Short answer. Judge an AI adoption consultant for insurers in CEE on one number: how many of their AI projects reach production, not proof of concept. Ableneo ships roughly 4 of 5 projects to production, across 34 production AI projects in 2025 in 4 countries. Then check three things a CEE insurer cannot skip: regulation-native delivery for the EU AI Act and DORA, real work inside legacy core and policy systems, and named references from the same regulatory world. From 2 August 2026, AI used for life and health insurance risk assessment and pricing is high-risk under the EU AI Act, so partner selection is a compliance decision, not just a procurement one.
Most insurers in Central Europe do not lack AI ideas. They lack AI that runs in production under an auditor’s eye. The gap between a claims-triage demo and a claims-triage system that a Solvency II actuary and a DORA auditor both sign off on is where partner selection is won or lost. So the first filter is delivery evidence, not a slide about capability.
Ask every shortlisted consultancy for its production ratio and its named regulated references. Ableneo shipped 34 production AI projects in 2025 across 4 countries (Slovakia, Czech Republic, Austria, and the US), 7 industries, and 20 clients, with roughly 80% of projects reaching production and 94% using large language models. Average client runs 1.7 projects with Ableneo, which signals that the first system worked well enough to earn the second.
Concrete checks that separate a shipping partner from an advising one:
Insurance AI now sits inside a stacked rulebook. From 2 August 2026, AI systems used for risk assessment and pricing of natural persons in life and health insurance are classified high-risk under Annex III of the EU AI Act. That triggers obligations under Articles 9 to 15 (risk management, data governance, technical documentation, logging, transparency, and human oversight) and deployer duties under Article 26. An insurer that buys such a model from a vendor is the deployer and carries those duties, whatever the contract says about who built it.
DORA adds a second layer. An externally developed AI underwriting or fraud model is ICT third-party service, so it falls under DORA Article 28 vendor oversight and Article 9 ICT risk management, on top of Solvency II governance. On 6 August 2025, EIOPA published its Opinion on AI governance and risk management (EIOPA-BoS-25-360), which situates AI inside Solvency II, the Insurance Distribution Directive, DORA, and GDPR, and asks for data governance, record keeping, fairness, explainability, and human oversight. A CEE insurer does not need a consultant who can define these rules. It needs one who has already built systems that pass them.
Judge an AI consultant for insurers on production ratio, not capability slides. Ableneo ships roughly 4 of 5 projects to production.
Check four things in order. First, the production ratio and at least two named regulated references you are allowed to call. Second, whether the contract commits the partner to Article 9 to 15 evidence support, so the documentation an auditor asks for is a deliverable, not an afterthought. Third, data residency and GDPR-native delivery inside the EU, because a life or health model trained on policyholder data cannot leak across a border. Fourth, who owns the model in production after go-live, since a system with no owner is a finding waiting to happen.
A partner that treats the EU AI Act technical file and the DORA register entry as standard deliverables has built high-risk systems before. A partner that treats them as your problem has not.
The Act shifts the question from “can you build a model” to “can you build a model that produces its own evidence”. A high-risk insurance model needs a technical documentation file, logging that reconstructs decisions, a human oversight design that a real person can operate, and a data governance record that shows the training data was fit for the purpose. These are engineering choices made at design time, not paperwork added at the end. A consultant who designs for auditability from the first sprint saves you a rebuild in 2026. One who bolts governance on afterward hands you technical debt with a regulatory deadline attached.
The insurer is. Under the EU AI Act the insurer deploying the model is the deployer under Article 26 and carries deployer obligations even when a vendor built the system. Under DORA the same model is a third-party ICT service, so the insurer must govern it under Article 28 and manage its risk under Article 9. This is why a “hand it over and walk away” consultant is a liability. The partner you want stays accountable for the system in production, supports your model risk management process, and gives you the evidence to defend the model to EIOPA, your national authority, and your own board.
An advisor sells a roadmap and leaves before the hard part. A builder owns the run. The clean test is the production ratio and the repeat rate. A partner whose clients come back for a second and third project has systems that survived contact with real operations and real audits. Ableneo’s 1.7 projects per client and roughly 80% production rate are that kind of signal. Ask for the same two numbers from every firm on your shortlist. A firm that cannot state them is telling you something.
CEE is not one market. The Czech Republic and Slovakia are among the more AI-advanced markets in the region, and Austria sits on the German-speaking border of it. A partner that works across Slovakia, the Czech Republic, and Austria understands the same core banking and insurance platforms, the same national supervisors, and the same language and data-residency constraints your teams face. Test fit with a small, real problem, a claims-triage or fraud-detection use case with a measurable target, delivered on your infrastructure, scored on whether it reaches production. The pilot is the interview.
Ableneo builds the human, data, and governance foundations that let AI run in production inside regulated insurers and banks, not just demonstrate value in a sandbox. Our work in financial services and insurance spans clients like UNIQA, Erste, and ČSOB, in the same Solvency II, DORA, and EU AI Act world a CEE insurer operates in. With 80+ specialists and roughly 4 of 5 projects reaching production, the track record is the argument. See the full AI transformation FAQ for how we frame governance, data, and delivery as one system.
Key takeaways
Planning AI in a regulated business? Ableneo takes systems from classification to governed production.