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The Guest Chair is where we share what we learn from inviting industry specialists into Eleven’s weekly meetings – practitioners with deep, current context on what matters to founders and investors: market dynamics, emerging trends, and sector shifts. These are people who see it up close every day.
Each piece distills the takeaways we’d want every founder in our portfolio to hear – clear insights, practical implications, and the questions worth asking next.
Our first guest is Michael Ivanov, Partner at Carlsquare. He has spent 15+ years advising growth-stage technology companies on M&A and strategic transactions across Europe, and his work on these deals gives him a ground-level view of how buyer behaviour, valuations, and market structure are shifting in real time. Here is what he is seeing right now.
1. Where We Are in the M&A Cycle
The tech M&A market isn’t going through a temporary dip. It’s going through a structural reconfiguration. Multiple compression, deep uncertainty, and AI disruption are happening simultaneously, and each amplifies the other.
Michael uses the term “Peak Fear” to describe the current moment: the introduction of advanced AI models turned previously attractive software assets into question marks almost overnight. Buyers who were ready to write checks paused. Sellers who assumed stable multiples found the ground shifting beneath them.
It’s worth being precise about why this feels different from previous disruptions. The shift to cloud computing in the 2010s was significant, but it was primarily a change in how software was delivered and monetised, though the underlying products largely remained intact. What AI introduces is something more fundamental: a change to the product itself. Intelligence is being woven into the core of how software works, what it can do, and what users expect from it. That raises questions not just about delivery, but about whether entire product categories will exist in their current form five years from now.
That said, this isn’t a reason for pessimism. History suggests that waves of technological disruption create more value than they destroy, they just redistribute it. The companies that adapted earliest to cloud didn’t just survive; many of them defined the next era. The same logic applies here, but the speed and depth of the shift demand a more honest assessment of where your product sits.
The broad market expectation is that H2 2026 will be the activation point for deals currently on the sidelines. But the downside risk hasn’t passed, and the market is watching closely whether major players can translate AI investment into actual earnings, retention, and upselling.
The key is results, not narrative.
2. The Insourcing Threat
Many founders haven’t fully reckoned with a quiet shift in their competitive landscape: their own customers are starting to build in-house.
Tech-savvy companies that used to spend hundreds of thousands on SaaS are now redirecting that budget toward internal engineering. AI-powered coding tools have made the “build” option meaningfully more accessible. Internal IT teams, armed with better tooling than they’ve ever had, have become a silent competitor, eroding sales pipelines and making buyers nervous.
"The internal build option is now genuinely compelling. The tooling has changed the calculus."
Michael Ivanov
Partner at Carlsquare
The question every SaaS founder should ask honestly: If our primary buyer type decided to build what we do, how hard would it actually be today?
If the answer is “not that hard,” that’s a positioning problem, and it needs fixing before any sale process begins. The antidote is depth: proprietary data, workflow complexity, domain expertise, regulatory knowledge – the things that can’t be replicated by a capable engineer with access to Cursor and a weekend.
3. AI and Value Accrual: Where the Money Is Going
One of the most important structural questions in tech right now is where value will accrue in an AI-native world. Michael’s view is clear: infrastructure layers (hosting, compute, model providers) will capture a disproportionate share.
But it’s important to be precise about the application layer, because writing it off entirely would be a mistake. What’s happening is more nuanced than “applications don’t matter.” The distinction between “intelligence” and “application” is blurring. Intelligence is increasingly embedded within applications: think systems of work that learn, adapt, and automate rather than simply display data. The application layer isn’t disappearing; it’s being redefined. The thin, commoditised apps that sit on top of infrastructure without adding proprietary intelligence or workflow depth: those are exposed. Applications that embed intelligence into complex, domain-specific workflows are a different story entirely.
One practical implication Michael highlighted: companies don’t always need massive LLMs for basic tasks. The trend is toward running small, open-source models internally to handle 80–90% of specific workflow automations efficiently and cheaply. Buyers expect companies to leverage this to make R&D and go-to-market significantly more productive, driving growth without proportional OpEx increases.
For AI-native companies, COGS (Cost of Goods Sold) is the critical question from day one. Hosting plus intelligence creates a cost layer that fundamentally changes unit economics compared to traditional SaaS. It’s one of the first things a serious buyer will dig into.
4. What SaaS Buyers Are Actually Looking At
❗️ Retention is the single most important exit-readiness metric. It signals resilience above growth rate, logo count, or TAM. The last 18 months of gross and net retention will be examined in granular detail in any serious process.
"Loss-making businesses are very hard to sell right now. The question buyers ask isn't "is it profitable?" but "is there a credible path to break-even?""
Michael Ivanov
Partner at Carlsquare
For companies that can’t demonstrate retention strength, there’s an alternative route, but it’s harder: show clear synergies with a strategic buyer around AI automation. The framing that tends to land:
“We help you move faster so you don’t fall behind competitors.”
As Ben Thompson has argued extensively in Stratechery, the companies that become acquisition targets in shifting markets are usually the ones solving an urgency problem for the buyer, not just offering incremental improvement, but addressing a gap the buyer can’t afford to leave open.
5. Strategic Buyers Have Changed. PE Is Now the Engine.
The landscape of who actually buys technology companies has shifted materially.
Large strategic acquirers have become far more selective. The mega-checks into broad software categories have largely stopped. Historically, buyers like Oracle and Salesforce provided massive liquidity through multi-billion dollar acquisitions. Now, they’ve redirected capital almost exclusively toward building internal AI infrastructure or making selective acqui-hires for AI talent.
Public companies also face a structural constraint that gets underappreciated: stock market punishment for short-term profitability drops. Michael cited one case where a NYSE-listed buyer had to walk away from a deal after their stock fell 55% in 30 days, making equity financing impossible. When your acquisition currency loses half its value mid-process, even the best strategic rationale can’t save the deal.
Private equity has stepped in as the primary driver of technology M&A. The thesis playing out:
✔️ Public software multiples decline
✔️ PE acquires undervalued public companies
✔️ Buy-and-build consolidates fragmented sectors
✔️ Consolidation happens between PE-backed assets
Much of the expected H2 wave will likely be equity-for-equity, as valuation gaps narrow and AI disruption urgency makes founders more open to non-cash exits.
One more signal worth noting: if private funding dries up, IPOs become a path of last resort, not a growth milestone. As Hamilton Helmer might put it, the “power” in an IPO comes from optionality; when it becomes a necessity, the dynamics shift against the founder entirely.
6. Why Deals Fall Apart, and What Saves Them
Most late-stage deals don’t fail because of a bad process. They fail because the company’s performance slips during the process.
A slow quarter mid-deal can kill something that was otherwise well-structured. The reverse is also true: a co-founder departure or a key customer churning can be survived if the numbers hold. If a company consistently beats its budget, most other problems become solvable.
This sounds straightforward, but it’s brutally hard in practice.
"Running a company and running a sale process simultaneously is one of the most draining things a founder can do."
Michael Ivanov
Partner at Carlsquare
The temptation is to let the operator’s foot off the gas while the dealmakers take over. Michael’s observation is that the founders who close successfully are the ones who refuse to do this, treating the process as a parallel workstream rather than a distraction from the core business.
What’s making everything harder right now:
✔️ CAC is rising consistently
✔️ Multi-year commitments are harder to secure
✔️ Sales cycles are getting longer
Together, these raise the bar for what buyers consider “good”, and make maintaining momentum during a process significantly more difficult. The practical takeaway: if you’re considering a process in the next 12–18 months, start building the operational muscle for it now. Get your reporting clean, your retention narrative tight, and your team aligned on the expectation that business performance is non-negotiable during the deal.
7. Sectors with Genuine Upside
Not everything is under pressure. Michael shared where he sees structural opportunity:
✔️ Tech-Enabled Services is a standout category. Not pure labour shops: those will struggle as automation replaces headcount leverage. But companies that combine deep domain expertise with technology to deliver outcomes? Every global industry needs hands-on help executing AI transformation, and the firms that can do this at scale will command premium multiples. The key differentiator: a genuine technology layer that makes the service more scalable, not just a consultancy that happens to mention AI in its pitch deck.
✔️ Defence tech is experiencing a structural spending shift in Europe, with budgets expected to double or triple, driven by micro-warfare, cyber, drones, and satellite capabilities.
✔️ Industrial tech (robotisation, digital twins, IoT convergence) is accelerating, with China’s lead creating urgency for European players to invest and acquire.
✔️ Cybersecurity continues to see growing structural demand as AI expands the attack surface.
✔️ Life sciences is predicted to grow significantly as AI integration accelerates drug discovery, diagnostics, and clinical operations.
✔️ SaaS remains a fundamentally strong category for capital deployment, the recurring revenue model hasn’t lost its appeal, and the best SaaS companies are more efficient and more defensible than ever. But selectivity matters more than it has in a decade. The spread between the best and the rest is widening. Price discipline, retention quality, and a clear answer to the “why can’t AI replace this?” question now separate the investable from the uninvestable.
❓What’s genuinely uncertain: pure-play horizontal software without a service layer, a defensible vertical moat, or a strong answer to the insourcing question. The exit path for these companies is the hardest to map right now.
8. What This Means If You're Building Right Now
The market Michael describes rewards a specific kind of company, and it’s not what most founders are currently optimising for.
1️⃣ Retention is your most important number. Not growth, not ARR. Retention is the signal buyers use to assess whether your product is defensible in an AI-transformed world. If customers are staying and expanding, it means you’re embedded. If they’re churning, no narrative fixes that.
2️⃣ You need a credible path to profitability. That doesn’t mean you need to be profitable today. But you need to be able to show exactly how and when you get there, and the assumptions need to hold up under scrutiny.
3️⃣ “Nice to have” is no longer a viable position. You need to be embedded deeply enough that replacing you creates real operational pain, not just friction on one workflow. If a customer could build your product in-house in six months, a buyer will think the same thing.
4️⃣ Hybrid models are winning. The most defensible companies right now combine technology with domain expertise, services, or operational complexity that can’t be easily replicated. If your moat is the software alone, it’s worth stress-testing whether that’s still enough.
5️⃣ Know who would buy you – and build toward it. Not as an exit obsession, but as a strategic lens. Understanding your likely acquirer sharpens how you think about partnerships, which markets you prioritise, and what capabilities you build. The founders who exit well usually saw it coming years before it happened.
One Broader Perspective Worth Holding on To
Michael, speaking as someone trained in economics, sees AI as potentially the most significant positive force available to address deep structural challenges in the global economy, from unsustainable debt levels to productivity stagnation. The disruption we’re seeing in M&A isn’t just a market cycle. It’s part of a larger recalibration, and the companies being built today will shape how that recalibration plays out. There’s genuine reason for optimism, but it belongs to the builders who are clear-eyed about the transition, not the ones waiting for the old rules to come back.
The fundamentals don’t change with the cycle. The companies that will be acquired, on good terms and by the right buyers, are the ones being built with that outcome in mind from day one.
