How We Introduce Artificial Intelligence in the Insurance Sector
How can we safely introduce artificial intelligence into the insurance sector? In 5 steps, with humans at the helm.
Artificial intelligence in the insurance sector doesn't start with technology. It starts with a choice: do we use AI because we can, or because it makes things better for our clients? At Group Induver, that answer was clear from the start. Only the second one counts.
That sounds simple. Putting it into practice is less so. The insurance sector is an environment where trust, compliance, and human judgment are non-negotiable. Introducing AI into an environment like that takes more than buying a license and letting people work with a new tool. It requires an approach. A framework. And the discipline to stick to your principles, even when faster or cheaper shortcuts are available.
Step 1: First Understand, Then Act
We didn't start with the question "which AI tool should we use?", but with "what do we want to achieve, and for whom?" Only once that was clear did choosing a tool actually mean something.
For Group Induver, the answer was clear: AI must empower our employees so that they have more time for what truly matters: the conversation with the client, the complex file, the advice that is spot-on. No more, no less.
Starting from that goal, we deliberately chose professional, secure AI solutions like Claude. No free consumer tools. The reason is a matter of principle: anyone responsible for client data and client interests can't work with tools where that data gets processed outside the organization without any guarantees.
Step 2: First Train People, Then Roll Out Tools
Artificial intelligence in the insurance sector stands or falls with well-trained employees. This is not just our conviction; it is European law.
Since February 2, 2025, the European AI Act (Article 4) obliges every organization using AI to ensure its employees are sufficiently AI-literate. This obligation applies to everyone working with AI: from claims handlers to advisors, and from marketing professionals to executives. Anyone who cannot demonstrate this is already non-compliant today.
Group Induver is leading the way in this regard. We invested early in training, guidance, and awareness for our colleagues. Not as a reaction to a mandate, but out of the conviction that AI only adds value when the people using it understand what it can do, and what it cannot do.
Every colleague at Group Induver can request a professional AI license. More than 80% of our employees already have a license, 68% use it weekly, and 50% daily. That is no coincidence. It is the result of a structured AI implementation where training and access went hand in hand.
Step 3: Start Small, Learn, and Scale Up
We deliberately chose a phased introduction of AI in the workplace. No large-scale rollout of unproven systems, but targeted pilot projects with measurable goals.
Because we strongly believe in the added value of artificial intelligence in the insurance sector, we set up our own AI team.
They continuously look at which tasks are repetitive and time-consuming, and then try to automate them. To do this, we train AI skills and deploy intelligent AI agents (agentic AI). The output is carefully evaluated.
Two examples:
Automatic Settlement: Automated Handling Of Workplace Accident Files
We started with one well-defined process: handling workplace accident files. Structured, repeatable, and with clear quality criteria. The result: AI processed 1,058 files, 91% fully automatically, with over 95% accuracy. That freed up 20 working days our team can now spend on personal client contact, complex files, and quality advice.
Analysis Bundle: Automated Policy Analysis And Comparison
In a second test, we wanted to cut down on manually retyping policy data into comparison tables. Our AI application read and compiled the data automatically. The result for our employees? Fewer errors and more time for quality advice.
Both applications started small, proved their value, and are now being rolled out further. That's the only responsible way to do it.
Step 4: Always Keeping Humans at the Helm
The European AI Act imposes strict requirements on human oversight, transparency, and explainability for high-risk AI applications, which include risk assessment and claims processing systems in insurance. These requirements formally apply as of August 2026. Group Induver already applies them as a standard today.
In concrete terms, this means that AI output is always validated by an employee. Doubtful cases are always assessed by a human. And the ultimate responsibility for a decision always lies with a person, never with an algorithm.
This is not a brake on innovation. It is the only way artificial intelligence in the insurance sector can build long-term trust—with clients, with regulators, and with our own employees.
Step 5: Innovation in a Secure Sandbox
In addition to the implementation within Group Induver, we are building Ōmata in parallel: a completely new, AI-first insurance broker of the future. We deliberately develop from scratch, free from the limitations of legacy systems.
Ōmata is our innovation platform: new technology and forms of service delivery are tested there in a shielded, controlled environment. What works there and proves its value, we bring back to Group Induver. In this way, we combine the benefit of radical innovation with the security of a controlled rollout.
Why This Is the Only Logical Approach
The insurance sector is under growing pressure to implement AI quickly. The temptation to follow what others are doing, or to let speed take priority over diligence, is real.
But artificial intelligence in the insurance sector isn't a choice between speed and safety. It's a choice for sustainable value creation.
Anyone who introduces AI without a framework, without training, and without human oversight is building on shifting sand. Anyone who does it responsibly builds a foundation that can be built on for years to come.
Assuralia, the Belgian professional association of insurers, confirms this: the sector embraces AI as an evolution, not a revolution, with the human factor as its anchor. The European AI Act gives this framework its legal foundation. Group Induver gave it substance well before that.
Frequently Asked Questions About Artificial Intelligence in the Insurance Sector
How Does Group Induver Introduce Artificial Intelligence in the Insurance Sector?
Group Induver deploys artificial intelligence in the insurance sector with strict safeguards for data security, human oversight, transparency, and compliance. In doing so, we select, test, and validate AI applications within a clear framework, rather than on the basis of hype or speed.
How Does Group Induver Safely Introduce AI Into Its Own Operations?
Group Induver introduces AI safely via a five-step plan: we define goals, train employees, execute targeted pilot projects, keep humans at the helm for validation and ultimate responsibility, and we test innovative AI applications in the protected environment of Ōmata before rolling out successful applications across the entire group.
What Does the European AI Act Mean for AI in the Insurance Sector?
Since February 2, 2025, the AI literacy obligation applies: employees working with AI must have sufficient knowledge of both the opportunities and the risks. As of August 2026, strict requirements apply to high-risk AI applications, such as claims processing and risk assessment: transparency, human oversight, and the explainability of decisions are mandatory.
Why Does Group Induver Choose Professional AI Tools Instead of Free Alternatives?
Group Induver chooses professional AI tools because free consumer tools do not offer sufficient guarantees for processing confidential client data. Professional solutions include contractual agreements regarding data processing, security, and compliance. This is not just an ethical choice; it is also a requirement under the GDPR and the European AI Act.
How Does Group Induver Keep the 'Human in the Loop' Across AI Applications?
Group Induver keeps the 'human in the loop' by always having AI output validated by an employee. Doubtful or complex cases are always assessed by a human. The ultimate responsibility for decisions always rests with our employees. This applies to all AI applications, even when the level of automation is high, such as in automated claims handling with 91% straight-through processing.
What Is the Difference Between Rolling Out AI at Group Induver and at Ōmata?
At Group Induver, AI is embedded into existing processes and client relationships, with strict validation and a phased rollout. At Ōmata, the AI-first insurance broker of the future, AI is built into all processes right from the start. Ōmata functions as an innovation sandbox: complex experiments are tested in a controlled environment, allowing proven applications to be safely transferred to Group Induver afterward. Naturally, nothing goes into production that is not 100% secure and of the highest qualitative standard.
What Are the Risks of AI in Insurance if It Is Not Implemented Safely?
The risks of artificial intelligence in the insurance sector are substantial: data leaks due to the use of uncertified tools, incorrect decisions resulting from insufficient human oversight, reputational damage among clients and regulators, and legal sanctions under the AI Act. Anyone who implements AI without a framework and without training builds on quicksand.
How Do I Know as a Client That AI Is Being Used Safely at Group Induver?
As a client, you know that AI is being used safely because Group Induver works exclusively with professional, certified AI solutions, applies strict frameworks for data and compliance, trains employees in AI literacy, and guarantees human oversight on all AI-supported decisions. The European AI Act establishes these obligations legally. Group Induver is already applying them.
Why Is a Phased Approach the Right Way to Implement AI in Insurance?
A phased approach is the right way because it allows for learning in a manageable environment, detecting errors early, and making adjustments before they have a large-scale impact. It gives employees time to adapt and build trust in new tools. Furthermore, it allows the value of an application to be proven with measurable results before it is scaled up. This is precisely how Group Induver works: starting small, learning, and scaling up responsibly.
Questions? Contact Us.
Do you have questions about our vision on AI, or how we deploy AI to serve you even better? Please feel free to contact us.
