You’ve overseen a growing portfolio of SaaS companies at saas.group. What is fundamentally changing in the SaaS landscape right now?
One of the biggest shifts is that we are seeing software move from being a system of record to becoming a system of action. Historically, most SaaS tools were there to organise information and support decision-making, the actual work still sat with the human. Today software is starting to take on more of that work directly. Instead of just surfacing insights or structuring workflows, AI-enabled products can increasingly execute tasks end-to-end. That’s a very different value proposition.
It changes everything from product design to pricing to market size. When software starts doing work instead of just supporting it, the ceiling for growth increases massively. We are no longer just competing for software budgets but also competing for labour budgets. That expands the total addressable market dramatically, but it also raises the bar for what “good software” looks like.
SaaS valuations have recently dropped significantly. Why do you think the market is struggling to price these businesses right now?
Investors are still applying old frameworks to a new reality. Classic SaaS multiples were based on predictable recurring revenue, high gross margins, and relatively stable cost structures. AI breaks some of those assumptions, especially around cost, where inference and compute introduce variability.
At the same time, AI-native companies may grow faster but have less defensibility early on. So you get this mismatch: traditional SaaS looks slower, AI looks riskier, and neither fits neatly into existing valuation models.
There’s a lot of talk about “the death of SaaS.” Do you buy into that narrative?
No, but I do think “lazy SaaS” is dead. If your product is just a thin layer of features, you should be worried. But if you’ve spent years building workflows, integrations, trust, compliance, and reliability, that remains incredibly valuable. In fact, I think we will see a wave of customers returning to mature, well-built products after experimenting with quick AI tools that don’t hold up in production environments.
The sector is certainly evolving and we shouldn’t expect SaaS companies of the future to look like the past. I believe that the companies that adapt effectively amidst the AI revolution will be bigger, more impactful, and more valuable than anything we’ve seen before. But the transition period will be messy, and not everyone will make it.
Can ‘legacy’ SaaS companies compete against AI-Native companies?
Mid-market SaaS companies are often dismissed as legacy tools, but I would argue that this is one of the biggest misconceptions in the market right now, and they are actually best positioned for AI transformation?
These SaaS companies already have three crucial things AI-native startups are still trying to build: customers, revenue, and domain expertise. AI transformation isn’t just about building new products, it’s about embedding intelligence into real workflows that already exist at scale. In many cases, these companies also sit on years of structured and unstructured customer data. That becomes a natural foundation for building AI features that are actually useful and differentiated.
So while startups get a lot of attention, the real AI transformation is often happening inside these “boring” SaaS businesses, because they have something to transform. These aren’t small feature updates. They’re strategic shifts in how the product delivers value, and we’re seeing this play out across multiple companies. Take AddSearch – they have pivoted from a traditional website search product to an AI-powered answer engine. Instead of just returning links, they now generate direct answers, which fundamentally changes the user experience and has driven meaningful growth. Keyword.com recognised early that search itself is changing. They launched a product to track brand visibility across AI platforms like ChatGPT, Perplexity, and Gemini. That repositioning opened up an entirely new growth vector.
With Prerender.io, the shift is even more structural. Originally, they helped JavaScript-heavy sites get indexed by traditional search engines. Now, as AI crawlers increasingly shape how content is discovered, their infrastructure is becoming critical for AI visibility as well. They’re evolving into a platform that ensures discoverability across both search engines and AI systems, while already operating at massive scale, serving billions of pages.
How are cost structures changing for SaaS businesses with AI?
This is one of the most underestimated shifts. Traditional SaaS had very predictable cost structures – mostly fixed costs, and high margins, but with the boom of AI, we are seeing variable costs tied to usage. That means margins can compress if founders are not careful, and also requires pricing to evolve, as you can’t charge a flat fee if your costs scale with usage.
Companies that figure out how to balance performance, cost, and pricing will have a big advantage.
At saas.group, you focus on acquiring SaaS companies with strong product-market fit. Has AI changed your acquisition strategy?
It has reinforced our core thesis more than anything. We look for businesses that have already done the hard work building robust products, strong customer relationships, and defensible positions. AI can amplify those strengths, but it can’t replace them, which is why we are looking to acquire a product that already has depth and then working with founders to layer AI on top to unlock new growth. AI native startups move faster and can rethink everything from first principles, but incumbents have distribution, data, and customer trust.
How should valuations evolve in this new environment?
For a long time, SaaS benefited from assumptions such as high multiples on ARR, heavy adjustments for stock-based compensation, and a willingness to prioritise growth over almost everything else.
That is now being replaced by a much more grounded framework. Investors are increasingly looking at real profitability, on a GAAP basis, and asking harder questions about cost structure, for example around sales and marketing efficiency, and now AI-related compute costs as well.
At the same time, AI is introducing new variables. Revenue may be less predictable if it’s usage-based, and margins can be more dynamic because of inference costs, meaning you can’t rely on simple rules of thumb anymore.
Valuation is becoming less about applying a multiple and more about understanding the underlying business, with a focus on true earnings quality, defensibility and efficiency.
What advice would you give founders building SaaS companies today?
This is a tougher environment for founders, but also a more exciting one. The bar is higher, and so is the upside. The old playbook of scaling sales and marketing spend ahead of revenue is under pressure. Capital is more expensive, and investors are looking closely at efficiency.
It’s no longer enough to show growth, you need to show that your business actually works as a business. That means real margins, disciplined spending, and a clear path to GAAP profitability.
At the same time, AI is raising expectations on the product side. So the challenge is doing both: building something meaningfully better while also running a tighter, more efficient company.
The founders who win will be the ones who combine product ambition with financial discipline.
Tim Schumacher is an entrepreneur and investor focused on building and scaling purpose-driven technology companies. As Co-Founder of saas.group, he is focused on acquiring and growing independent, founder-led SaaS businesses, creating a long-term, founder-friendly alternative to traditional private equity and building a global portfolio of profitable software companies. He is also Founding General Partner of World Fund, Europe’s leading climate tech VC, committed to investing in European tech with significant climate performance potential. Tim’s entrepreneurial career began as the co-founder and long-time CEO of Sedo, the world’s largest domain marketplace, and he also serves as Chairman and lead investor of Eyeo, reflecting his longstanding commitment to entrepreneurship and digital rights.
