TLDR: French insurtech Alan raised €480 million in a round that the Financial Times first called one of the largest by a “non-AI” company. That mislabeling of Alan points to a more fundamental error: how markets keep misjudging which companies are making the transition to the Agentic Era. In the Orchestration Economics framework, Alan serves as a case study of a company making the crossing. Alan is a disruptor that owns its context, workflow, and the verifier that decides whether its agents are right. That last asset is the most decisive and least-watched test of who crosses the agentic threshold and who is displaced. In Alan's case, the binding constraint may ultimately come from capital rather than technology.
When the Financial Times described French insurtech Alan’s latest funding round as Europe’s biggest “non-AI” fundraising of the year, it mislabeled the company in an interesting way. In this case, the miscategorization of the unicorn is not just about marketing buzzwords.
On June 25, the paper broke a story that offered a counter-narrative to a venture world that seemed interested in nothing but AI: “Prosus leads €480 million investment in French health tech startup Alan,” read the headline over a subhead noting that the “Paris-based group raises one of Europe’s largest non-AI start-up rounds this year.” The FT later swapped that subhead for the more anodyne “The deal values the 10-year-old Paris-based group at €5.5bn.”
The difference between the two subheads is worth examining. But not just to question the FT’s editorial judgment.
Rather, the miscategorization is entirely understandable because it is a microcosm of the larger struggle playing out across markets as they try to price the impact of generative and agentic AI on legacy software. This is most evident in the binary debate of software versus AI. The market’s reflex may be directionally correct for some categories, but it is analytically lazy. Alan is an example of why the binary framing is wrong. It is proof that some existing companies can make the crossing to the Agentic Era.
As I wrote in Orchestration Economics when discussing the February 2026 SaaSpocalypse, this is “a confused, simplistic attempt to price a structural shift in where control, coordination, and value capture reside”. This is not the death of SaaS. It is the Software Sorting,” a re-ranking of where value will sit “when autonomous agents become the primary actors inside enterprises.”
The harder question for investors is how to tell which companies can make the crossing and which can’t. That question reaches well beyond software.
In Orchestration Economics, I reserve a specific label for a company that has secured the structural position to capture value in this new paradigm: AGNT. It is an end state, not a badge handed out for momentum. A company earns it only once it holds the orchestration position and shows the value separation that proves it.
Alan has not arrived there. But of the companies I track, it is one of the clearest emerging orchestrators: a disruptor already building the new playbook rather than an incumbent wondering whether it can.
Electricity, Computers, and the ‘Non-AI’ Reflex
The “non-AI” reflex is not new. It is the latest version of a mistake that markets make at the start of every general-purpose technology: confusing a force that reorganizes an economy with a like-for-like upgrade.
When electricity reached the factory, the first generation of owners treated it as a cleaner alternative to steam engines. They pulled out the central steam plant, dropped a single large electric motor in its place, and kept the same overhead shafts and belts driving the same machines in the same order. The power source changed. The factory did not. And for three decades, the promised productivity gains barely showed up in the numbers. They arrived only when a later generation stopped swapping the engine and rebuilt the factory around the new principle: small motors on each machine and floor plans laid out around the flow of work rather than the geometry of the belts. Productivity then climbed steeply, and industrial leadership reshuffled.
The economic historian Paul David used this story precisely to explain why the computer, too, took decades to surface in the productivity statistics.
“Non-AI” is the modern “just a cleaner engine.” It looks at Alan, sees an insurer selling insurance, and files it under the old economy.
Alan’s First Wave: From €173 Million in 2024 to €804 Million ARR
Go back to September 2024, barely two years ago, in a timeline that already feels like another epoch. It was less than two years after the first public release of ChatGPT. Anthropic would not publish the Model Context Protocol for another month. Generative AI dominated the conversation, with the turn toward agents still over the horizon.
That month, Alan, already a unicorn, raised €173 million at a €4 billion valuation. It was the largest insurtech round in Europe that year, accounting for close to one in four euros invested in the sector. The mood elsewhere was unambiguous: Insurtech was a dead category, software multiples were stumbling, and the only heat in the room was generative AI.
But even then, Alan had established itself as a disruptor. It received the first new health-insurance license granted in France since 1986 and, in the decade since, has grown from nothing to 1.1 million members and roughly 37,000 corporate clients across France, Belgium, and Spain.
I argued at the time that the valuation was not, in fact, crazy. Alan’s leadership had already begun an aggressive investment in generative AI. Not a chatbot bolted onto a legacy stack to pass as cutting-edge, but AI worked into the core. “In Alan’s case,” I wrote then, “GenAI is already enabling gross margin improvement that has solidified its unit economics, put it on a path to profitability, and given it an advantage over other insurance incumbents.”
The detail mattered: Alan had integrated AI across the business, reporting a 28% cut in per-member administrative cost in 2023, with automation concentrated where insurers bleed: claims analysis and fraud. My case was that recurring revenue was the wrong lens for Alan, because it competes against incumbent insurers rather than software peers, and that the real story was margin. Gross margins are razor-thin in insurance, which is what sank so many insurtechs. It helped that Alan’s founders are also Mistral co-founders, which gives the company privileged access to sovereign European models in a domain where data residency is not optional.
That was early. The company used the round to accelerate, and it had already placed itself at the vanguard of the agentic crossing, in the part of the economy I describe as Wave One in Orchestration Economics: insurance, with claims adjudication against codified coverage rules, deep historical loss data, and a high routine-to-judgment ratio, alongside banking, corporate services, and customer support, where autonomous resolution has already been demonstrated at scale within weeks of deployment.
That performance is reflected in the numbers. ARR reached €804 million in early 2026, up from €340 million two years before, growth of 48% and then 53% in consecutive years. Management is guiding past €1 billion this year. Meanwhile, its valuation has climbed from €2.7 billion in 2022 to €5.5 billion today. Unusually for a company growing this fast, it is also moving toward profit: France turned EBITDA-positive in 2025, and group losses roughly halved.
That combination is the analytically interesting part. High-growth challengers usually buy growth at a loss. Profitable insurers usually do not grow at this rate. Alan is doing both, and its own accounts credit AI for the margin side thanks to automation concentrated in claims and fraud, where insurers tend to bleed.
Alan is already a challenger, restructuring around AI. It is not acting like an incumbent debating whether to embrace AI or simply defending its existing position.