AI Is Changing Our Industry
in Insurance Brokers

The short answer

The question is not what AI can do. It is which of your carrier commission lines gets cheaper for a client to produce themselves. The version of this question that applies to insurance brokers is not the generic one. 71 percent of revenue flows through carrier commissions while shifting an incremental 8 percent to fees would require replacing 142 renewal accounts and cut near-term margin by 1.8 to 2.3 points — so an answer that ignores 19.0 will be confidently wrong. The analysis has to start from 91.2 and 664 rather than from revenue.

Most strategy conversations start from capability and end nowhere, because capability is not the variable that decides outcomes. The variable is whether the commission you receive for placing coverage becomes dramatically cheaper for a carrier or a client to handle directly.

That is answerable line by line. For each commission stream: what fraction of the placement or service cost is the work being automated, how much of the standard commission or contingent commission is defended by something other than that work, and how quickly could a credible alternative reach parity on renewal retention.

The uncomfortable finding is usually that the exposed lines are the profitable ones, because high-margin placements are normally information work. The response is rarely to adopt faster; it is to move what you charge for toward risk-control or captive feasibility rather than the placement steps the automation makes cheaper.

How to tell this is actually your problem

These three together are the signature. One on its own usually points somewhere else.

✓ The pressure is showing up as negotiated reductions in standard commissions on renewals, not as lost accounts.
✓ Clients are asking why placement or reporting still requires the same cycle time when comparable outputs appear faster elsewhere.
✓ A newer broker quotes a comparable program at a fraction of the standard commission plus contingent structure.

The move that usually makes it worse. Adopting the tools without changing what you charge for, which lowers the cost of servicing the 71 percent carrier commission book and invites carriers to reduce the same commissions, leaving the margin where it was.

Who this is for — and who it is not

It is for you if you run or finance an insurance broker and the pressure is showing up as price, not as lost deals. It is the situation where the numbers are available but nobody has put them in an order that produces a decision.

It is not for you if Percision is the wrong tool if you already know the answer and only need execution capacity, or if the business is pre-revenue — then the constraint is evidence about the market, not analysis of your own figures. Percision is not a lawyer, tax advisor, auditor, licensed appraiser, clinical or regulatory filer, or an AI implementation shop. It does not do HR casework, creative-only brand work, or impersonate a named consulting firm. It is a strategy analysis engine — not a template library. Also wrong if you need facilitation, politics, or someone to sit with a lender or buyer. Those are human jobs.

Percision is not a lawyer, tax advisor, auditor, licensed appraiser, clinical or regulatory filer, or an AI implementation shop. It does not do HR casework, creative-only brand work, or impersonate a named consulting firm. It is a strategy analysis engine — not a template library.

What this looks like when the analysis is actually run

Below is an excerpt from a real run of this analysis on an insurance broker. It is a sample profile rather than a customer, and it is unedited engine output — this is the format you get, on your own numbers.

The subject is Kesterline Risk Partners, a sample company profile used for testing rather than a customer — 47.8 million dollars in total revenue from commissions and fees.

This is one move out of a full analysis. Read a complete report — every page, no email required.

What the engine does with this question

This question routes to AI Horizon, one of 29 engagements the platform runs. For insurance brokers it works through 19.0, 91.2, 664 and 31, then produces the sequence rather than a list of options — which move first, what it funds, and the observation that would say the sequence is wrong.

You watch the analysis get built before paying anything. Read a complete report here if you would rather see the depth first.

Questions people ask about this

Should we build AI into our product or use it internally first?

Internally first is usually right, because it produces evidence about your own economics before you make promises to customers. The exception is when a competitor has already reset the customer expectation, in which case internal efficiency arrives too late.

How fast is this actually moving in my industry?

Judge by price, not by announcements. When the market price for the output you sell begins to fall, the disruption has arrived regardless of what the technology can demonstrate.

What if we are too small to invest in this?

Smaller businesses usually have the advantage of being able to change what they charge for quickly. The move that matters is repositioning, and it is cheaper for you than for an incumbent with a large base to protect.

Is this different in insurance brokers than in other industries?

Materially, yes. 71 percent of revenue flows through carrier commissions while shifting an incremental 8 percent to fees would require replacing 142 renewal accounts and cut near-term margin by 1.8 to 2.3 points — which changes both the diagnosis and the order of the fixes. The metrics that decide it here are 19.0, 91.2, 664, and an answer built on industry-general benchmarks will usually point at the wrong one first.

What data do I need before this analysis is worth running for an insurance broker?

Less than most people expect. Your last twelve months of revenue and cost split the way you already split it, plus whatever you hold on 19.0 and 91.2. The analysis is explicit about what it is assuming where your data stops, which is more useful than waiting for numbers you may never have.

When is Percision the wrong tool?

Percision is the wrong tool if you already know the answer and only need execution capacity, or if the business is pre-revenue — then the constraint is evidence about the market, not analysis of your own figures. Percision is not a lawyer, tax advisor, auditor, licensed appraiser, clinical or regulatory filer, or an AI implementation shop. It does not do HR casework, creative-only brand work, or impersonate a named consulting firm. It is a strategy analysis engine — not a template library. Also wrong if you need facilitation, politics, or someone to sit with a lender or buyer. Those are human jobs.

Does Percision replace a lawyer, tax advisor, auditor, or AI implementation team?

Percision is not a lawyer, tax advisor, auditor, licensed appraiser, clinical or regulatory filer, or an AI implementation shop. It does not do HR casework, creative-only brand work, or impersonate a named consulting firm. It is a strategy analysis engine — not a template library.