【V+ Perspective】Is SaaS dead? No. It is being reassessed and restructured.

Recently, the argument that "SaaS is dead" has resurfaced. The reason is straightforward: the pace of AI technology advancement has far exceeded expectations, and the value of many products that were originally built on "interface + function encapsulation" is now being questioned as to whether AI will directly commoditize them. The capital market is also responding to the risks with valuation adjustments, and the volatility of cloud/software stocks has increased significantly.

1) What exactly is the market selling? Let's ground our emotions first.

If we use "the pullback from the 52-week high" as a simple and repeatable indicator, the recent pullback in the stock prices of many US cloud/software companies has fallen between 20% and 60%, with a median of around 39%, and a few stocks have even pulled back more.

• The focus isn't on any single company, but on the market rethinking a question: What software values will AI rapidly commoditize? And what values will be amplified by AI?

• Therefore, what you are seeing is not a "one-size-fits-all" market trend, but a "repricing": companies that can implement AI in enterprise processes, data, and risk control are usually more resilient to market downturns; pure tool-type, low-stickiness products will face greater pressure.

2) Is SaaS really doomed? There are two levels beneath the surface.

The first layer: SaaS is divided into two major customer groups - 2C and 2B.

• 2C (To Consumer) focuses on "single-point value and low integration costs":

  • Examples include: translation, language learning, personal content generation/editing, presentation/copywriting assistance, etc.

• 2B (To Business) leans towards "process-oriented, system-oriented, long-cycle implementation, and deep integration":

  • Examples include: internal process management, customer service/work orders, information governance, cybersecurity and compliance, and supply chain collaboration.

3) 2C: Simple applications can indeed be subjected to rapid crushing.

In the 2C world, many products are essentially "encapsulating capabilities as a UI." When AI capabilities are provided directly through dialogue/commands, and can even automate task processes, users will naturally ask, "Why should I pay a monthly fee for a single feature?"

• The categories most significantly affected typically include:

  • Translation and Language Learning (especially focusing on exercises/question banks/simple interactions)

  • Content generation/editing and simple design assistance

Demand has not disappeared, but differentiation has become thinner and supply has exploded, resulting in a decrease in pricing power and an increase in the cost of customer churn.

4) 2B: Enterprise-level software is difficult to replace in the short term

It's not that AI isn't powerful enough! Rather, there are several significant hurdles in enterprise-level scenarios:

• Deep integration: Complex connections with ERP, finance, HR, permissions, data warehouses, APIs, etc.

• Stable and accurate: run every day, no mistakes allowed, errors must be traceable and recoverable.

• Cybersecurity Compliance: Authorization, Audit, Retention, Supplier Risks and Compliance Evidence Chain

  
  

In other words, the competition in the B2B sector is not about "creating an AI demo," but about "putting AI into real-world operations and ensuring its stable operation."

5) The more crucial moat: private data

Public data (accessible via web scraping) has been widely learned by most large-scale models, and general-purpose capabilities are rapidly catching up. The truly high-value scenarios for enterprises mostly lie in private data that is unavailable or difficult to obtain on a large scale from outside sources.

• Transaction and fulfillment records, customer interaction and customer service conversations

• Internal documents, knowledge base, contracts and process specifications

• Process/equipment/maintenance data, audit and risk control records

  
  

Therefore, the key to enterprise-grade SaaS is not "whether it has AI", but whether it has private data assets that are governable, authorizable, and usable.

6) The final hurdle: Vertical domain know-how

Many B2B SaaS solutions are not general-purpose tools, but rather deeply embedded with industry know-how: industry language, judgment rules, exception processes, approval mechanisms, audit standards, and compliance requirements. These are not simply things that an AI agent "can generate" and "can be deployed."

7) Why did the stock price plummet? The fundamental reason was overvaluation; AI simply triggered a warning sign.

There are two common valuation languages for SaaS:

• Price-to-Earnings Ratio (P/E): Meaningful for companies with stable profits; often distorted for unprofitable companies.

• Enterprise Value/Revenue (EV/Revenue) or EV/ARR: A more commonly used framework for growth SaaS

In the past, when there was ample funding and a strong growth narrative, the market was willing to give high multiples; when interest rates, growth expectations, or the competitive landscape changed, valuations tended to quickly revert to their previous levels. AI makes the risk of "commoditizing value" more tangible, thus becoming the needle that pricks the bubble.

8) From a strategic perspective: Markets with more realistic valuations may actually present excellent opportunities to be oversold.

Compared to the US market's long-standing practice of giving software extremely high premiums, some markets (such as Taiwan) have always had relatively conservative valuations for SaaS (e.g., price-to-earnings ratios in the teens). After US assets have completed a 30-40% or even deeper correction, if the fundamentals remain solid and AI can be applied to private data and processes, it may actually create a more reasonable risk-reward opportunity.

In conclusion: SaaS is not dead; what's dead are SaaS products that only sell generic functions and interfaces.

The next round of winners will be more like a "system of record" plus an "AI layer (transforming private data into controllable automation)" plus "industry know-how and compliance capabilities." The market is shifting gears, and now is a critical window for repositioning and restructuring product strategies.

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VENTURE+ specializes in SaaS and AI investments, offering more than just funding. We provide startups with strategic guidance, corporate partnerships, and capital market planning. We aim to be the "Best Co-Founding Partner" bridging startups, venture capital, and industry leaders in long-term collaboration.