Overview
Conversations about artificial intelligence in insurance often center on major global corporations, high-end platforms, and technology pilots from Silicon Valley. However, the actual use of AI spans more grounded contexts.
AI is reshaping insurance with faster claims, smart underwriting, and fraud detection—even in emerging markets like Ukraine, where adoption is steadily growing, according to Arsenal Insurance data.
AI plays a growing role in everyday processes—informing decisions, managing risks, and handling claims.
Artificial Intelligence is increasingly transforming the insurance sector by automating processes, enhancing decision-making, and improving customer service.
AI refers to computer systems designed to perform tasks that typically require human intelligence, such as recognizing speech, making decisions, and interpreting data.
AI in Practice: Daily Use and Internal Integration
Over the past year, AI tools have become a standard part of my routine. I use them to monitor market activity, prepare internal documents, and organize competitor data that previously required hours of manual work.
In essence, they serve as constant support, handling analytical tasks quickly and consistently. Arsenal Insurance has also started applying AI to core operations.
Notable examples include:
- Automated underwriting to reduce turnaround times and improve accuracy
- Remote claims handling through image-based damage evaluation
- Use of diagnostic algorithms in health insurance to refine pricing and offer early medical insights
Effective Applications and Limitations
AI delivers clear benefits in areas such as:
- Underwriting that draws on behavioral and historical datasets
- Fast claims handling
- Scalable actuarial modeling
- Pattern-based fraud prevention
Still, the main obstacles are not technical. In Ukraine, AI-related regulations remain unclear, which leads to hesitation around full automation of critical decisions.
Companies also weigh customer expectations and data privacy concerns. In such an uncertain legal environment, many choose a more conservative approach.
This reluctance is understandable. A similar pattern occurred in the early days of digital banking, which now operates as a standard part of everyday life.
AI promises to revolutionize how property and casualty insurance business gets done. The exact ways AI will influence business are unknown.
Disruption and regulation will certainly result, but it remains to be seen whether property and casualty insurers will follow or use AI as a means to lead.
Focus on People, Not Just AI Tools
Assumptions that AI replaces people overlook how it actually supports their work. Communicating this remains key.
We’ve introduced workshops that explain the tools and their purpose. As employees begin using them and see time savings and fewer repetitive tasks, concerns tend to drop.
However, internal change needs structured leadership. Some staff express anxiety or fatigue from constant updates. Clear communication and leading by example remain important.
AI exposures within traditional insurance policies possess the ability to become a significant and unexpected risk towards an insurer’s portfolio.
According to Munich Re research, the insurance market is undergoing a remarkable transformation, thanks to the exponential growth of artificial intelligence in insurance.
With AI comes this kind of systematic accumulation risk potential, especially if one model is being utilised across similar use cases across different companies.
Another area to consider is in the domain of copyright infringement risks with generative AI models.
Comparing Regions: Ukraine and Western Markets
Western insurers have more advanced AI deployment—such as near-instant claims approval—but that does not mean Ukraine lacks ambition.
Our position allows us to avoid mistakes seen in early-stage models and focus on what works.
Being later to implement AI also creates an opportunity to build with insight from other markets.
Business leaders and insurers quickly learned the best technology was the most responsibly developed technology (see How Insurers Can Get Best Results from Artificial Intelligence Tools?).
Internet companies know customers need an environment that protects them from ransomware. And the risk-based pricing behind insurance enabled businesses to manage the risks each technology presented.
Start Where You Are
AI enhances performance. It does not replace human input but improves speed and precision.
Waiting for perfect conditions slows progress. Industry leaders should begin with existing tools and scale gradually. The essential part is to include staff at every stage of the shift.
Future insurance operations will rely on cooperation between humans and machines—not competition.
Digitalization is changing the role of insurance, from pure risk protection towards predicting and preventing risks.
FAQ
AI supports underwriting, claims assessment, fraud detection, pricing models, and market analysis. It helps insurers process large volumes of data and make faster, more consistent decisions.
Examples include computer vision for damage analysis, predictive analytics for pricing, natural language processing for customer service, and automation for underwriting.
No. AI performs repetitive tasks and supports data analysis, allowing employees to focus on higher-level work. Most companies position AI as a tool to assist staff, not eliminate roles.
Main issues include unclear regulations, low public trust in automated decisions, limited access to training data, and internal resistance due to unfamiliarity with new tools.
Yes. Insurers must manage sensitive personal and medical data. Without strong legal guidelines, companies often avoid full automation to reduce potential risks involving data misuse.
Successful companies use clear communication, training sessions, and leadership involvement to build confidence. Demonstrating the practical value of AI tools reduces resistance over time.
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AUTHOR: Mykhailo Hrabovskyi – Head of Regional Division at “Arsenal Insurance”
