Insurance Part 6: The Feedback Loop (Advanced AI)

03.16.2026

Insurance Part 6 The Feedback Loop (Advanced AI).png The “AI Adoption” Series: The Conclusion

We have walked through the entire value chain of AI adoption:

Strategy: We defined the outcome (e.g., Profitable Growth).
Team: We aligned IT, HR, and Ops.
Data: We built a clean fuel source.
Insights: We deployed predictive models.
Action: We automated the workflow.

If you stopped at Part 5, you would have a highly efficient, automated insurance company. For about six months. Then, it would start to fail.

The final piece of the puzzle is the Feedback Loop. This is the mechanism that prevents your AI from becoming obsolete and transforms it from a tool that executes orders into a partner that informs strategy.

The Industry Reality: The “Set It and Forget It” Trap

The most dangerous myth in AI is that it is a one-time project. You do not “build” an AI; you “raise” it.

The Drift Problem: AI models are trained on historical data. But the world changes. Economic inflation spikes, new vehicle technologies emerge, and legal precedents shift. When the world changes and the model does not, we get Model Drift.
The Failure Rate: Research indicates that nearly 85% of AI projects fail to deliver sustained value, often not because the technology broke, but because it drifted into irrelevance without continuous monitoring (The Praxi Pod/KPMG).
The Regulatory Pressure: The NAIC (National Association of Insurance Commissioners) and various state regulators are now demanding that insurers prove their models are not drifting into discriminatory patterns. You cannot just use the model; you must audit the model continuously.

The Strategic Imperative:

You must build a “Closed-Loop” system. The output of your automation (Part 5) must become the input for your next strategy cycle (Part 1).

The Strategy Template: Monitor, Interrogate, Refine

To close the loop, you need three specific capabilities.

1. Monitor: The “Canary in the Coal Mine”

You need a subordinate AI whose only job is to watch the main AI.

The Function: This system tracks the “health” of your risk models.
The Trigger: If your “Auto-Quote” engine usually converts at 15%, and suddenly drops to 12% in the Northeast region, the monitor sounds an alarm.
The Value: You catch the market shift (e.g., a competitor lowered rates in that region) weeks before it shows up in your quarterly financial report.

2. Interrogate: The “Digital Oracle”

Once the alarm rings, you use AI to answer the difficult questions.

The Old Way: You ask an analyst to pull a SQL report, export to Excel, and build a pivot table. This takes three days.
The New Way: You ask the AI, “Why did conversion drop in the Northeast?”
The Answer: The AI analyzes thousands of declined quotes and tells you: “Competitor X has introduced a new bundle for EV owners, causing us to lose 40% of our Tesla renewals.”
The Shift: You are no longer guessing; you are informed.

3. Refine: The “Strategy Updater”

This is where the loop closes. You take that insight and feed it back into the Business Strategy (Part 1).

The Action: You do not just “fix the bug.” You adjust the strategy. You might decide to launch a competing EV bundle or exit that specific niche entirely.
The Result: Your strategy is no longer a static document written in January; it is a living organism that evolves in real-time.

The Underpinning: Governance as a Lifeguard

This brings us back to our first underpinning: Strategy Includes Governance.

In a feedback loop, governance is not a blocker; it is a safety net. It ensures that as your models “learn” and update themselves, they do not learn bad habits.

Example: If your model notices that declining claims from a certain zip code improves profitability, it might “learn” to redline that zip code.
Governance Role: The governance framework detects this bias immediately and blocks the update, ensuring you remain compliant while pursuing profit.

The Direction: Dynamic Insurance

We are moving away from the annual cycle of insurance (annual policy, annual rate review, annual strategy) toward Dynamic Insurance.

Current State: We price risk based on who you were last year.
Future State: We price risk based on how you are behaving now, and we adjust our business strategy based on how the market is reacting today.

Series Conclusion: The Next Step is Yours

We have covered a lot of ground. We moved from the boardroom strategy to the IT basement, through the data swamp, and into the automated future.

Your Immediate Next Step:

Do not try to build all six parts at once.

Go back to Part 1.
Write down your Business Outcome (e.g., “Reduce Small Commercial Expense Ratio by 5%”).
Identify the one subordinate strategy (Part 2) needed to achieve it.
Execute that single thread.

AI is not magic. It is engineering. And like any engineering project, it is built one brick at a time.

Salvatore Magnone is a father, veteran, and a co-founder, a repeat offender in the best way in fact, and a long-time collaborator at DOOR3. Sal builds successful, multinational, technology companies and runs obstacle courses. He teaches business and military strategy at the university level and directly to entrepreneurs and military leaders.

https://www.linkedin.com/in/salmagnone/