For a 10-year-old carrier that still has a combined ratio far above 100, Lemonade has never been reluctant about dissing its established competitors or about patting itself on the back. In that vein, CEO Daniel Schreiber recently published a manifesto titled, "Why Incumbents Won't Catch Up."
The cheeky claim is that Lemonade was founded as an AI-native and thus has a 10-year head start on State Farm, Allstate, Progressive, GEICO, et al. Schreiber says the incumbents are "optimized for yesterday," while Lemonade is "designed for the world as it’s becoming." He argues that Lemonade's advantage will keep growing.
Schreiber's argument doesn't make me want to rush out and buy stock in Lemonade, which, after some years in the wilderness, has recently surged and now carries a hefty $5.1 billion market valuation. But I don't dismiss his argument, either. He's certainly right that early movers like Lemonade have an advantage that incumbents need to reckon with. He also poses three measures for AI adoption that all insurance companies should test themselves on.
Let's have a look.
Schreiber writes that "companies who slap technology on top of their legacy businesses are not changing their DNA: their incentives, capital allocation logic, talent mix, data architecture, distribution dependencies, brand promise, investor expectations, and legacy stacks. Those systems and processes co-evolved over many decades. They cannot be reengineered piecemeal; and untangling them is laborious and risky."
He says Lemonade began as an AI-native:
"The result is a different cost structure. A faster clock speed. A compounding feedback loop that continuously improves underwriting, customer experience, and efficiency.
"The question, then, is not whether incumbents can “use AI.” Of course they can. And they should. The question is whether they can re-architect themselves to close the gap to Lemonade.
"That seems unlikely."
To buttress his argument, he suggests three tests for whether an insurer is adopting AI at its core. All three, of course, show Lemonade outpacing incumbents.
The first is what Schreiber calls The Scaling Quotient. You look at how fast you're growing, by whatever measure you use. You then divide that growth rate by the rate at which your headcount is increasing. If you're growing, say, your policies in force far faster than you're adding people, you're winning. If not, not.
Second is Loss Adjustment Expense Ratio. You take your loss adjustment expenses and divide by your gross earned premium. If you're spending a lower percentage than the industry average, and the percentage is declining, you're winning. If not, not.
Third is what Schreiber calls Structural Precision. This involves two calculations of gross profit. First is gross profit divided by your exposure — you want as high a profit as you can get based on the risk you're taking on. Second is gross profit divided by your sales and marketing expenses — you want to acquire customers as efficiently as possible. You add the two calculations, then compare yourself to the industry over time.
Those all strike me as fair enough measures of efficiency for any carrier, and AI is certainly the main driver these days. I think his approach can be extended to other players in the insurance industry, not just carriers. Agencies, for instance, can measure whether AI is making them more efficient in winning clients, in processing renewals and so on.
If you take Schreiber's piece as a wake-up call for incumbents, I can get behind that, too. They can't just be tacking on bits of AI to become slightly more efficient, and they can't just wait and see. The carriers developed their cultures over decades, and changing them will take many years. People don't change overnight even if the technology does. Incumbents have to be thinking big — NOW — and experimenting with ways to allow for radical change. That may even mean new service-based business models, such as Predict & Prevent, or very different distribution channels, such as through embedded insurance.
Schreiber can certainly point to lots of industries where upstarts with a head start and momentum overcame incumbent behemoths — look at Kodak, Blockbuster, Nokia and Blackberry, city taxi monopolies and Sears (as well as every other company in Amazon's path).
Now to quibble.
For one thing, Schreiber is focusing almost entirely on overhead, which accounts for maybe 20% of every premium dollar, while claims in P&C account for north of 60%. You can be as efficient as you want in processing claims, but if you're taking on bad risks you're still going to lose — and even after years in the business, Lemonade's combined ratio in the fourth quarter was 139.
In addition, as Simon Torrance writes in this thorough analysis, the sort of AI that will really matter in the long run is AI agents, and the competition is just beginning in that phase. He says:
"The genuine compounding asset — the one that cannot be replicated by purchasing the same technology at a later date — is not automated claims processing. It is what happens [when] deliberative agentic teams capture structured reasoning with every decision, build institutional memory that compounds across thousands of cases, and encode expert judgment that persists independently of the individuals who generated it. This is Intelligence Capital. The question Lemonade's investors should be asking is whether their architecture has built this — or whether it has built a more efficient version of what every insurer will have by 2027."
Lemonade might also want to be careful about lecturing incumbents just yet, given that it is still small and has so many ways it could slip up as it expands into new lines of business and new geographies. (Here is a good analysis of its opportunities and challenges.)
But I suppose being cheeky is in the company's DNA at least as much as AI is.
I hope the rest of us take the Lemonade manifesto for what it's worth — and devise real metrics that accurately measure our progress with AI (or lack thereof), think boldly about where AI agents can change everything about our businesses and start reshaping our cultures for, as Schreiber put it, "the world as it's becoming."
Cheers,
Paul