There's an urgent and slightly uncomfortable conversation happening across the insurance market right now. We talk a lot about growth, distribution, AI, data and digitization, but most of our operating models simply aren't built for the environment they're being asked to perform in.
This was the backdrop to Send’s recent INFUSE webinar, where we explored what it really means to move from a traditional, linear underwriting model to something fit for 2026. My view in one line: The challenge isn't innovation, it's whether our foundations can support it.
Brokers, MGAs and insurtechs are moving quickly. They're building smarter, more connected models, and in some cases, they're becoming more confident in their understanding of risk and pricing than the carriers behind them. Carriers haven't lost their edge, but there is a growing gap between what they have and what they can actually use. When your partners can ingest, process and act on data faster than you can, the balance starts to shift.
We're trying to make old models do new things
Many insurers are still running on legacy systems, fragmented data and manual workflows held together with spreadsheets. Trying to partner with more innovative businesses with that kit underneath you is a bit like putting Formula One parts onto the family car. In theory, it should make you faster. In reality, the underlying vehicle just isn't built for it.
What this is quietly doing to the data underneath doesn't get talked about enough. Carriers have always relied on their own book to set pricing, shape appetite and spot trends. As more of that book gets written by more advanced partners, the picture starts to erode. The partner is collecting richer, more granular data than the carrier ever did, but it doesn't plug neatly back into legacy systems. So, the carrier is left with two bad options: force new, unique data into systems that weren't designed for it, or hold underwriting discipline on a book they can only half see.
Meanwhile the boardroom conversation hasn't caught up. I still see leaders planning with the line, "we did well last year, so let's take that and add 10%," without really understanding how or why they got there. Managers are patting themselves on the back about the growth, while their underwriters are quietly wondering whether the wheels are about to come off. From the top floor it looks like a winning streak. From the underwriter's desk it looks like a book they can't quite see the edges of.
This isn't a technology problem. It's a trust problem.
Whenever the conversation turns to data, we default to the usual list of quality, consistency, standardization and validation. Those things matter, but for me the defining characteristic of good data is simpler. It's trust.
If an underwriter doesn't trust the data, they won't trust the outcome. And if they don't trust the outcome, they'll find a workaround. Spreadsheets sitting alongside core systems, manual overrides, parallel processes. Every one of those is a vote of no confidence in something that was meant to solve the problem.
We still talk about this as if it's a technology issue. It isn't. We know how to cleanse, enrich and validate data. The harder bit, and the one we keep ducking, is getting people to agree on what a data point actually means and how it should be used. That is where transformation programs stall. Not because the tools aren't good enough, but because the alignment isn't there.
Real change starts with asking better questions
We need to stop asking how to force people into the process and start asking why they're working around it. Those workarounds are telling us something. They point to gaps in trust, usability, clarity or alignment. If you don't understand the gap, no amount of new technology will close it in a lasting way.
You need the right driver, not just a better car
The firms moving fastest right now, particularly MGAs and newer entrants, don't just have better technology. They have a different mindset. They're entrepreneurial, closer to the customer, and they design their operating models around outcomes rather than internal constraints. They're still looking outwards.
You can give a business a Formula One car, but if the way it thinks and operates doesn't change, it won't deliver the performance you expect. Technology creates opportunities. It doesn't replace judgement, culture or customer understanding. You need both the right driver and the right vehicle. One without the other is either dangerous or going nowhere.
Looking ahead
I'm often asked where the market will be in three to five years. What I can say is that the organizations winning right now, in insurance and well beyond it, are the ones built around their customers. Netflix, Starling, Octopus Energy. They design around the customer first, and they run small, deliberate experiments so they can respond when things change. They don't bolt new technology onto broken processes and hope for the best.
Insurance isn't there yet. We know we're going to adopt better technology. The real question is whether we can build the operating models, data foundations and trust to actually use it. If we don't, we're just making the same car go a bit faster. And that won't be enough for what's coming next.
