2036 / THE FUTURE BEYOND THE FUTURE
Predictive Risk + Sensors + Insurance Reinvention
What if your insurance company made more money preventing a disaster than paying for it?
Insurance could evolve from a promise to pay after a loss into a service that helps people stop selected losses before they happen.
THE BIG PICTURE / IN 30 SECONDS
Five ideas.
One extraordinary possibility.
2031
2036
- 01
Insurance has traditionally become most visible after something goes wrong. A pipe bursts, a building burns or a storm causes damage, and the insurer assesses the loss and helps pay the cost according to the policy.
- 02
But more sources of information can now reveal risks before the damage is complete. A water sensor may detect a leak, a weather service can warn of a dangerous storm, and equipment monitoring can reveal unusual conditions that deserve inspection.
- 03
If insurers help customers respond earlier, both sides might avoid the worst consequences. A warning that prevents major water damage could spare a family the disruption of moving out and spare the insurer a large claim.
- 04
By the early 2030s, some policies could begin including practical prevention services. Insurers might offer qualified safety monitoring, maintenance advice or support to reduce exposure rather than focusing solely on reimbursement.
- 05
The extraordinary 2036 possibility is a different insurance business model. Some insurers could be rewarded for the disasters they help customers avoid—provided pricing remains fair and people do not lose coverage simply because they refuse intrusive surveillance.
An insurer is already offering incentives to prevent a claim. Chubb has documented programs that help policyholders obtain water-leak detection and shutoff equipment, with possible insurance discounts subject to eligibility. Zurich has described using artificial intelligence to identify properties at elevated fire or water-damage risk and work with customers on prevention. These are concrete early examples—not proof that most insurance losses can be prevented or that all insurers have adopted the model.
THE BIGGER STORY: What changes when a company that earns its living from risk starts creating value by reducing the risk itself?
THE FULL STORY / TODAY'S EVIDENCE, TOMORROW'S POSSIBILITIES
What happens when
the breakthroughs compound?
The extraordinary possibility: Insurance could evolve from a promise to pay after a loss into a service that helps people stop selected losses before they happen.
Imagine the difference
A family returns from a holiday to find the floor ruined by a slow plumbing leak. Repairs take months. Insurance may cover much of the cost, but it cannot easily replace the disruption, lost possessions and hours spent managing contractors. Everyone would have preferred an inexpensive intervention days earlier.
Now imagine a connected sensor detecting unusual moisture and alerting the household. The owner authorizes a plumber and shuts off water to the affected line. The repair becomes a small job instead of a major claim. A useful future insurer might help install the sensor, offer an emergency service and share some of the financial benefits created by avoiding a much larger loss.
It's an ordinary example with a remarkable implication. Insurance would begin changing from a financial response to bad news into an ongoing relationship aimed at preventing certain forms of bad news. The idea is simple; making it fair and economically sound is not.
2026: Risk information already exists, but incentives don't always align
Today, insurers use a variety of information to assess and price risks. Property information, weather histories, claims records and building characteristics can all influence an underwriting decision. This is already visible in real insurance offerings. Chubb describes programs for water-leak sensors and automatic shutoff equipment, including possible discounts for qualifying customers. Zurich describes using AI to identify properties at elevated risk of fire or water damage and collaborating with customers on loss prevention. These are practical initiatives, though actual results depend on equipment, implementation and whether a warning leads to action.
Artificial intelligence can help examine patterns across complicated data, but that capability creates a tempting misuse: insurers might use more data solely to identify people they would rather not cover. Better prediction could lead to higher premiums or exclusion in high-risk communities rather than better prevention. There is also the risk of treating correlations as explanations. A model might identify a neighborhood as vulnerable without establishing a fair basis for an individual price.
The more interesting commercial possibility is to connect risk information to practical services. Detect a leak, arrange help. Identify elevated wildfire exposure, support appropriate mitigation. Recognize abnormal equipment vibration, schedule maintenance. The aim would be to reduce expected losses in ways that the customer can verify and understand.
2031: Protection becomes an active service
Picture an insurer in 2031 working with homeowners in an area increasingly affected by severe weather. Customers can opt into a program that provides verified alerts, advice on protective measures and assistance with selected upgrades. Participation is transparent: people know which information is collected, who receives it and how it might affect premiums. An independent study evaluates whether the program actually reduces losses rather than merely attracting customers whose homes were already safer.
For commercial clients, insurers might develop partnerships with equipment-maintenance firms and building operators. A manufacturer with critical machinery could receive an early risk notification and arrange service before a prolonged shutdown. Here the insurer's knowledge about losses becomes useful operational information, not just a number in a renewal letter.
But insurers cannot prevent every event. Severe storms, earthquakes and wildfires can overwhelm even well-prepared buildings. A prediction that leads to a missed alarm could create complex liability questions. And a provider collecting continuous information about homes or workplaces must not become a private surveillance system.
2036: A business that profits from the loss that never happens
By 2036, the industry might have developed more products that explicitly combine coverage, monitoring and prevention. A property insurer might offer lower total ownership costs for buildings that demonstrate effective maintenance. An industrial insurer could provide risk-engineering services supported by reliable monitoring. Public authorities and insurers might cooperate on projects that reduce community-wide losses rather than merely reprice coverage after repeated catastrophes.
The deeper transformation is in the economics. A company that pays claims after damage has an opportunity to save money when damage is avoided. The customer gains more than a smaller premium: less disruption, fewer injuries, greater confidence. If those savings can be measured and shared fairly, prevention could become a significant competitive advantage.
The darker possibility must be taken seriously. If insurers gain powerful insight into risk while offering no help to reduce it, more people may become priced out of essential coverage. A system optimized only for selecting the safest customers would be impressive prediction technology and poor social policy. A genuine innovation should expand protection, not merely divide people into profitable and unprofitable groups.
IT GETS PERSONAL / FOUR DIMENSIONS OF CHANGE
What could this mean
for my future?
My life
An insurer that helps prevent a home disaster could deliver value long before a claim. But people should have choices about sensors, personal data and the ability to challenge an inaccurate conclusion. A voluntary safety tool is very different from being required to monitor every movement in your home to obtain affordable coverage.
My career
Insurance could need more risk engineers, data specialists, behavioral researchers, loss-prevention experts and people who can explain model decisions to customers. Traditional claims expertise would remain important: some losses will still occur and must be handled fairly. The emerging skill is turning risk knowledge into practical, ethical intervention.
My business
Companies can start by studying their own preventable losses. Which incidents happened after an earlier warning sign? Would a sensor, inspection schedule or maintenance process have changed the outcome? Insurers and brokers should be asked how they can support actual prevention, not just renew coverage. A valuable pilot should measure loss reduction, customer benefit, cost and privacy implications together.
My industry and community
The most significant effects could appear in regions facing growing flood, wildfire or infrastructure risk. Insurance alone cannot make unsafe places safe. Public investment, land-use rules and resilient construction remain essential. New technologies should help communities manage risk rather than simply making it easier to withdraw coverage from them.
JIM CARROLL'S PERSPECTIVE
Reinvent the outcome, not just the transaction
Jim Carroll's industry work on insurance, AI and business-model change suggests a useful distinction. Digitizing a claims form is an improvement to a familiar process. Using intelligence and technology to reduce the probability of the claim can change the service itself. That is a much larger opportunity—and a more difficult strategic challenge.
The question for insurance leaders: If our greatest value were measured by losses prevented, what would we do differently tomorrow morning?
THE REALITY CHECK / WHAT MUST HAPPEN FIRST
What must happen before this future becomes real?
Programs require evidence of actual prevented losses, consent-based data use, fair pricing, transparent model decisions and careful regulation. Prevention must not become an excuse for withdrawing protection from people who need it most. This scenario does not claim that weather disasters can be stopped or all claims eliminated.
THE BIGGER YOTTABIT IDEA
The future is bigger
than you think.
The YottaBit possibility is a world where insurance is not merely there when something terrible happens, but sometimes helps make sure it doesn't.
THE SCIENCE / CHECK THE EVIDENCE
Where the facts end
and the future begins.
The sources below support the present-day foundation of this story—not a promise that the 2031 or 2036 scenarios will happen. These are possibilities, not forecasts.
- Chubb, Water Coverage and Leak-Prevention Programs — Insurer-backed monitoring, shutoff equipment and conditional discounts.
- Zurich, How accurate data and AI can transform claims and help customers build resilience — Insurer-reported prevention initiatives and limitations.
- NIST, Community Resilience Systems Modeling — Planning approaches to reduce losses from hazards, not proof of insurer-specific benefits.
- NIST, Infrastructure Resilience — Resilience, smart connected infrastructure and trustworthy systems.
- Research direction: evaluate documented loss-prevention programs, insurer-specific evidence and the fairness effects of monitoring before adding any quantitative claims.
- Jim Carroll: AI Megatrends — Insurance and Future, Sector by Sector — Insurance, historical industry commentary.
THE NEXT FUTURE / KEEP EXPLORING