China AI Monthly - Excess Fear of AI Disruption in Software, Esp for China

Research evidence excerpt

China AI Monthly - Excess Fear of AI Disruption in Software, Esp for China

YTD from 6.1x to 5.7x. Our China (CN) SW basket (19 stocks): has fallen 13% YTD. Cons 2026 35

30 31 31 30 28 28 26 26 24

25rev has fallen 5% since Jan 12, and EV/S is down 15% YTD from 5.0x to 4.3x, suggesting the 20

sell-off was driven by earnings downgrade (D/G) and multiple contraction. 2015

The rise of LLMs and AI agents is driving a structural shift in SW architecture and 0

economics. We believe AI is NOT a SaaS "apocalypse", but a "natural selection mechanism", as .Source: Jefferies estimates (See Table 1 for details)

players with defensible moats that proactively embrace AI can evolve into AI-native platforms, Score: Max 40, min 0. High score = less vulnerable to AI

while those with weak moats and are slow to adopt AI risk displacement. Three key impacts:

Exhibit 4 - JEF SW coverage's AI moat and

1) Architectural shift. SW will transition from UI-centric, human-operated systems to API- timeframe of AI transition

first, agent-executable workflow platforms. Agents can automate tasks autonomously but

still rely on SW APIs for workflows, business logic, and data. 2) Pressure on seat-based

pricing. As agents replace human operators, per-seat pricing models face structural pressure,

pushing vendors toward consumption- and outcome-based pricing. 3) Margin pressure. Unlike

traditional SW's near-zero marginal cost, LLM inference is a big usage-based variable cost,

which means SW players will have to pass such costs on to customers or be able to charge

a healthy margin. . Source: Company, Jefferies

Timeframe only shows relative window for AI transition

CN SW is less prone to AI disruption, but frail IT budgets remain the headwind. Many CN