Insurers are investing more in technology than ever before (1). AI, cloud, automation: the ingredients for efficiency and scaling are there. And yet? Many promising projects remain stuck in the pilot phase. The question is no longer whether the potential is there - but why it often remains untapped. Those who take automation seriously in 2025 can create real competitive advantages now.
From proof of concept to real benefits
According to recent studies, only around a quarter of companies make the step from successful AI piloting to sustainable, productive use (2)(6). We see this time and again in the insurance industry in particular: smart ideas, strong individual initiatives, but a lack of bridges for integration into the line organization. What is missing is not technology. It is the structured transition from innovation to impact.
The potential is tangible and has been proven many times over: Automated claims processing, intelligent risk assessment, contract processes without media discontinuity - all of this can be realized today (3)(4). Companies that implement this report noticeably shorter processing times, reduced error rates, significantly relieved teams and measurably higher customer satisfaction (4)(5). In short: less effort, more impact.
Automation is not an IT project
What makes these projects successful is rarely the algorithm alone. The decisive factor is the interaction between technology, processes and people. An organizational "operating system" is needed that consciously links these three dimensions:
- Change management: AI changes job descriptions, roles and expectations. If you don't involve employees, you risk uncertainty and resistance. Good projects invest in communication, support and dialog right from the start.
- Data readiness: Bad data leads to bad decisions. Data quality is not a downstream issue, but the basic prerequisite for any automation (3).
- Production maturity: A good prototype is a start. But only with monitoring, governance, clear responsibility and a well thought-out operating model can it become a viable productive system (6).
What counts now: Three impulses from practice
1. scaling instead of tinkering
Pilot projects have their value. But they remain worthless if there is no clear path to scaling. Successful organizations define handover points early on, build a robust target architecture and establish MLOps processes (Machine Learning Operations processes) with continuous monitoring, A/B testing and feedback loops (6).
2. actively shaping change
Automation does not mean replacing people. It means: Relieving people. Training, clear objectives and the involvement of teams turn skepticism into productive energy. Those who actively support change create trust and stability (5).
3. simplify technology
Cloud-based platforms create the basis for speed and autonomy. They allow specialist departments to implement their own automation ideas without long waiting times in IT. This promotes ownership, innovation and operational effectiveness (1)(3).
Our conclusion at wibas
Automation is not an end in itself. But it is a powerful lever for doing what insurers are particularly good at: Calculating risks, managing complexity, creating customer proximity. AI makes this faster, more data-based and more resilient (4).
2025 should be the year in which "We are currently testing something" becomes "We are scaling successfully". Companies that make the transition now will not only secure efficiency gains - but also future viability.
And this is exactly where we support you: in a structured, practical way, together with your teams.
Sources
[1] KPMG - Insurance industry: How to implement AI successfully
[2] CIO.com - 88 % of AI pilots fail to reach production - but that's not all on IT
[3] Deloitte Germany - AI in insurance companies
https://www.deloitte.com/de/de/Industries/insurance/perspectives/ki-in-versicherung Company.html
[4] KPMG - Non-life insurance: Increasing efficiency with generative AI
[5] WTW (Willis Towers Watson) / WTW & Insurance Industry 2025 - AI in the insurance industry: How insurers are taking the next step
[6] REVARTIS - Why 88% of AI pilots stall. Learn how to bridge the gap from strategy to scaled impact
https://revartis.com/insight/beyond-the-ai-pilot/
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