European insurance is at a point where strategic ambitions and execution realities clash. Many insurers have solid plans for modernisation, but actual implementation still lags. Three-quarters of modernisation projects still fail. Only a small proportion of insurers have succeeded in scaling AI beyond initial pilots. And only one in three feels confident about complying with upcoming DORA requirements.
This growing gap between vision and execution is becoming evident in financial results. Over the past five years, insurers that successfully carried out digital transformation projects have delivered higher shareholder returns than those that have not. This marks a notable structural divide in an industry that traditionally progresses slowly.
Across Europe, three groups are emerging. Some insurers are already operating on modern, cloud-based platforms and can innovate at a pace that competitors notice. A second and much larger group is mid-transformation. They have momentum, but their success depends heavily on disciplined execution. A third group remains constrained by legacy systems, and most of their technology spending is absorbed by maintenance rather than growth.
Table of contents:
- Regulation Becomes a Strategic Technology Driver
- AI Finally Scales for Insurers That Build the Infrastructure
- Embedded Insurance and API First Distribution Reshape the Market
- Core Platform Architecture Determines Innovation Velocity
- Climate Risk Analytics Demand New Models and New Data
- Automation Offsets Workforce Shrinkage and Operational Pressure
- Ecosystem Integration Evolves Into Multi-Party Orchestration
- What This Means for 2026
Seven Forces Reshaping Insurance Technology in 2026
Seven technology forces are shaping these outcomes. Each one is important on its own. Together, they determine how insurers in Europe will compete through 2026 and beyond.
#1 Regulation Becomes a Strategic Technology Driver
Regulation is shifting from a compliance requirement to a powerful driver of modernisation. DORA, the EU AI Act, and CSRD reporting rules require levels of operational transparency, model governance, third-party oversight, and data lineage that older systems were never designed to support.
Only a minority of insurers feel fully prepared for these requirements. Yet the organisations addressing them proactively are discovering meaningful benefits. Building real-time monitoring and unified data governance creates cleaner processes, more reliable insights, and faster decision cycles. Strengthening oversight of external partners improves resilience and reduces operational risk. Investing in AI governance now will prevent costly redesign later.
“Only 25% of entities feel compliant with ICT risk management, while just 8% have full compliance in resilience testing and third-party risk management.” Deloitte
Regulation is quietly becoming the justification and the momentum behind many modernisation programs. As insurers strengthen these foundations, they become better positioned to solve a challenge that has held the industry back for years. They can finally scale AI in production.
#2 AI Finally Scales for Insurers That Build the Infrastructure
Most insurers do not struggle with AI accuracy. They struggle with operationalising AI at scale. Many carriers have working models, but very few have the systems required to run AI safely and consistently in day-to-day operations.
To move beyond pilots, insurers need reliable data pipelines, automated retraining, continuous monitoring of model performance, early detection of drift, full version control, and explain ability tools that satisfy regulatory expectations. These are the organisational and technical foundations that allow AI to operate reliably and transparently. Without this foundation, AI remains a set of interesting experiments. With it, AI becomes a true operational capability.
“Top performing insurers succeed because they build the organisational infrastructure that supports reliable, transparent, and scalable AI.” Evident AI Insurance Index
Where AI is deployed effectively, it is already reshaping underwriting and claims. Natural language processing is classifying loss descriptions more consistently than manual review. Computer vision is supporting adjusters with initial damage estimates. Underwriting assistants are surfacing historical patterns, comparable risks, and pricing suggestions in seconds. Fraud detection models are identifying subtle behavioral signals that humans might miss.
Once AI becomes reliable and repeatable, insurers are ready to connect these intelligent capabilities to external partners and distribution ecosystems. This shift is accelerating across Europe.
Marko Sumina, Product Manager at Adacta, commented:
“In 2025, the most successful AI projects in insurance were not the flashiest ones, they were the ones that were production ready. As insurers move from standalone models to copilots and agent based automation, the key differentiator becomes infrastructure: governed data pipelines, repeatable deployment, explainability, and measurable outcomes. The next phase of AI in insurance will be driven by multimodal processing and end to end automation across claims and underwriting, but only insurers that invest in scalable foundations will be able to deploy it safely and consistently. AI is becoming an operational capability, not an experiment. ”
#3 Embedded Insurance and API First Distribution Reshape the Market
Embedded insurance has grown rapidly in Europe. Customers increasingly expect protection to be offered at the moment they purchase a product or service. This approach improves conversion and reduces acquisition costs, but it requires insurers to support real-time integration and instant policy creation.
Delivering embedded insurance requires stable, well-documented APIs, fast rating engines, event-driven processes, and modular product components that partners can easily use. Traditional systems cannot support these expectations without significant workarounds, and even then, performance often falls short.
“API first products with real-time rating and modular coverage are essential for integrating insurance seamlessly into partner customer journeys.” Insurance Journal
As more sectors integrate insurance into their journeys, insurers that cannot support fast, reliable connectivity will lose opportunities to more flexible competitors. This shift also forces insurers to rethink their architecture, as embedded distribution depends on a modern, adaptable core.#4 Core Platform Architecture Determines Innovation Velocity
In 2026, an insurer's innovation speed is determined almost entirely by its architecture. Modern platforms use smaller services that can be updated independently. They process events in real time rather than in overnight batches. They connect easily with business partners. And they support unified data models so that analytics and operations work from the same information.
Insurers working on these platforms can introduce new products more quickly, adjust rating logic without destabilising other systems, and respond to changes in customer behaviour or regulation with greater confidence. Those operating on legacy platforms face longer release cycles, more operational risk, and slower learning loops.
“Modern insurance core platforms built on modular, service-based architectures enable faster product delivery, real-time processing, and greater flexibility, while legacy systems continue to slow innovation and increase operational risk.” Insurance CIO Outlook (2025)
Most insurers find themselves in a hybrid state where some parts of the organization run on modern systems while others remain connected to legacy environments. This hybrid model can be effective, but it requires deliberate architectural planning so that it does not become a long-term barrier to innovation.
Ultimately, core architecture determines whether insurers can execute change consistently or remain trapped in incremental progress. It defines how fast new ideas move into production, how safely systems evolve, and how confidently organisations respond to whatever the market, regulators, or risk environment demands next.
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Bojan Pikl, Product Manager at Adacta, commented:
“Core platform architecture directly determines how fast an insurer can innovate: modular, event driven cores enable rapid, low risk change, while tightly coupled legacy systems slow delivery and increase uncertainty. In effect, architecture turns innovation either into a continuous flow or a constrained, stop start process”
#5 Climate Risk Analytics Demand New Models and New Data
Climate events are becoming more frequent and more severe, and they are increasingly breaking the assumptions that traditional catastrophe models rely on. Historical loss data is no longer a reliable predictor of future risk. This requires insurers to adopt more sophisticated modeling approaches.
“The rising frequency and severity of extreme events is widening the insurance protection gap because traditional risk methods based on historical loss patterns fail to capture these changes.” Foresight
New methods combine forward-looking climate scenarios with geospatial analytics, satellite imagery, and high-resolution exposure mapping. Modellers are blending insights from multiple catastrophe model providers to reduce uncertainty. Parametric insurance is gaining traction because it offers fast and transparent payouts that depend on environmental triggers rather than manual assessment.
These approaches demand significant improvements in data infrastructure and governance. They also require insurers to revisit their risk appetite in regions where volatility is increasing. As model complexity grows, the operational workload increases as well. This reinforces the need for more intelligent automation across underwriting and claims.
#6 Automation Offsets Workforce Shrinkage and Operational Pressure
The European labour market is tightening. Specialist roles in insurance are becoming more difficult to fill, and many experienced professionals are nearing retirement. Automation is now crucial to maintain service levels and operational quality.
“European insurers face increasing operational pressure from workforce shortages and an aging talent base, driving the need for efficiency and automation to maintain service quality.” EIOPA
Insurers are using automation to eliminate repetitive tasks, enabling experts to concentrate on complex decisions. Automated document classification decreases manual data entry. Image analysis assists adjusters in estimating damage more consistently. Straight-through processing facilitates faster turnaround for simple claims. Unified workbenches provide underwriters with all relevant information in one place instead of being scattered across multiple systems.
Automation also helps preserve institutional knowledge. As workforce transitions accelerate, the ability to capture decision patterns and embed them into systems becomes just as important as reducing workload.
By stabilising internal operations and reducing reliance on manual effort, insurers build the operational capacity needed to collaborate more effectively with external partners. These internal improvements set the stage for the next force shaping the industry, the shift from simple integrations toward full ecosystem orchestration.
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Beti Ilinčič, Product Manager at Adacta, commented:
“As an expert in claims handling and product management, I see firsthand how automation is becoming indispensable for insurers facing a tightening labor market and an aging workforce. Automation in claims is no longer optional - it’s a strategic necessity. By reducing manual processing time by up to 40%, enabling straight-through processing, and embedding intelligence into workflows, insurers can transform claims from a reactive process into a proactive, data-driven experience that safeguards expertise and elevates service quality.”
#7 Ecosystem Integration Evolves Into Multi-Party Orchestration
Most insurers aspire to participate in digital ecosystems. They want to collaborate more effectively with brokers, MGAs, reinsurers, service providers, and non-insurance brands. The challenge is that true ecosystem orchestration requires far more than basic system connectivity.
Ecosystems operate through continuous data exchange. They depend on consistent documentation, shared event notifications, customer consent frameworks, anonymisation rules, and workflow engines that coordinate activities across multiple organisations. Few insurers today have mastered this level of coordination.
“Digital insurance ecosystems require insurers to manage continuous data exchange, third party dependencies, governance, and operational coordination that extend far beyond basic system integration.”
Those who do succeed approach integration as a product in its own right. They provide well-designed APIs, partner onboarding environments, and standardised interaction patterns. They establish clear commercial rules so that every participant understands their responsibilities and rights.
This shift is reshaping competitive advantage. Insurers that can orchestrate complex ecosystems will have significantly more reach and influence than those that remain limited to bilateral integrations.
Ivana Vukobrat, Product Manager at Adacta added:
“True competitive advantage will belong to insurers that treat ecosystem orchestration as a core operating capability, not a peripheral IT initiative. Those that invest early in governance, standardised interaction models, and scalable integration platforms will be best positioned to control distribution, data flows, and value creation across increasingly complex insurance networks. ”
What This Means for 2026
By 2026, the primary differentiator in European insurance will not be which technologies insurers choose. It will be how effectively they execute the transformation. Modernisation, AI, cloud platforms, embedded insurance, automation, and advanced risk analytics are no longer optional initiatives. They are foundational capabilities.
The insurers that succeed will be those that focus less on isolated projects and more on building execution capacity across technology, operations, and governance. They will invest in architectural foundations, operating models, and skills that allow change to move reliably from strategy into production.
Beyond DORA and the EU AI Act, European insurers face increasing regulatory pressure from CSRD enforcement, evolving Solvency II supervisory expectations, and stricter cyber resilience requirements, all of which reinforce the need for resilient, well governed, and execution ready operating models.
