as AI-generated content (AIGC) and intelligent customer service may lack technical support

Based on current stock price data [0]:

• 52-week high
  : HK$92.60 (current price HK$63.85, down 30% from the annual high)
• Year-to-date gain
  : +57.46% (but down 19.07% in 3 months)
• Valuation level
  : P/E ratio of 13.85x, in a relatively reasonable range

:

• If the resignation news spreads and there is no clear successor arrangement, it may trigger short-term stock price fluctuations
• The long-term impact depends on whether Kuaishou can demonstrate the stability of its technical team within 3-6 months
• Investors will closely monitor the disclosure of AI investment and R&D expenses in the
  2025 Q4 financial report
  [4]

:

• The recommendation algorithm has been in operation for many years, with a
  sound engineering system
  and massive data accumulation
• Kuaishou has established a
  7×24-hour monitoring system combining a 10,000-person review team and AI technology
  [1], indicating strong technical infrastructure
• The company’s R&D team is large, so the departure of a single individual has limited impact on overall capabilities

:

• AI large models are in a
  frontier exploration field
  , highly dependent on the strategic judgment of leading figures
• Next-generation innovation
  of the recommendation algorithm (e.g., end-to-end models based on reinforcement learning) requires strong technical leaders [3]

Kuaishou has historically had a “dual-core” leadership model (Su Hua and Cheng Yixiao), and experienced growing pains during the transition to a single leadership [1]. This change in technical leadership occurs at a time when Kuaishou is facing:

• Business adjustment period
  : Recent layoffs in the commercial team and cancellation of some business lines [1]
• Security challenge period
  : Just suffered a large-scale attack by “black and gray industries” in December, exposing weaknesses in the defense system [1]

may amplify the negative impact of the technical leader’s departure.

: Despite the departure of dozens of management personnel, Apple’s AI R&D team remains active and innovative, thanks to nearly 200 internal contributors listed in a 96-page research document [3]. This indicates that .

The competition for AI talent in the industry was fierce in 2025:

• Meta Poaching Wave
  : Multiple core researchers from OpenAI (including core contributors to GPT-4o) were poached by Meta [5]
• Domestic AI Company Turmoil
  : Many AI startups face talent loss and commercialization difficulties [6]

These cases show that

.

1. Clarify Succession Arrangement
   : Announce the replacement plan for the technical leader as soon as possible to avoid an extended power vacuum
2. Stabilize Core Team
   : Implement incentive measures for key technical personnel to prevent chain resignations
3. Transparent Communication
   : Clearly communicate to the market that the technical roadmap remains unchanged to eliminate uncertainty

Strategic Direction	Specific Measures
Technical Echelon Building	Establish a multi-layer technical management system to reduce over-reliance on individual talents
External Cooperation	Strengthen industry-university-research cooperation with universities and research institutions to supplement technical capabilities
AI Infrastructure Investment	Increase investment in infrastructure such as computing power and data platforms to reduce reliance on individual capabilities
Talent Strategy Upgrade	Recruit well-known experts in the AI field to rebuild the image of technical leadership

• Diversified Technical Layout
  : Avoid betting all innovation on a single technical direction
• Product Moat Construction
  : Strengthen non-technical barriers such as content ecology and creator relationships
• Commercialization Structure Optimization
  : Reduce over-reliance on algorithm optimization and explore new monetization models

1. Personnel Change Signals
   • Whether a new AI technical leader is appointed within 3 months
   • Turnover rate of core technical team members
   • Frequency and content of external statements by technical executives

2. Technical Progress Indicators
   • Number and quality of AI-related patent applications
   • Iteration speed of large model versions
   • Performance of the recommendation algorithm in user duration and retention rate

3. Financial and Business Indicators
   • Trend of R&D expense ratio to revenue
   • Change in customer acquisition cost (CAC)
   • Ad load rate and monetization efficiency

4. Market Reaction
   • Whether stock price volatility rises abnormally
   • Adjustments to analyst ratings
   • Changes in short positions

: Mainly wait and see; focus on signals of stability in Kuaishou’s technical team

:

• If Kuaishou can quickly fill the technical leadership vacuum and maintain stable business data, it can be regarded as an
  opportunity to increase positions
• If there is large-scale loss of the technical team or a significant slowdown in user growth, it is necessary to
  reassess the investment logic

: Kuaishou’s differentiated advantages in the sinking market and content ecology still exist, but .

The potential impact of Zhou Guorui’s resignation on Kuaishou has the characteristics of

:

✅

: Kuaishou’s technical system is relatively mature, so the departure of a single individual will not cause business interruption

⚠️

:

1. Risk of falling behind in the AI large model competition
2. Decline in commercialization efficiency due to stagnation in recommendation algorithm innovation
3. Talent shortage caused by chain reaction in the technical team

• If the resignation involves deeper organizational issues (e.g., related to strategic differences or performance pressure), the impact may exceed expectations
• If competitors (ByteDance, Tencent) continue to widen the gap in AI capabilities, Kuaishou’s technical shortcomings will be harder to make up for
• Changes in the regulatory environment may amplify technical shortcomings (e.g., reliance on AI capabilities for content security review)

: This resignation is a stress test for Kuaishou’s technical strategy. The company’s response speed and ability will determine whether this becomes a turning point in its decline in technical competitiveness. It is recommended that investors and management closely monitor signals of stability in the technical team over the next 3 months.

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[0] Jinling AI Data Analysis Platform - Kuaishou Technology (1024.HK) Company Profile, Real-Time Quotes and Historical Price Data
[1] Fortune Channel - “Why has Kuaishou, which started with ‘Lao Tie Economy’, become a target of ‘black and gray industry’ attacks?” (https://caifuhao.eastmoney.com/news/20251225084413243769480)
[2] Sina Finance - “Traditional ‘manual + algorithm’ model is challenged, Kuaishou urgently recruits security positions with a monthly salary of 60,000” (https://finance.sina.com.cn/jjxw/2025-12-23/doc-inhcuunm5346437.shtml)
[3] 36Kr - AI Industry Reports and Related Information on ByteDance’s Doubao 1.8
[4] Yahoo Finance - “Farewell to the ‘pie-in-the-sky’ era! US VC institutions collectively predict: Enterprise-level AI will be large-scale implemented in 2026” (https://hk.finance.yahoo.com/news/告別-畫大餅-時代-美創投機構集體預言-2026年企業級ai將大規模落地-210005474.html)
[5] Business Insider - “12 executives, researchers, others who left OpenAI in 2025” (https://www.businessinsider.com/executives-board-members-and-researchers-who-left-openai-in-2025-2025-12)
[6] Wangjing She - “Series on ‘Big Factory Disease’ in the Internet from an AI Perspective” (https://m.sohu.com/a/969595690_120491808)