Insure Think

Incorporating climate risks into modeling and pricing can help insurers better anticipate and manage their potential health and financial impacts.

AI models are now reliable enough to automate most decisions that define performance in insurance, writes Taktile CEO Maik Taro Wehmeyer.

With the right foundation, insurers can more fully embrace AI and realize the benefits it brings, writes Kevin Gaut, CTO of Instanda.

Real improvement in managing uncertainty from a risk perspective won't come from better technology alone.

One particular focus of attorneys general in the insurance space will likely be companies' use of AI in underwriting.

The broker experience is determined not by how quickly a risk can be submitted, but by how efficiently and confidently a carrier evaluates it.

Insurance needs to stop treating its shrinking pool of checks as business as usual, especially when the data needed to manage the risk inside that pool already exists inside most carriers' own systems, writes Shareen Minor, chief revenue officer, U.S., at Vitesse.

The high-risk delay is not a compliance holiday. It is time to make AI evidence, procurement and accountability operational, according to Corto Romagny, general manager for U.S. Operations at Uxopian Software.

Three areas inside agency finance are seeing the clearest, most measurable returns from AI and automation: commission reconciliation, premium financing and the monthly close.

In every weather event, entire regions are described as "impacted" as if risk were evenly distributed across geography. However, on the same street, sometimes even next door, one property suffers significant loss while another holds up.

The most successful insurers avoid framing digital transformation as a choice between experience and technology.

Once an AI-generated answer causes a loss, the argument moves beyond whether the answer was wrong, writes Dr. Viroshan Naicker, co-founder and CEO of Refiant.

Agencies rarely struggle because they don't use the right technology. They struggle because technology decisions become disconnected from the operational problems they are trying to solve.

The best place to start AI adoption is tasks where employees already describe them as repetitive, slow or unnecessarily difficult, writes Amy Carlisle, president of MSI.

Cyber incidents raise key questions about coverage, particularly when it's a third party under attack, writes Deborah Dioguardi, EVP and Professional Lines National Practice Leader at Jencap.

Effi Fuks-Leichtag, chief product officer at ERGO NEXT Insurance, writes about how entrepreneurs are turning to AI search tools for insurance guidance.

A wave of new AI-enabled frameworks for marketing mix modelling are becoming the new standard among forward looking marketing leaders, writes Karl Canty, partner at Artefact.

Recent chemical incidents in Washington and California highlight the peril of forgoing pollution coverage, writes Dennis Willette, SVP and head of environmental at Westfield Specialty Insurance.

When AI can make false evidence look real, insurers can struggle to know who to trust, writes Tom Rasmussen, vice president of product for claims at Carpe.

Insurance companies with the greatest advantage will adapt products and experiences locally while reusing capabilities globally.

The tasks that fill BPO delivery centers sit squarely inside what agentic AI systems handle today, writes Martin Henley, CEO of mea Platform.

The property-and-casualty insurance industry is undergoing a major digital transformation with the rise of generative artificial intelligence, writes Abhishek Peter, manager of digital marketing at FECUND Software Services.

The rise in infostealer malware and increasingly sophisticated phishing campaigns is compounding the problem for insurers.

Connected systems can help consumers understand each stage of the life insurance journey and ensure a more seamless, less fragmented consumer experience.

Virtual and mixed reality still have value for internal use and customer experience, even if other industries are moving on, writes Mark Klein, Chief Digital Officer at ERGO Group AG.

Legacy infrastructure, data challenges, workflow integration issues, regulatory concerns and skill shortages remain key obstacles in 2026

The carriers that are getting it right aren't using AI to replace adjusters.

Organizations that prepare early will be better positioned to protect their people and minimize operational disruption when severe weather strikes.

A successful insurtech venture requires a strong combination of innovation, insurance expertise, regulatory understanding and scalable technology, writes Abhishek Peter, manager of digital marketing at FECUND Software Services.

Insurance companies are unknowingly turning away customers when technology fails both the applicant and the human handling customer service, writes Michael Podgortsev, director of data and AI strategy, speaks from personal experience: A hum

AI is a limited resource, powered by even more limited resources. Carriers must not forget that, writes Jim Girard, vice president of engineering at Benekiva.

The insurers that build for execution, rather than waiting for the next tool or the next shock, will be the ones still keeping pace when the systems around them strain.

New systems will help but insurers first need to organize institutional knowledge and review processes.

As data sources expand and risks become more dynamic, embeddings are influencing how insurers assess risks, segment portfolios and support underwriting and pricing decisions, writes writes Brian Keller, PhD, vice president of AI and data science for LexisNexis Risk Solutions.

Teams should revisit sourcing decisions continuously, rather than treat them as fixed multi-year commitments.

A dangerous assumption persists that existing commercial insurance portfolios will naturally absorb any liabilities arising from algorithmic failures.

Insurance carriers have always relied on data to understand risk. What has changed dramatically, however, is how that data is used, writes Brian Keller, PhD, vice president of AI and data science for LexisNexis Risk Solutions.

Carriers must move beyond highly visible AI activity that may look like progress and toward real operational transformation, writes Peter McMurtrie, a partner of the insurance practice for West Monroe.

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.