TLDR

Large Language Models (LLMs) are changing the game by making data more accessible and actionable. Looking ahead, AI will empower new players to challenge industry giants by creating efficient workflows, developing comprehensive platforms, and customizing sales approaches. Companies like Wiz show the way with their all-in-one solutions and agile strategies. Vertical SaaS companies will thrive by building marketplaces and capitalizing on AI advancements. The next decade will see a wave of new players disrupting traditional markets faster than ever before.

Introduction

In the past decade, companies like Shopify, Toast, Ironclad, Procore, and Mindbody have emerged, built new marketplaces, and solidified their positions within their respective industries.

At the same time, many large vertical markets are encumbered by unstructured data, slow sales cycles, and incumbent forces that are difficult to unseat. LLMs represent a paradigm shift since they can now turn unstructured data into workable information that is quickly and readily accessible and processible for different machine learning algorithms or end-user reviews.

I will focus on what AI will largely mean for the next decade.

In this post, I will describe how AI will shape new emerging players and then discuss strategies for how they will be able to unseat incumbents.

Structuring the Unstructured: Why LLMs will change Enterprise SaaS

In the technology hype cycle for AI, we are clearly at the peak of inflated expectations. Gartner itself has proclaimed that we are at the peak, as more and more business users adopt AI without a clear and specific use case in mind. In personal experience, I have seen this most often with incumbent software solutions that throw a chatbot wrapper on top of their product and hope for the best. Earlier last year, my colleague Zach Abramovitz were so blown away by ChatGPT that he was reconsidering investing in any enterprise software application.

But LLM's power in vertical software really comes at the augmentation and displacement of routinized tasks around unstructured information and its low cost to create them.

Building Better Data Towards Market Leadership

At the application layer, the winners will be those who can take generally applicable models, synthesize traditional workflows, and make that data processable. Data exists in unstructured text and notes for many businesses, such as legal, accounting, and healthcare. (Imagine all the handwritten notes that lawyers write on documents or doctors do on medical charts). What LLMs provide is a means to quickly and easily sort this information to take actionable steps with data transformation and/or place it. This technological shift is a catalyst for disruption, but it will take the companies themselves to exploit this shift to emerge as new incumbents.

For traditional industries that have established software moats, such as in legal, construction, accounting, or healthcare, new AI-forward companies will have to build more robust full-service platforms, connect users to more services, and invest intelligently into a highly scalable GTM motion.

To do so, future market leaders will have to build more quickly, drive more revenue per customer, and continue to invest in their GTM strategy. Utilizing AI for all these purposes will propel new market leaders to unseat incumbents.

Build Horizontally: Nobody Beats the Wiz

For those of you who get the early 90s reference, Kudos. If not, I am concerned I am getting too old.

But Wiz, the Israeli Cyber Security startup, represents a template for the next generation of fast-growing SaaS companies in the coming decade.

At the core of the Wiz solution is a security graph that not only helps identify possible issues that could lead to problems but also correlates all of that information across the different areas that a company is trying to protect, whether that’s the network, identity, secrets, or workloads. While the Wiz may have had the help of a massive funding round in the beginning, the Wiz well-developed product strategy and scalable solutions are now much faster and affordable to build. This is largely because companies are able to scale their operations so much faster. (I have one early stage company that basically built its sales team off of ChatGPT).

Wiz is unique because they built a best-in-class all in one solution that meant their sales team to enter an organization from multiple angles. By targeting specifical to the the different personas they had multiple angles through which they could land and expand.

This strategy is likely to be replicated by newer SaaS players as it will become cheaper and faster to deploy and sales motions can be easily customized.

It will still take world class teams to execute, but these types of companies will be more likely in the coming decade.

Monetize interactions

At the same time, it will be even easier for companies that can use vertical SaaS to marketplaces that will solidify their positions.

First, SaaS companies will be able to quickly contextualize data from users to build marketplaces and to tack on other interactions. As companies are better able to make of their platforms unstructured interactions they will be better equipped and faster to develop moats around their products.

While in years past it took years for companies like Mindbody to build solution for vertical operations that had over 50% market penetration. AI-First companies will entrench themselves faster to lock-in first the vertical efficiencies and then establish themselves as nexus between buyers and sellers in a particular market.

Conclusion

While many incumbents will use the AI revolution to strengthen their positions, the upcoming decade promises the emergence of new players. These newcomers, particularly in traditionally challenging areas for building vertical SaaS solutions, will establish themselves faster than ever before. This shift will be driven by AI technologies, enabling companies to challenge and potentially surpass established industry leaders.

Special Shout out to John Villa at Meridian Street, Naomi Getz at Forum, and Catherine En at Greylock for their work and writing that inspired this piece. Feel free to reach to me to share your thoughts.