The AI "Deflation" Storm: Why is Even AMD Shaken When the SaaS Model Collapses?

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In early February 2026, tech stocks—including hardware giants like AMD—experienced a significant correction. This was not simply a profit-taking, but rather a core and deep-seated market structural problem that surfaced: investors began to question the impact of AI on the software industry, viewing it as shifting from "empowerment" to "deflation."

The so-called "impact on software business models" stems from market fears about the powerful capabilities of AI agents. Once AI becomes so efficient that it destroys the traditional software industry's "per-seat licensing" profit base, the value logic of the entire technology industry chain will be rewritten.

I. Core Fear: From "Empowering Humans" to "Replacing Humans"

In the past few years, Wall Street's optimistic assumptions about AI have been based on the "addition" logic: AI will make employees more efficient, so companies will buy more software (such as Copilot) for employees to use, and software companies' revenue will increase.

However, in early February 2026, with Anthropic and Google releasing a new generation of highly autonomous AI agent tools, the market landscape underwent a fundamental shift:

• The old model (the golden age of SaaS): If a company hired 100 lawyers or engineers, it would need to purchase 100 software licenses (Seats).

• The New Fear (The AI Agent Era): New AI tools can directly perform legal reviews or write code, rather than simply assist. Companies may only need to hire 10 senior professionals to oversee the AI, while the work of the remaining 90 people is done by AI.

• Result: Businesses will no longer need 100 software licenses, but only 10. This will cause the revenue ceiling for software giants such as Salesforce, Adobe, and even Microsoft to collapse.

II. In-depth analysis: What is the "deflation" of the software business model?

When the market discusses AI causing "deflation," it doesn't refer to a decline in overall economic prices, but rather to **"the technology causing a contraction in the total value (TAM) of the software industry"**. This is a highly disruptive shift in economic logic.

Why does maximizing efficiency lead to revenue destruction? We can look at it from three levels:

1. The avalanche of the "personnel" base

Current software giants (such as Zoom and Salesforce) rely on "per-capital billing." The investment logic assumes that as a company grows and has more employees, it will sell more software.

However, in the era of AI agents, if a company lays off 90% of its junior staff and only keeps core personnel to oversee the AI, 90% of the software company's user base will disappear instantly.

2. Price increases cannot compensate for the loss in quantity.

Even if software companies try to increase the price per unit (for example, by increasing the price per AI account by 50%), they cannot make up for the 90% drop in numbers.

• Previously: 100 people × $100 = $10,000 in revenue

• Currently: 10 people × $150 (including AI premium) = $1,500 in revenue

  This is deflation: technology advances, customer costs decrease (money stays in customer pockets), but software vendors' total revenue shrinks significantly.

3. The collapse of the valuation system

The high price-to-earnings ratio (P/E ratio) of software stocks is based on the assumption of "continuous high revenue growth". Once the market realizes that AI is "subtracting" (eliminating software and employees) rather than "adding", the value of software stocks will face a dramatic revaluation.

III. Chain Reaction: Why Does This Affect AMD and NVIDIA?

This is a reverse transmission of the supply chain. Although AMD and NVIDIA sell hardware, their fate is closely linked to the downstream software industry:

1. Software profitability is hampered: If SaaS companies find that customers are significantly reducing their purchasing seats due to the adoption of AI, their revenue growth will stagnate or even decline.

2. Capital Expenditure (CapEx) Tightening: Software companies are major customers of cloud services (AWS/Azure), and cloud giants are major customers of chip manufacturers. If the software layer cannot make money through AI (or even has its revenue eroded by AI), they will stop renting expensive AI computing power.

3. Hardware demand bubble bursts: Investors worry that current chip stock prices are built on "endless investment in AI infrastructure." Once terminal software proves to be "deflationary," upstream chip demand will vanish instantly.

IV. Tipping Point: Market Signals in February 2026

This surge in concerns is not unfounded, but rather based on specific market events:

• A fully automated demonstration: Anthropic and Google's new tools showcased "fully automated" capabilities in the legal and coding fields. Upon seeing the demo, the market immediately sold off software stocks in related verticals (such as legal technology and outsourcing companies).

• Enterprise IT budget freeze: According to market intelligence, some enterprises have begun to freeze traditional software procurement and instead wait and see if they can directly use AI Agents to replace existing complex software processes at a lower cost.

V. Conclusion: Reassessment of the Technology Industry Value Chain

Simply put, the market is currently experiencing a painful period of mindset adjustment:

• Past view: AI is additive (selling more chips, selling more software licenses).

• The current concern is that AI is subtraction (AI is becoming so good that it reduces the need for so much software and employees).

If software companies cannot find an effective way to successfully transition from "per capita" to "outcome-based" billing, then this "deflation storm" will not be limited to software stocks, but will spread along the supply chain, posing a severe fundamental challenge to hardware giants such as AMD.