With the new year in full swing, property and casualty insurers are navigating a period of considerable uncertainty. Customer expectations are evolving, risk patterns are becoming more volatile, and human-AI collaboration is reshaping decision-making. In 2026, the distance between strategic intent and operational execution will separate those gaining ground from those losing it.
While insurance executives recognize that modern core systems and advanced technology are essential for transformation, the industry still lags and faces mounting pressure to meet broker and policyholder expectations. Too often, limited technological maturity holds progress back. Personalization won't scale without stronger data foundations. AI will create more technical debt unless workflows evolve at the same time. And climate risk modeling will fall short without dynamic underwriting.
Here are four trends every insurer should watch – and act on – in the year ahead.
1. From static to dynamic: how evolving consumer expectations are redefining insurance
Today's consumer will not accept an inferior experience. Across insurance, our research shows that two in three (63%) policyholders are willing to share data to receive personalized policy recommendations and premium discounts. Insurers recognize this: while 87% of industry executives acknowledge that their customers expect personalized experiences, only 54% report readiness to deliver at scale. The gap isn't customer willingness or awareness; it comes down to execution.
Insurers that design products around usage‑based coverage, dynamic pricing, telematics, and embedded distribution – rather than static, one‑size‑fits‑all models – are increasingly capturing outsized growth and staying ahead.
2. The data foundation: why personalization stalls without infrastructure
Personalization requires AI-ready data infrastructure, not just integration. 70% of insurers say data fragmentation and quality challenges limit their ability to derive actionable insights. The data sources relied on can be siloed and disconnected, with different practices for underwriting or claims, and quality standards attached. This creates inconsistent results and conflicting interpretations. Legacy systems become a bottleneck holding back progress. Without this foundation, personalization remains more promise than practice.
When done right – prioritizing data quality, integration and democratization of data with real-time capabilities – the payoff is real. Carriers report improved retention rates when they integrate customer service insights across functions. Forward-looking insurers are already translating data-driven strategies into real-world solutions, setting new benchmarks for personalization across the industry.
As an example, Nationwide introduced a discount scheme for its policyholders, linking safe driving behavior in its usage-based insurance program to unlock personalized savings on homeowners' insurance.
3. Scaling AI: translating enterprise intelligence into customer outcomes
With data infrastructure in place, AI amplifies personalization at scale. But here's the paradox: insurers want to deploy AI agents across operations and increase their generative AI investments, yet most pilots stay pilots. Across large enterprises, AI gets stuck in individual functions, creating technical debt and inconsistent operational models rather than transformation. 2026 will start to reveal which insurers moved from proof-of-concept to proof-of-impact. This means ensuring AI delivers measurable outcomes, builds trust, and enables collaboration at scale.
The harder half isn't technology deployment – it's workflow redesign. You can't bolt AI onto legacy processes and expect enterprise-wide transformation. While 96% of financial services leaders cite regulatory and compliance concerns, that caution often masks a deeper challenge: redesigning how work actually happens.
Real impact emerges when AI is embedded across processes, systems, and operating models – turning data infrastructure into tangible customer outcomes. The insurers reporting improved underwriting outcomes through advanced capabilities didn't just invest in technology; they used these capabilities to address critical underwriting gaps while optimizing exposure management.
4. From reactive to resilient: why climate risk will demand a new insurance playbook
As personalization and AI reshape customer engagement, climate risk is exposing the limits of historical data models. They struggle to capture the rising severity of secondary perils and the growing exposure from population shifts into high-risk zones. According to the Gallagher Re 2024 Natural Catastrophe and Climate Report, severe convective storms accounted for 41% of global insured catastrophe losses. Capgemini data also reveals 70% of the global population is expected to reside in urban centers by 2050, amplifying exposure in vulnerable regions. Regulatory mandates are equally tightening with scenario analysis, climate risk disclosures, and capital adequacy norms now becoming table stakes.
These paradigm shifts demand a move from reactive to resilient risk modelling. By consolidating high-resolution hazard mapping, real-time climate data, and predictive analytics into underwriting platforms, insurers can improve pricing accuracy and strengthen capital adequacy against secondary peril losses.
One global insurer centralized its property data from multiple sources to enable dynamic risk scoring and portfolio-level exposure analysis. As a result, they identified concentration risk across portfolios by specific perils, uncovering multimillion-dollar missed limits. That's resilience in action: insight that changes pricing, accumulation, and capital decisions before the next event.
The road ahead
Taken together, these four trends signal a defining imperative for the property and casualty insurance industry in 2026. This is no longer about incremental improvements. It's about embedding intelligence, agility, and foresight into every layer of the enterprise that turns disruption into opportunity.
