Introduction
The rules that governed software pricing for a decade are breaking down. Per-user SaaS models made sense when users were people. Now that AI is automating those seats, the pricing logic collapses — and carriers, brokers, and insurtech vendors are all rethinking the economics at the same time.
Michael Nadel is a partner and head of the global insurance practice at Simon-Kucher & Partners. He joined Josh Hollander for his second appearance on the show to dig into what the AI era is actually doing to monetization — from the pricing mistakes early movers keep making, to why outcome-based models are harder to execute than they are to sell, to a 50,000-session LLM shopping simulation that revealed what could become the next SEO arms race for insurance carriers.
Guest Bio
Michael Nadel is a partner and head of the global insurance practice at Simon-Kucher & Partners, a global strategy consultancy focused on growth, pricing, and monetization. Before consulting, he spent time at CNA in strategy and innovation, and earlier led large-scale financial services implementation work at Accenture. He advises carriers, brokers, MGAs, and insurtech vendors on pricing strategy, and co-hosts an annual monetization masterclass at InsureTech Connect.
Key Topics
- From offense to defense — A year ago, clients asked how to monetize new AI features. Today the questions are more defensive: how does AI threaten my core product, my pricing model, and my existing revenue base?
- The two biggest AI pricing mistakes — Pricing before understanding what customers actually value, and jumping to outcome-based models before you can define or reliably deliver the outcome.
- Outcome-based pricing is the destination, not the shortcut — Buyers love paying only when value is delivered. The problem is definitional complexity — what counts as the outcome, who controls it, and what happens when results fall short.
- AI spend that looks like RPA in new packaging — Carriers running well-designed AI programs focus on workflow economics, not technology for its own sake. The recommended split: 70% on high-value workflow automation, 20% on data and governance, 10% on exploratory bets.
- GEO: the next SEO — Simon-Kucher simulated 50,000 insurance shopping sessions across 50 consumer personas and three major LLMs. What gets a carrier recommended by an LLM is not the same as what gets them ranked on Google. CMOs need to decide how to treat LLMs as a distribution channel now.
- Services businesses face the same disruption — Pure labor arbitrage is structurally challenged by AI. Firms that survive will combine domain expertise with AI-enabled delivery and evolve from vendors to partners.
Notable Quotes
"You need to understand what people value before you prescribe a price. But very often, people build something, bring it to market, and then try to figure out why it isn't selling."
"Automating a bad process simply creates a faster bad process."
"It's not replacing system X with system Y — it's changing the way you work fundamentally. Orange juice to lemonade. Not a better way to make orange juice."
"Last year, roughly one percent of our traffic came from LLMs. This year it was roughly five percent and increasing."
Resources
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