From Rule of 40 to Rule of 55: How GenAI is disrupting SaaS valuations

Generative Artificial Intelligence ("GenAI") is causing structural changes to SaaS companies that will have a profound impact on growth and margins, forcing investors to rethink how they are valued. The bar for performance will be raised so dramatically that over the long term the Rule of 40 that has governed the SaaS industry will be replaced by the Rule of 55.

The Rule of 40 states that a software company's combined revenue growth rate and profit margin should equal or exceed 40%. It is often calculated based on operating cash-flow margin to reflect a more accurate cash-based vision. It is calculated as:

Revenue Growth Rate (%) + Profit Margin (%) >= 40% or,

Revenue Growth Rate (%) + Operating Cash-Flow Margin (%) >=40%

The Rule of 40 helps evaluate whether a SaaS company is reaching the right balance between investing in growth or achieving profitability. SaaS companies that outperform the Rule of 40 tend to have higher valuations, and the Rule of 40 marks a valuation "frontier". This frontier should change as a result of GenAI.

Over the past decade, SaaS companies have given rise to some of the most resilient companies, becoming an attractive target for both venture capital and private equity. Going forward, only the SaaS companies that have fully leveraged the potential of GenAI will emerge from this crowd.

GenAI has primarily been analyzed as a means for productivity gains. But its effects are much more comprehensive, driving a redefinition of almost every factor that determines a SaaS company’s growth perspectives, gross margin and EBITDA.

It is essential that investors and founders alike grasp the nature of this New Normal. Founders must ensure they are maximizing every advantage of GenAI. Investors must be able to look deeply into a company’s metrics to understand how well it has deployed GenAI – and where potential weaknesses might lurk – to correctly assess the valuation.

?In this article, we break down the implications of this transformation and focus on the different components of the income and balance sheet to see how GenAI will contribute to superior performance.

?Advanced Growth Intelligence

For some context behind this analysis, our firm has developed a new analytical framework for assessing the business models of Disruptive Technology companies called Advanced Growth Intelligence (AGI). The analysis validates both the intrinsic value of the business as well as its resilience to larger macro trends that can disrupt existing models and assumptions – such as GenAI (See our Deep Dive into the GenAI stack here).

This detailed and rigorous study of these models feeds into an assessment of four key pillars: Quality of Margins; Quality of Revenue; Quality of Growth; and Balance Sheet Strength. At its heart, AGI recognizes that any assessment must fundamentally help build a conviction on a business's .

With that in mind, let’s go back to the Rule of 40 as it looks today. For the 136 SaaS public companies that our firm tracks, the current Rule of 40 is actually 31% as shown in the table below.

When we break out the 19 SaaS companies that we consider to be the best performers (implied ARR valuation multiples above 10x), that number jumps to 52%. These top performers mainly differ from other SaaS companies in having a higher gross margin of +2pp and a leaner G&A structure.

Here’s how we see GenAI transforming performance for SaaS companies:

Now let's dive into how we get there.

• Revenue

In the short term, GenAI integration will have a limited impact on SaaS revenues, but it will unleash stronger growth by 2025 and beyond.

To understand how SaaS companies will capture value with GenAI, let’s look at Adobe. The company has deployed two classic approaches: Created a new feature with GenAI Adobe; created a new product with Firefly.

AI features integration is strategic in the short term because it defends SaaS companies against the risk of obsolescence, but it doesn’t immediately drive revenue gains. In fact, it’s likely that the industry will refrain from implementing any price increases in existing products even as they include some GenAI functionalities. Such was the case with Adobe with its Adobe reader features. Other companies are launching new GenAI powered products - Firefly in the case of Adobe - that allow an immediate price uptick as the product is new.

But in the next months, SaaS toplines will be boosted by price increases that are justified by the additional value provided to customers. In the long term, such shifts could enable more transformative pricing structure change – from a pay-per-user to a pay-per-use model.

In the long run, the widespread integration of GenAI will unleash stronger revenue growth, from both new customers through new GenAI product revenue and the ability to upsell existing customers to additional features.

?Result: +2pp gain in YoY revenue growth.

?

• Gross Margin

One of the most complex areas to measure is GenAI’s impact on costs. That’s because in the short term, companies will need to spend to fully integrate and deploy this technology.

For instance, GenAI implementation could increase Cost of Sales due to additional spending on inference, engineering, and MLOps.

The choice of model is critical for SaaS applications. The wrong model could significantly hamper margins. Model selection requires a deep understanding & quantification of the inferences at stake to make the right decision. (See again our GenAI tech stack breakdown). The good news is that latency and cost continue to improve and OpenAI just announced that GPT-4o would be 2x the speed of GPT-4 turbo, and what be half the cost.

We intuit that in a first time, GenAI will be neutral to gross margins as SaaS companies are unable at first to offset their inference costs to customers as path to adoption is still ongoing.

However, this will be somewhat offset by reduced labor costs at call centers as more functions are automated. Klarna has notoriously benefited from this effect by launching an AI assistant in early 2024 that already handles 2/3 of customer service chats – a load that would have required 700 full-time agents. The result has been impressive reductions in repeat inquiries and resolution time.

Similar gains could occur at professional services level.

Result: -5pp loss in margins in the short-term; +1pp -+2pp annual gain post-2025.

• R&D

We concur with the conventional wisdom that expects significant productivity gains, especially for coding. However, this will be partly offset by higher R&D spending as teams need to develop GenAI capabilities.

The current GenAI tech stack enables developers to automate or accelerate coding operations. Coding assistants will drive up to 30% productivity gains for entry-level scripts creation. They will also produce gains by understanding existing code, improving the ability to analyze and address the tech debt created by legacy infrastructure. In addition, MLOps will bring new efficiencies to fetching data, engineering features, training, testing, storing, and model deployment.

The challenge is that to efficiently implement these tools, the R&D team will need to develop GenAI capabilities. Acquiring those skills takes money. On a recent earnings call, for example, Snowflake warned investors that it expects to spend heavily to recruit the right R&D talent. And Adobe reported that its R&D costs had increased to 18% of revenue in FY23, up from 16% in FY21.

SaaS companies and investors need to assess the impact of how GenAI is being used to address diverse tasks, such as using a coding assistant such as Microsoft Copilot for developers, for building new features, or for automating maintenance operations.

Put these pieces together, and we believe that SaaS companies can make 30% cost improvements on up to 60% of their R&D structure.

Result: +5pp annually long term.

• Sales, Marketing, and Admin

SaaS companies will gain efficiency in sales, marketing, and administration by using GenAI to automate content production, perform repetitive tasks, and enhance the productivity of sales reps.

GenAI implementation won’t have much impact on some core expenses, such as rent, insurance, C-level wages, and critical core sales operations. However, all content-related production tasks will be accelerated, resulting in more productivity and less labor expenses. SaaS companies can potentially use GenAI to drive up to 30% improvements in their G&A structure - about 2% of G&A costs.

For instance, IBM announced in May 2023 plans to replace nearly 8,000 jobs with AI. Non-customer-facing roles are targeted by this plan, specifically in the HR and accounting sectors. IBM aims to replace this workforce with a few dozen AI-based roles to help develop and maintain these systems.

Sales employees will also take advantage of the automation of repetitive tasks to increase their sales time. SaaS companies can make up to 30% improvements on 50% of their S&M structure through GenAI – about 5% of S&M costs.

Combined, S&M and G&A are where most of the productivity gains should occur at first.

Result: +7 pp annually long term

• Other potential impacts to consider

The GenAI impact on the balance sheet is still coming into focus. This remains an area of ongoing study for us. As SaaS companies add GenAI capabilities and scale their offering, there is no guarantee that customers will adopt them or that the company will be able to properly monetize them. That means the costs here are “known unknowns.”

What is known is that SaaS companies will face additional CAPEX/OPEX spending to implement GenAI solutions internally and for their products. The GenAI disruption can transform the traditional asset-light model of SaaS companies towards more CAPEX-intensive practices, especially for specific end-to-end models that require additional hardware investment.

CAPEX implementation costs could include additional investments required to develop and set up applicable frameworks to the company’s use cases; costs related to developing or licensing proprietary datasets; and costs related to infrastructure or hardware improvements required for GenAI implementation.

OPEX implementation costs could include such items as recurring data aggregators that will be purchased on a recurring basis.

Conclusion

Consolidating GenAI’s impact across all of these components, we project a +15% gain for SaaS companies, with roughly 2% arising from additional growth and + 13% of EBITDA improvement. The Rule of 55 will become the new standard to measure top performers.

Reaching those heights starts with getting a granular view of how these different elements feed into margins and revenue. This new GenAI world is here. Leaders and investors need to immediately start to understand how they need to shift their thinking about valuations and their playbooks for achieving these new benchmarks.