Roundtable Forum: Summer Cycles Again · VC3.0 | 36Kr WAVES 2026 New Wave 圆桌论坛：夏天周而复始·VC3.0| 36氪WAVES2026新浪潮

TL;DR

• The current AI investment cycle is characterized by a shift from pure technology speculation to deep industrial integration, where AI acts as a catalyst for structural changes across traditional sectors rather than replacing them entirely.
• Venture Capital models are evolving into "VC 3.0," requiring GPs to possess strong policy alignment capabilities, particularly with state-owned capital that demands local economic returns and industrial attraction alongside financial gains.
• AI is accelerating scientific discovery and manufacturing efficiency (e.g., protein folding, material science), offering China a strategic advantage in offsetting demographic challenges through "AI + Robotics."
• The labor market is undergoing severe polarization, with mid-level technical roles facing displacement while top-tier strategists and those capable of integrating AI tools see increased value, leading to a "one-nine" rule of wealth distribution.

Why It Matters

This discussion highlights the maturation of the AI industry from a hype-driven phase to a pragmatic, policy-aligned era where success depends on navigating complex geopolitical landscapes and government expectations. For investors and entrepreneurs, it signals that pure software plays are insufficient; value creation now requires deep integration with hard tech, manufacturing, and national strategic goals. Understanding these shifts is critical for aligning investment theses with the new reality of state-led capital and the evolving role of human labor in an automated economy.

Technical Details

• Investment Landscape Shift: There is a marked transition from dollar-funded, US-model replication to RMB-funded, policy-driven investments. State-owned capital now accounts for 80-90% of new fundraising, necessitating GP strategies that balance financial returns with local government mandates such as industrial attraction and reverse investment.
• AI for Science & Manufacturing: AI applications are demonstrating exponential speedups in R&D, such as reducing protein folding research time from years to weeks and accelerating oxygen production simulations for Mars colonization from 1200 years to two weeks. This underscores AI's role in enhancing traditional industry efficiency rather than just creating new digital services.
• Labor Market Polarization: The impact of AI on employment is described as creating a "one-nine" distribution curve. Mid-level workers (e.g., junior programmers, basic coders) face significant displacement due to AI agents' ability to handle tasks up to 70-80% proficiency. Value is increasingly concentrated among top-tier individuals who can refine AI outputs to 90-100% and those who build the underlying infrastructure ("shovel sellers").
• Geopolitical Context: The current cycle is deeply influenced by US-China technological competition. Chinese startups are no longer copying Western models but are expected to lead in areas like hardware, models, and applications, operating in a unique domestic context that requires navigating both international sanctions and domestic policy directives.

Industry Insight

• Strategic Alignment for GPs: Venture Capital firms must evolve beyond traditional due diligence to include policy analysis and government relations. Success depends on the ability to secure state capital by demonstrating how investments contribute to local industrial ecosystems and national strategic objectives.
• Focus on Hard Tech Integration: Investors should prioritize companies that combine AI with physical industries (manufacturing, healthcare, robotics) rather than pure software applications. The value proposition lies in tangible efficiency gains and solving real-world bottlenecks in traditional sectors.
• Talent Strategy for Startups: Entrepreneurs need to build teams that leverage AI for execution while retaining high-level human judgment for strategy and quality control. The workforce structure will likely shrink in the middle layers, requiring a focus on recruiting top-tier talent who can effectively orchestrate AI agents and navigate complex regulatory environments.