The insurance sector is undergoing one of the most profound transformations in its history, and cloud technology is at the heart of it. The shift is accelerating far more quickly than most insurers anticipated. Sollers’ global customer survey from 2021 predicted that by 2030, eight of the ten largest insurers in every market would rely on cloud solutions. In fact, developments in the insurance industry are progressing even faster.
One of the most disruptive changes cloud providers bring to the insurance industry is easy access to advanced AI. Instead of developing expensive, complex models from scratch, insurers have started to utilize readymade AI capabilities offered by hyperscalers. This enables rapid automation of claims processing, modernisation of customer contact channels (via dialogue-oriented AI) and faster, data-driven underwriting decisions. The real revolution, however, lies in agentic AI. Cloud providers have revolutionised traditional automation and created autonomous AI agents that can plan and execute complex workflows – such as handling an entire claims process from initial claim reporting to settlement negotiations – with minimal human supervision. Agentic solutions could also be implemented outside the cloud, but providers offer an entire ecosystem of tools, frameworks and orchestration layers that make these agents efficient, secure and scalable.
Cloud providers also solve the problem of "data silos" by leveraging data mesh concepts that offer data as a product, self-service data access, bundled governance and much more. This approach enables specific business areas – such as claims processing and underwriting – to own and curate their data while making it easily discoverable and usable for the rest of the organisation or even external partners. By leveraging data lakes, data catalogues and other interoperable services, insurers can gain a holistic view of the customer without the bottlenecks that occur with traditional data warehousing solutions. Insurers can also create a single source for big data, saving costs for transfer between different consumers (BI, reporting tools, other clouds). It is possible to perform advanced real-time analytics on large data sets, which was not previously possible with a local legacy infrastructure.
The third reason why cloud has become so important for insurance is its scalability. Insurance is a business of peaks and valleys: renewal seasons, catastrophic events, and shifting market cycles. The pay-as-you-go model of cloud computing is perfectly suited to this variability. Insurers can scale instantly when demand spikes without paying for unused infrastructure.
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Governance and explainability become decisive factors
Security is often cited as a problem, but it is in fact one of the cloud's greatest strengths. Providers invest billions in security measures that individual companies cannot match. They offer advanced tools for identity management and real-time detection of suspicious activity, which is critical for protecting sensitive policyholder data from cyber threats.
The ability to automatically implement regulatory safeguards is now a basic requirement. Insurers choose providers that enable them to define policies centrally and apply them globally. If a provider cannot demonstrate automated "prevention" of non-compliant applications (e.g., preventing data exchange outside the EU), it is typically disqualified from central insurance tasks. Cloud providers have developed a wide range of tools for AI model explainability. Here is an overview of the existing solutions:
AWS offers Amazon SageMaker Clarify. It detects biases in data prior to training and explains model predictions (e.g., "The claim was classified as high risk primarily due to characteristics X and Y")
Azure offers the Responsible AI Dashboard, a tool that is highly valued for its user-friendly interface that enables companies to understand model behaviour
GCP stands out with Vertex AI Explainable AI, offering feature attributions and the "What-If Tool," which insurers can use to simulate how changes in data points (e.g., a change in the age of a car) would affect risk assessment
Beyond tools, each provider has built comprehensive governance frameworks. Azure’s Responsible AI Standard v2 maps to EU AI Act requirements. Through its Well Architected ML Lens AWS provides architectural guidance for its services. Google focuses on rigorous documentation via model cards and integrates AI governance with cybersecurity through its Secure AI Framework (SAIF) – a strong fit for insurers building complex, bespoke models.
The fifth reason why cloud has become so attractive are audit capabilities AWS pairs automated evidence collection with on-demand access to its own compliance reports. Google’s Access Transparency alerts insurance customers in real time when support engineers access their data – an important feature for European insurers concerned about extraterritorial access. Azure integrates cloud and Microsoft 365 activity streams, offering unified visibility into user behaviour. Insurers are not just buying servers. They are buying the ability to prove their systems are secure, their data sovereign and their algorithms fair.
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Turning complex insurance data into real business value
Michał Litwiński - UK Project Manager
