The Rise of Vertical AI Agents: A Game Changer for SaaS

Did you know that every company that is a SaaS unicorn could have a vertical AI unicorn equivalent? The landscape of technology is shifting rapidly, and vertical AI agents are at the forefront of this transformation.

Jared is fired up about vertical AI agents

Every three months, the advancements in AI seem to accelerate, and we’re now on the brink of a revolution with vertical AI agents poised to replace entire teams and functions within enterprises. This progression is nothing short of mind-blowing. With the emergence of multiple players in the AI space, competition is thriving, creating a fertile marketplace ecosystem where consumers have choices and founders have opportunities.

The parallels between early SaaS and LLMs

To understand the potential of vertical AI, it’s essential to draw parallels with the Software as a Service (SaaS) boom. Many startup founders, especially the younger ones, often overlook the sheer scale of SaaS. Over the past two decades, Silicon Valley has primarily funded SaaS companies, with over 40% of venture capital dollars flowing into this sector. This has resulted in more than 300 SaaS unicorns, showcasing the massive potential that vertical AI agents could replicate.

The catalyst for the SaaS boom was the introduction of the XML HTTP request in 2004, which allowed for the creation of rich internet applications. This pivotal moment transformed software from a product installed on a desktop to a service accessed via the web. Similarly, we are witnessing a new computing paradigm with large language models (LLMs) that enable fundamentally different applications.

Why didn’t the big companies go into B2B SaaS?

One might wonder why tech giants haven’t dominated the B2B SaaS space. The answer lies in the complexity and specialization required for various verticals. Each B2B SaaS company needs deep domain expertise, which large companies often lack. For instance, why didn’t Google build a competitor to Gusto, a payroll service? The answer is simple: Google doesn’t have the specialized knowledge to navigate the intricate world of payroll regulations.

This specialization has allowed numerous vertical SaaS companies to thrive, as there is no single entity that can cater to every industry’s needs. The early skepticism surrounding SaaS—much like the current hesitance towards LLMs—mirrors the journey of many startups that have successfully carved out their niches.

How employee counts might change

Traditionally, as revenue scales, so does the number of employees. However, with the rise of vertical AI agents, this dynamic may shift dramatically. Startups might find that they can achieve significant growth with fewer employees by leveraging AI to automate repetitive tasks. Imagine a future where a company can operate efficiently with just ten employees, all thanks to the power of AI.

This shift could redefine how startups approach hiring and scaling. Instead of focusing on building large teams, founders may prioritize hiring skilled engineers who can develop and implement AI solutions that streamline operations.

The argument for more vertical AI unicorns

The potential for vertical AI agents is staggering. Every SaaS unicorn could have a vertical AI equivalent that not only replaces existing software but also reduces the need for human labor in various administrative tasks. This means that vertical AI agents could potentially be ten times larger than the SaaS companies they disrupt.

For example, companies like Outset are already leveraging LLMs to enhance survey and qualitative research processes. By automating these tasks, they are not only improving efficiency but also creating a more effective solution for businesses.

Current examples of companies/uses

As we explore the landscape of vertical AI agents, several companies stand out for their innovative approaches:

• Outset: Utilizing LLMs for surveys and qualitative research.
• MCH: An AI agent for QA testing that replaces traditional QA teams.
• Nico: A company automating the recruiting process, eliminating the need for large recruiting teams.

These examples illustrate how vertical AI agents are not just theoretical concepts but are already making significant impacts in various industries.

AI voice calling companies

The voice technology sector is also experiencing rapid growth. Companies like Salient are automating tasks traditionally performed by low-wage workers in call centers, such as debt collection. By leveraging AI, these companies can streamline operations and reduce churn, creating a more efficient workforce.

The advancements in voice technology have made it possible for AI to handle tasks that were once thought to require human interaction. This shift opens up new opportunities for startups to innovate and disrupt traditional industries.

What is the right vertical for you as a founder?

For aspiring founders, the key to success lies in identifying boring, repetitive administrative tasks that can be automated. Many successful vertical AI startups have emerged from founders who have firsthand experience with these tedious processes.

Consider the example of a startup that developed an AI agent to bid on government contracts. The idea stemmed from a founder’s friend who spent hours refreshing a government website for new proposals. By recognizing this inefficiency, the founder was able to create a solution that addresses a real need.

Bolded takeaway: Look for repetitive tasks in your industry that can be automated with AI, and you may just find your next billion-dollar startup idea.

As we move forward, the landscape of vertical AI agents will continue to evolve. What opportunities do you see in your industry that could benefit from automation? Share your thoughts and let’s explore the future of AI together!