Recently, discussions regarding "SaaS is Dead" and "SaaS is Weak" have become active among IT industry professionals and investors.
These topics have gained attention following the rapid adoption of generative AI, which triggered a temporary, significant decline in the stock prices of SaaS companies.
In this blog, I would like to explain how to interpret these discussions and discuss their relationship with uSonar's own SaaS business model.
Introduction: A Review of Previous Discussions
Tracing the origins of this discussion, it appears that the prevailing theory is that it began with statements made by Microsoft CEO Satya Nadella at the end of 2024, suggesting that business tools such as SaaS would be transformed by the arrival of the AI era.
Since then, various opinions have been exchanged, primarily within parts of the SaaS industry. While there were actual moves to adapt businesses in light of this trend, the discussion subsequently subsided.
However, entering 2026, on January 30, the U.S. generative AI venture Anthropic announced an innovative implementation regarding the business AI "Claude Cowork." This attracted attention for its potential to drastically increase the efficiency of various office tasks, leading to a sudden decline in SaaS stocks in both Japan and the U.S.
The association that "full-scale business AI has finally arrived" and "the SaaS market might be replaced by AI" spread. However, looking at it more closely and calmly, there seems to be a difference between "SaaS that will be phased out" and "SaaS that will survive" in the AI era. What exactly is that difference?
Main Argument: The Definition of SaaS and Key Points for Identifying Surviving SaaS
Here, we define SaaS (Software as a Service) companies as follows.
Main Definitions and Features of SaaS
• Accessed via the Internet: No installation or physical package purchase required
- Subscription Model: Pay-as-you-go, monthly, or annual contract-based billing.
- Vendor Management and Updates: Maintenance, management, and the latest updates are handled by the service provider.
- Multi-tenant Architecture: A system structure where a single instance is shared among multiple customers.
- Cloud-based: Data is stored in the cloud via the internet and is accessible from outside the office.
Key Advantages and Disadvantages
- Advantages: Low implementation costs, no maintenance required, simultaneous multi-user access, and rapid deployment.
- Disadvantages: Limited customization, internet connectivity required, and potential security risks.
Representative Service Areas
- Operational Efficiency, Communication, Customer Management & Sales Support, HR & Back Office
So, which of these characteristics are perceived as "Dead" or "Weak"?
A careful examination of the ongoing discussion suggests that the impact of AI will be felt in three specific areas: ID-based billing, UI touchpoints, and in-house system development.
1. ID-Based Billing (Per-Seat or Per-User Pricing)
The traditional model was that the more users within an organization, the more the client company paid to the SaaS provider. However, the emergence of generative AI is disrupting this structure. As AI begins to take over human tasks, the number of required personnel—and consequently the number of contracted IDs—will decrease. The concern is that as efficiency improves, SaaS business revenue may decline.
2. UI Touchpoints
Providing various functions through an intuitive UI (User Interface) has been a core value of SaaS. The argument is that this value is rapidly becoming obsolete due to the evolution of AI.
Regardless of whether the UI is designed for humans, any LLM (Large Language Model) can generate the necessary business outputs simply by processing the input data. This means that the mere existence of a superior UI is no longer a sufficient reason to maintain a contract.
3. In-House System Development
The argument here is that the services and systems provided by SaaS vendors may be replaced because they can now be developed in-house using convenient AI tools. With AI capable of coding faster than software engineers and allowing for flexible, custom-tailored solutions, the incentive to continue paying fixed costs to SaaS companies is diminishing.
In summary, the reality of the debate is that several of the core strengths of SaaS companies are being neutralized by AI. This does not mean that all characteristics of SaaS have weakened. It is clear that the debate over the "Death of SaaS" refers specifically to the relative decline of feature-provision-based SaaS.
Conclusion: As a Data Infrastructure Provider, uSonar Is Positioned to Leverage Both AI and SaaS
uSonar provides value to corporate clients via a cloud-based model. While it can be categorized as SaaS in that respect, the value we deliver lies in our proprietary data. Consequently, our market position differs from that of other SaaS providers.
Our core strength lies in providing our corporate clients with our proprietary corporate database, "LBC (Linkage Business Code)." LBC is a master corporate dataset covering 12.5 million business locations. Beyond the collection and classification of corporate information from the internet, it is composed of irreplaceable and difficult-to-replicate data assets that we have independently built over more than 35 years since our establishment in 1990.
Below, we outline three key strengths of uSonar that are becoming increasingly vital in the AI era.
Barriers to Entry
Building a database of our scale today would require a significant investment of time and capital. While the emergence of AI has lowered the barrier to functional development, the value of accumulating original data remains unchanged.
Value as Raw Material for AI
In an era where generative AI and AI agents are entering the realm of corporate decision-making support, companies that possess high-precision corporate data are positioned at the origin and foundation of the AI supply chain. This is because no AI can maximize its potential without concrete, high-quality data.
High Retention Rate
Corporate databases integrated into core systems involve high switching costs once implemented. In fact, our churn rate is exceptionally low, at 0.21%.
What are your thoughts?
As with uSonar, I believe you can now understand that a business model based on data retention occupies a robust position relative to both AI companies and SaaS companies, allowing it to leverage the strengths of both.
While we continue to monitor the discourse surrounding "SaaS is Dead/Weak," uSonar remains committed to providing value to our corporate clients by focusing on the comprehensiveness, freshness, and accuracy of our corporate data.
