Insure Think

Fraud prevention is the foundation for trust at scale, shaping how confidently customers engage.

If the first half of the year was defined by a race to bring AI-powered products to market, the second half will be defined by commercial discipline and pricing realities, write Michael Nadel and Andrew Larsen of Simon-Kucher.

The path forward is to assess risk one property at a time, in close to real time, using AI.

To get the best results from AI, insurance companies must first address the structural problems that create friction within their processes, writes Earl Shaw, CIO of Renaissance.

Genuine readiness in 2026 requires documented third-party access audits across broker and TPA relationships plus evidence that controls were verifiably in force.

Advancements in estimating tools are helping insurers deliver faster and seamless digital claims, writes Marc Rothchild, EVP and head of claims at Xceedance.

Insurers will start relying on more advanced approaches to evaluating cyber risk, including continuous cyber risk monitoring.

AI-powered platforms have collapsed the production timeline for a professional TV commercial from weeks to hours. But the agents who are getting real value out of TV advertising right now aren't just putting campaigns out. They're building frameworks for reading what comes back.

A quick quote and great customer experience does the rest.

Effective digitization eliminates manual data transcription while protecting the insurer's view of risk.

The rise of agentic AI is about to expose a major divide within the insurance industry.

Despite the growing risk for industrial events, these incidents are often excluded from CAT aggregation frameworks. 

In many cases, the tools used in insurance are not fully autonomous agents that make decisions independently — and for good reason.

When a new claim enters the system, a race against time begins.

Carriers that deliver communication quality, clarity of instructions, compassion from staff, and a single dependable point of contact were remembered and chosen again.

Insurers can break the cycle by expanding their use of global talent, strengthening compliance training and treating administrative support as a strategic capability vs. a back-office expense.

AI is evolving from an attractive innovation into something much closer to an operational necessity.

Moving the fastest or spending the most does not guarantee real progress with AI.

If insurers can use AI to build a property file, policyholders should have the right to know what is in that file when it affects premium, eligibility, renewal or coverage.

Problems will arise without good governance in place to guide AI adoption.

Carriers are adopting AI to improve underwriting, pricing and risk selection, but most models still rely on static data collected at a single moment in time.

Dashcams and other in-cab technologies are giving companies the tools they need to assess driver behavior.

Insurtech companies most likely to endure will prioritize the basics over elaborate tech.

Insurance carriers are investing in technology to gauge how interactions between carriers and policyholders are evolving.

High-resolution aerial imagery and property intelligence are enabling insurers to compress the time between landfall and portfolio-level understanding from weeks to days.

Instead of waiting for claims to confirm damage patterns, carriers can begin identifying likely impact zones earlier.

The combination of an AI tool with a human makes it easier to obtain accurate quotes, identify coverage gaps and share documentation between parties.

The focus is on surviving such an attack, with resilient systems and processes that ensure business continuity against all odds.

Can an insurer explain its decisions and demonstrate that AI is being used fairly and responsibly?

The next generation of pricing will harness AI, behavioral analytics and real-time data streams.

Audit your KPIs, align around outcomes and measure incrementality across the conversion stages.

By reducing data sprawl, improving governance, and preparing for forensic investigations in advance, organizations can strengthen their security posture and ensure they are ready to meet the demands of insurers when it matters most.

Tech gives insurers a chance to price risks more accurately, make buying insurance faster and create new products and services.

In a softening market, insurers that succeed with AI will not be those who deploy it fastest, but those who pair innovation with governance, accuracy and accountability.

Legacy platforms are recognized as a growing operational and regulatory exposure, yet any attempt to modernize them is perceived as introducing even greater risk

Reputation events are currently managed reactively by communications teams reporting using tools built for brand storytelling.

The insurance industry doesn't have an AI adoption problem—it has a structural design problem.

Automation will change underwriting, but judgment, context, and accountability still belong to people.

Bridging the gap between knowledge and core systems is the key to an improved user experience.

It is not just about modernizing systems, but about standardizing how transactions are processed and how data is exchanged across the ecosystem.

Carriers gain ground when treating personalization as a structural shift instead of a simple feature enhancement.

The goal is to improve risk management and expand access to more customers in markets that better data now makes possible.

As insurers modernize their products and operations, delivery capability is becoming a key differentiator.

AI is making fraud more sophisticated and harder to detect.

Moving beyond a model centered on reimbursing claims to one that supports healthier outcomes earlier in the pet care journey.

The gap between how insurers invest and measure risk is widening in ways that are often difficult to detect.

Seasonal risks impact every business differently.

Underwriting, risk models and policyholder support must evolve to reflect how identity data is used in modern fraud.

The residential property management industry has a glaring risk problem: a systemic failure to treat renters insurance compliance as a continuous obligation, rather than a one-time checkbox.

AI redefines how risks are assessed, policies are priced and claims are managed.