Y Combinator: The market size of vertical AI agents will be ten times that of SaaS

In 2024, the wind of AI Agents is blowing stronger.

At the "Baidu World 2024" event on November 12, Baidu founder Robin Li emphasized that "intelligent agents are the most mainstream form of AI applications and are about to reach their explosion point."

Across the ocean, YC partner and seasoned investor Jared pointed out in the latest deep dive that vertical AI Agents are expected to become an emerging market ten times larger than SaaS, with significant advantages in replacing manual operations and improving efficiency, potentially giving rise to tech giants with a market value exceeding $300 billion.

So, why are the big players so optimistic about AI Agents?

In the latest episode of YC's program "Vertical AI Agents Could Be 10X Bigger Than SaaS," four seasoned YC investors—Gary, Jared, Harj, and Diana—analyzed why vertical AI agents will become the next entrepreneurial trend, starting from the development history of the SaaS industry, combining numerous examples and deep insights.

The four seasoned YC investors stated that advancements in LLM technology have laid the foundation for the development of AI Agents, with more and more startups beginning to utilize AI Agent technology to solve problems across various industries. When comparing AI to the early SaaS industry, the YC investors believe that breakthroughs in LLM technology are akin to the introduction of XML HTTP requests in browsers in 2004, opening up a new computing paradigm that allows AI Agents to deeply integrate software with manual operations, achieving a qualitative leap in efficiency and cost.

From Momentic's AI automated testing to Powerhelp's intelligent customer service system, and Salient's AI voice collection, vertical AI Agents are demonstrating strong capabilities in various niche markets. Since each field requires in-depth expertise, large companies find it challenging to quickly establish a presence, providing rare opportunities for entrepreneurs. More importantly, the application of LLMs will change the employment model in companies, and in the future, companies may achieve rapid growth with fewer employees.

At present, it seems that AI Agents have become the best choice for the implementation of AI.

1. The success of the SaaS industry is the best evidence for the rise of vertical AI Agents

Jared believes that the market size for vertical AI Agents will be enormous, potentially giving rise to companies with a market value exceeding $300 billion.

He believes that the success of the SaaS industry is the best evidence for the rise of vertical AI Agents. The emergence of the SaaS (Software as a Service) model has completely transformed the software industry. In the past, companies needed to purchase expensive software licenses and spend a lot of time and resources on installation and maintenance The SaaS model hosts software in the cloud, allowing users to access it by simply paying a subscription fee, significantly lowering the barriers and costs of software usage.

• Advantages of the SaaS Model:
  • Low Cost: No need to purchase expensive software licenses and hardware.
  • Ease of Use: Accessible via the internet without complex installation and configuration.
  • High Scalability: Subscription plans can be flexibly adjusted according to the needs of the business.
• Booming SaaS Industry: Over the past 20 years, the SaaS industry has received more than 40% of venture capital and has birthed over 300 unicorn companies, such as Salesforce, Workday, and Zoom. This fully demonstrates the enormous potential of the B2B software market.

Jared believes that vertical AI Agents, as an emerging B2B software, have the potential to surpass SaaS in market size. This is because AI Agents can not only provide software services like SaaS but also achieve automated operations through AI technology, further enhancing efficiency and reducing costs.

2. LLM Technology Lays the Foundation for the Explosion of Vertical AI Agents

Senior investors at YC compare the emergence of LLM technology to the introduction of XML HTTP request functionality in browsers in 2004, believing that both represent new computing paradigms that bring fundamental changes to software development. The XML HTTP request functionality gave rise to Ajax technology, enabling developers to build rich internet applications like Google Maps and Gmail, whose success propelled the booming SaaS industry.

• XML HTTP Request Functionality: Allows web pages to exchange data with servers without reloading the entire page, resulting in a smoother user experience.
• Ajax Technology: Utilizes XML HTTP request functionality to achieve asynchronous updates of web pages, enhancing user experience.

LLM (Large Language Model) technology also provides new possibilities for software development, combining software with human operations to create more powerful vertical AI Agents that can replace traditional SaaS software and manual operations.

• LLM Technology: Capable of understanding and generating human language, it can be used to build chatbots, automatically generate text, translate, and other applications.

3. Why Did Big Companies Miss Out on B2B SaaS?

The main reason big companies missed the B2B SaaS market is that it is highly fragmented, with each vertical requiring deep expertise and attention to specific issues. Large companies tend to focus on a few large markets rather than spreading their efforts across numerous niche areas For example, Gusto is a SaaS company focused on payroll management, and its success is attributed to its deep understanding of the various details and regulations in the payroll management field. For giants like Google, developing a product similar to Gusto would require a significant investment of time and resources to learn and understand the knowledge of payroll management, which is not cost-effective for them.

4. How will AI Agents impact the personnel structure of enterprises?

The application of LLM will change the hiring model of startups, and in the future, companies may only need fewer employees to achieve rapid growth. In the past, startups typically expanded their team size as their business grew, but LLM can help companies automate processes and reduce reliance on human labor.

For example, Triplebyte is a company that utilizes AI technology for software engineer recruitment. The software they developed can automatically screen resumes, conduct technical tests, and perform initial interviews, significantly reducing the workload of recruiters.

5. What is the market potential of vertical AI Agents?

The market size of vertical AI Agents will be ten times that of SaaS, as they can not only replace existing SaaS software but also replace a large amount of manual operations. Traditional SaaS software still requires human intervention to complete many workflows, while vertical AI Agents can combine software and manual operations to achieve higher efficiency and lower costs.

For example, Momentic is a company that uses AI technology for QA testing. Their AI Agent can automatically execute test cases and generate test reports, completely replacing traditional QA teams.

6. Application cases of vertical AI Agents

During the discussion, four senior investors from YC listed several examples of vertical AI Agent companies. Here are a few representative cases we selected:

• Outset: Utilizes LLM technology to improve the field of surveys and questionnaires. Traditional survey and questionnaire software requires manual design of questions, data collection, and result analysis, while Outset's AI Agent can automatically complete these tasks and adjust questions and answers in real-time based on user feedback, thereby improving the efficiency and accuracy of surveys.
• Momentic: Utilizes AI technology for QA testing, replacing traditional QA teams. Traditional QA testing requires manual writing of test cases, executing tests, and analyzing results, while Momentic's AI Agent can automatically complete these tasks and adjust test cases based on changes in the software's code and functionality, thereby improving testing efficiency and coverage.
• Powerhelp: Develops AI customer support agents that can handle complex customer support workflows, replacing traditional customer support teams Traditional customer support requires manual phone answering, email responses, and problem-solving, while Powerhelp's AI Agent can automate these tasks and provide personalized solutions based on user inquiries and historical records, thereby improving customer satisfaction and efficiency.
• Salient: Utilizing AI voice calling technology to automate debt collection in the auto loan sector. Traditional collection work requires manual dialing, communication with borrowers, and recording collection results, while Salient's AI Agent can automate these tasks and adjust collection strategies based on the borrower's situation and repayment ability, thus improving collection efficiency and success rates.

7. Development Trends of AI Voice Calling Technology

AI voice calling technology has developed rapidly in recent years. With advancements in AI voice synthesis technology and natural language processing technology, AI voice calling can be used in more complex scenarios, such as debt collection, customer service, marketing, etc.

• AI Voice Synthesis Technology: Can convert text into natural and fluent speech, allowing the AI Agent to converse with users like a real person.
• Natural Language Processing Technology: Enables the AI Agent to understand user intentions and emotions and respond accordingly based on user inquiries and feedback.

8. How to Choose the Right AI Agent Startup Direction?

Jared suggests that founders looking to start an AI Agent company should seek out tedious and highly repetitive administrative tasks. These tasks typically require a large amount of manpower and are easily replaceable by AI technology.

For example, the article mentions Sweet spot company, which recognized the presence of a large amount of repetitive work in the government contract bidding process, and thus developed an AI agent to help companies automate these tasks