Will intelligent data that automatically integrates and catalogs itself become the standard for business efficiency? Or will real change only come with AI-driven end-to-end automation, which will increase scalability and reduce costs? We should start looking for answers to the question of how artificial intelligence will affect the insurance sector today—so that we can consciously prepare our organizations for the coming changes and the most important trends of 2026.
During the Insurance 2026+ meeting, organized by Britenet and Gazeta Ubezpieczeniowa, I shared my conclusions based on observations of the market in 2025 and forecasts for 2030. Regardless of how far we try to reach in our predictions, one conclusion remains unchanged – artificial intelligence is no longer an experiment, but has become an element of business architecture, which is clearly visible in the insurance industry.
Key takeaways from this article
- Data Fabric and Data Products will be the new foundations of data architecture, enabling insurers to quickly and securely integrate data and prepare it to drive AI and process automation.
- End-to-end automation powered by AI increases scale, efficiency, and customer service quality. However, only those organizations that have prepared their processes, data, and team competencies to work with AI will reap the full benefits.
- Long-term operating models, such as Agentic AI and Touchless Insurance, will change the way decisions are made and customer service is provided. Their effective implementation will require a strategic approach, modern data architecture, and conscious planning of operational transformation.
The year 2026 will not bring a breakthrough in just one technology—it will be the moment when organizations equipped with mature, high-quality data and AI solutions will outperform their competitors. For the insurance market, this means a fundamental change, encompassing data architecture, process design, and the role of humans in their implementation.
Data Fabric and Data Products – new foundations of data architecture
In 2026, the question will no longer be “Do we have data,” but “can we use it in real time?” Traditional solutions, such as data warehouses and siloed integrations, are no longer sufficient in a world increasingly driven by AI. This is a significant challenge, especially since many companies still struggle with the problem of scattered data sources – core systems, CRM, IoT, and cloud environments – which are difficult to combine into a single, coherent picture of customers and processes. That is why one of the main trends of 2026 in the insurance industry is Data Fabric, a coherent layer of data that enables its automatic integration, cataloging, and management in real time.
At the same time, we are seeing an increasingly clear shift towards Data Products, i.e., treating data as a fully-fledged business product. Instead of raw tables, certified data sets are created, with a clearly defined owner, quality level, and method of use. This organization of data enables more effective implementation of AI models, speeds up customer service processes, and facilitates compliance with regulatory requirements. At the same time, it prepares the organization for faster and more efficient implementation of innovations in the future.
End-to-end automation driven by AI is becoming the norm
Today, the market shows that the greatest value comes not so much from a single AI model, but from the automation of entire insurance processes. Large and medium-sized companies around the world are increasingly implementing solutions in which some of the basic tasks—such as claims handling, damage assessment, and customer communication—are performed with minimal human involvement. We can already see examples of successful implementations on the international market.
One British insurance company, a leader in the general insurance sector, has implemented over 80 artificial intelligence models throughout the entire claims settlement process – from reporting a claim, through assigning cases to the appropriate teams, to final operational decisions. Meanwhile, an American insurtech representative has been fully automating approximately 55% of claims in the full cycle, without human intervention, for over a year.
Such solutions not only speed up operations and reduce costs, but also provide customers with convenient and personalized service – a response to their problems 24 hours a day, 7 days a week – which increases their sense of security and, consequently, their loyalty.
The insurance industry in 2030 – the era of Agentic AI and touchless insurers
In the long term, the insurance industry is moving towards full automation supported by AI. According to Gartner's forecasts, by 2029, autonomous Agentic AI systems will be able to independently resolve approximately 80% of typical customer service issues. This means that more and more processes will be carried out autonomously, without human intervention, while maintaining a high level of personalization and regulatory compliance.
In practice, this means that:
- Autonomous AI agent systems will act on behalf of customers—comparing offers, purchasing policies, reporting claims, and negotiating terms.
- Companies will transition to a dynamic, data-driven operating model in which many decisions are made in real time.
- Multi-agent environments will enable the automation of many customer service processes.
The natural direction of this technological evolution is the Era of Touchless Insurance – a model in which insurance processes such as policy issuance, claims settlement, and risk analysis will become almost entirely unattended, operating automatically in the background and in real time.
How can you prepare today for the future of the insurance industry?
The biggest pitfall awaiting insurance organizations is not the lack of technology itself, but the lack of organizational, architectural, and process readiness. Companies that are already investing in modern data architecture, data products, and end-to-end automation are laying the groundwork for scalable and effective use of AI in the coming years.
