Many industries move in cycles. SaaS is no exception.

SaaS companies are not increasing revenue, ARR, or profitability in isolation, but moving together as part of an overall industry trend.

Before investing in SaaS stocks, it’s important to know some of the fundamental factors at play affecting the performance of the industry.

To explain what is going on, I will be using example charts (not representative of any particular company or group of companies) for illustrative purposes.

The above example chart is the key explanation for what has been going on from 2020 to present. It has 3 distinct stages, which we have transitioned through.

Stage 1 is the ZIRP boom (zero interest rate policy)

Stage 2 is the efficiency hangover post rate increases

Stage 3 is the AI automation era

We have currently exited the efficiency hangover era and have transitioned into the AI automation era.

First, let’s take a look at Stage 1.

Stage 1 of the Zero-Interest Rate Policy SaaS Boom is characterized by these key components:

The combination of these factors meant businesses increased seats, signed more deals, and thereby increased the amount of revenue every B2B SaaS company received. This resulted in a boom for SaaS stocks.

Because many deals signed are multi-year, and many of the employees hired are a structural boost, the revenue gains from this period increased revenue growth for the following 3 years. IE, the deals signed in 2020 and 2021 resulted in revenue growth for the years 2021 through 2024.

Why is this? It’s because there is a lag in the revenue mix. New cohorts and new growth only represent a % of the total book. This means as time passes, the net new ARR becomes a bigger % of the book. See chart below that illustrates this concept in a fictitious example company, which we will come back to again later.

While Stage 1 represented the bulk of where net new ARR came from for SaaS stocks that drove revenue growth from 2020 through 2024, once rate hikes started coming into play in 2022, the forward looking picture got considerably worse.

Rate hikes slowed everything down, including new deal flow for SaaS companies. However, this did not immediately impact their revenue growth, as the record net new ARR from ZIRP era started becoming a bigger % of the book and those customers naturally spend more as they adopt more tools while maturing their product adoption.

Again, we return to this chart.

As we can see in Stage 2, bookings growth is decelerating quickly, but there is a lag in recognition for revenue growth. And the severity of revenue decline is also minimized because new bookings are a smaller percent of the total mix.

Stage 2 in this SaaS lifecycle is defined by:

During this period, it became hard for SaaS businesses to get new sales, with recession fears peaking as the federal funds rate spiked quickly. As a result, SaaS businesses heavily discounted or made special exceptions to get new deals done. These deals often last for multiple years. As a result, contracts signed in 2022-2023 have very favorable terms for customers that last into 2025-2026.

This also means that when things improve in 2026, the results will be less immediately noticeable, because the old contracts signed still have favorable client terms in effect, and although new businesses are ok signing more expensive terms as a result of the new business environment, it isn’t visible yet in top-line numbers.

We have now entered a new stage for SaaS, which is the AI automation era. AI tools are becoming useful with demonstrable ROI in many capacities. Early examples of this clearly exist in areas touching the implementation of coding, such as with Gitlab, J Frog, Data Dog, and more.

Businesses are now seeking ways to implement AI and automation to drive real ROI.

This is driving new deal flow to platforms that offer AI automation solutions. It is becoming visible across the spectrum as B2B SaaS businesses such as Gitlab and UiPath are reporting record net new ARR or significant ARR acceleration.

As we return to the above chart, an immediate increase in record net new ARR does not mean revenue growth stops decelerating. There is a hangover from Stage 2. This is because it takes time for net new ARR to stack and re-accelerate overall growth.

As shown above, in the example contract mix, most contracts are still from the 2022-2024 era with less favorable terms. Once those contracts become renewed at more attractive valuations, we will see those plus new customers accelerate growth in the B2B SaaS industry.

This leads to an interesting dynamic in the market.

The market currently sees:

Those two things appear at odds, but as we went over, it is completely natural as the previous stage has hangover affects that take a year or two until the new dynamics become a larger part of the customer and bookings mix.

Many SaaS businesses are getting record net new ARR because their products are becoming more valuable to everyone as customer’s needs increase from AI utilization. However, not all of these businesses are fully pricing the benefit of AI into their product as they switch from seat based pricing to consumption based pricing.

This creates an additional lag effect. Businesses right now are getting somewhat of a “free ride” on AI tools during this transition in pricing models.

The software industry went through a similar change over a decade ago when it went from a product license model to a subscription model. Customers previously were able to buy a product once and use it as long as they wanted. They often did not upgrade for many years at a time, unless new versions had significant must have improvements.

When software companies realized that they could instead utilize the cloud to create a product that was instead sold monthly, instead of once, and deliver constant updates to that product, they could force continued purchases of the product. At first, this would hit their revenue, as new sales would be recorded monthly, earning them say $25 a month, instead of a one time $300 sale. But, after a year or two, this model generated more revenue for software businesses.

There is no better display of this effect than Adobe in action. See their revenue below.

Adobe switched from a license based product to a subscription product in 2012. However, notice that revenue did not hockey stick until 2-3 years later in 2015. This is because of the standard 2-3 year lag in future bookings, as it takes time for users to eventually switch to the new pricing model and product and it took time for new cohorts to stack and age in.

We are currently undergoing that same transition for SaaS in the AI automation era. In this case, the transition is going from seat based pricing, to utility or consumption based pricing.

If we look at Gitlab for instance, they released their Duo Agent Platform which has agents to automate processes across the code infrastructure and deployment layer.

Right now, Gitlab is offering credits with seat based pricing to introduce the idea of consumption based model. They then charge overage charges for going beyond the credit limit. Businesses can also sign-up for credits at a discount rather than get overage charges. This is a bridge to get user adoption to the new product and eventually get them on consumption based models.

The way SaaS will benefit from AI is through consumption. This is because AI is naturally a consumption based product. AI is capex heavy and uses tokens to generate automations, and those tokens will be taxed by SaaS implementations, thus making money from consumption. This is the evolution of SaaS.

However, not all SaaS will benefit. The businesses that are able to effectively offer additional utility from AI implementations, or from cloud consumption as a result of AI, will better take a cut of the efficiencies offered.

There are some natural mechanics that will play out as we enter the next stage for this SaaS transition:

My personal preference is to avoid businesses that have a weak tax or weak overall % of revenue that can come from AI consumption, and focus on investments in businesses that are naturally advantaged to implement AI solutions or benefit from increased cloud usage from AI.

At the same time, we must recognize some SaaS businesses have a weak moat and may legitimately be at risk of new competition, although it may take some years for that competition to materialize.

If the mid 2010s transition from license based to subscription based model repeats again with a transition to an AI consumption model, there is massive upside potential in SaaS, which is something seemingly not factored into the SaaS market selloff.

Which SaaS names do you think are best positioned for the consumption transition? Drop a comment below.

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