The promise of automation in claims has been on the industry agenda for years. But how far have European insurers actually come? To find out, Adacta surveyed 110 senior insurance decision-makers across DACH, Eastern Europe, the UK, France, Spain, Portugal, and Benelux in late 2025. What emerged is a picture that is more honest than the industry narrative often suggests: meaningful progress in some areas, persistent gaps in others, and a clear sense of where the insurance industry is heading next.
This post summarises the key findings from the State of Claims Automation Market Study 2026.
Table of contents:
Most European insurers are still in the early stages of claims automation. Over 80% describe their current level as moderate or lower, and the largest single group (36%) relies on basic automation in isolated areas only. Just 17% have reached a high or very high level.
This reflects a wider pattern. The majority of organisations (82%) have not yet reached an advanced level of digital transformation overall. With 41% still at a moderate stage, digital processes in some areas, but far from enterprise-wide, is not lagging in isolation. It is progressing at roughly the same pace as digital transformation more broadly.
Not all parts of the claims handling value chain are equally automated. The data reveals a clear pattern: customer-facing and detection activities lead, while back-office decisioning lags behind.
FNOL intake is the most automated step, cited by 58% of respondents. Fraud detection follows at 49%, and customer experience touchpoints, including communication, at 43%. Further down the chain, adoption drops sharply. Reserve setting is the least automated stage, cited by just 17% of respondents.
On the technology side, established automation tools dominate. Chatbots and data analytics dashboards are each used by 58% of respondents, while Robotic Process Automation (RPA) and AI/Machine Learning (ML) models are each used by 44% of organisations. Newer capabilities, such as computer vision (27%), telematics and IoT (24%), and generative AI (24%), remain at an earlier adoption stage.
Generative AI is attracting significant attention, but most insurers are still in an exploratory phase. Only 6% of respondents say they have no plans to use GenAI, making interest near-universal. However, actual deployment is limited: just 26% are currently using or piloting generative AI in their insurance claims operations.
The largest group (37%) is actively exploring use cases for the next 12 months. A further 30% are monitoring the space without immediate plans to act.
This suggests that machine learning and artificial intelligence are technologies broadly accepted in principle, but where practical implementation remains work in progress. The gap between interest and deployment reflects both the genuine complexity of integrating GenAI into claims handling processes and the broader barriers to automation.
When asked what is holding back further automation, three challenges dominate the responses:
Skills gaps (38%), resistance to change (30%), and regulatory concerns (30%) each affect roughly a third of organisations.
When respondents described specific lessons from automation projects, data quality was the single most common theme: one in four cited incomplete records, duplicates, and unstructured documents as primary obstacles. Legacy system incompatibility and skills gaps followed.
The most effective solutions respondents pointed to were platform-level capabilities, including validation checks, centralised data models, and real-time dashboards, alongside clear implementation of roadmaps and hands-on training. These are not surprising findings, but they reinforce a consistent message: automation initiatives that underinvest data foundations and change management tend to struggle.
One of the most telling findings in the study is the gap between the benefits insurers expect from automation and what they have actually observed so far. Across all seven benefit areas measured in the survey, expected importance outpaces observed results by 23 to 34 percentage points.
The widest gaps appear in:
This does not mean automation is failing to deliver. It means that most organisations are still in early stages and have not yet captured the full value that more mature deployments can generate. The gap is an indicator of unrealised potential as much as unmet expectation.
Supporting this interpretation: over 80% of respondents report that a quarter or fewer of their claims processing decisions are fully automated. Just over half (51%) automate 10% or less of decisions. Only 8% have reached a level where more than half of decisions happen without human review.
Human oversight remains standard. The largest group (41%) uses Artificial Intelligence in an advisory role only. A further 34% allow automated decisions for low-risk insurance claims but maintain human oversight on exceptions. Only 6% employ extensive automation with minimal human intervention.
Regulatory readiness is another area where the gap between intent and action is visible. Only 19% of respondents say they are actively aligning their automated claims processing practices with emerging AI regulations, such as the EU AI Act. The majority (51%) have taken initial steps but acknowledge significant work remains.
Nearly a quarter (23%) report limited awareness of relevant regulations, and 7% are entirely unfamiliar with them.
This is a meaningful risk. As AI becomes increasingly embedded in claims process, affecting coverage determinations, fraud flags, and settlement values- regulatory compliance is no longer a future concern. It is now an operational requirement.
Despite the challenges, the outlook for investment is unambiguously positive. 80% of respondents expect their spending on claims AI to increase over the next two years, with 34% anticipating significant budget growth. No respondent plans to decrease investment.
When asked which innovation areas they are prioritising for the next two to three years, the answer is clear: replacing or modernising the core claims system is the consensus top priority. Among those who selected core system modernisation, 45% ranked it first and 80% placed it in their top two. No other category came close.
A second tier of priorities are STP expansion, data analytics, and new data source integration, each feature as top-two priorities for roughly a quarter to a third of respondents.
Looking specifically at where respondents expect the greatest business impact by 2027, three areas stand out: fraud detection and prevention (16%), faster claims processing and settlement (15%), and AI document review and analysis (14%). Together, these account for nearly half of all responses, pointing to a near-term focus on both risk reduction and operational throughput.
The State of Claims Automation Market Study 2026 paints a consistent picture. European insurers broadly accept that automation and Artificial Intelligence are essential to the future of claims. Investment intentions are strong. But the distance between current state and potential remains substantial.
The most advanced organisations are moving toward genuine straight-through claims processing, leveraging Robotic Process Automation (RPA) and AI to reduce manual touchpoints. The majority are still building the foundations: modernising core systems, improving data quality, developing the skills and governance structures that scalable automation requires.
The implication for insurers is not that progress is too slow. It is that the path forward is clearer than ever. The barriers are known and, to a significant extent, solvable. Organisations that treat core system modernisation, data quality, customer experience and regulatory readiness as parallel workstreams, rather than sequential ones, are best positioned to close the gap between expectation and result.
This article covers the headline findings from Part 1: State of Claims Automation Market Study 2026. The complete report, including detailed regional breakdowns by European regional markets and as well as line-of-business analysis, will be published on our website in April.