Insurance facing AI: a highly exposed sector

If there is one industry where artificial intelligence will not just be an optimization tool but a lever for total transformation, it is insurance.

The “Advancing AI across Insurance” report (KPMG, 2025) reveals that 57% of insurance organizations consider AI the most important technology to achieve their ambitions over the next three years.

Why? Because the profession relies on four fundamental functions — all of which are directly exposed to AI.

1. Customer service

Insurance is built on a promise: being there when the client needs it. Customer service is therefore both a matter of trust and an operational act.

In reality, it covers:

• Underwriting and pre-sales (advice, guidance, instant pricing),
• Policy lifecycle management (endorsements, certificates, renewals),
• Claims handling, the moment of truth when the protection promise must be honored.

These interactions require speed, precision, and empathy. Customer expectations have skyrocketed: instant availability, real-time information, personalized exchanges.

AI becomes a force multiplier:

• Enhanced chatbots to cut response times and absorb volumes.
• Virtual assistants to manage simple requests and escalate complex cases.
• Sentiment analysis to flag sensitive situations and adapt interactions.

2. Contractual documents

The contract is the DNA of insurance. Each policy generates a heavy flow of documents:

• Regulatory files (terms & conditions, IPID, information notices),
• Supporting documents (driving records, licenses, Kbis, IDs),
• Endorsements and certificates throughout the policy lifecycle.

This corpus must be captured, verified, indexed, and restituted without error. Yet manual checks are slow and error-prone.

AI excels here:

• Coverage gap detection and claims guarantee verification: AI compares guarantees, limits, and exclusions between contracts to instantly identify risks of non-coverage.
• Insurance-specific OCR to transform PDFs into usable data.
• Intelligent field extraction and validation (dates, policy numbers, license plates).
• Real-time compliance verification to reduce errors and delays.

3. Big Data

Insurance is a business of information and risk calculation. Pricing and underwriting decisions increasingly depend on vast datasets:

• Internal data (claims history, portfolio trends, payments),
• Partner data (solvency scoring, telematics, IoT, weather, health),
• Open data and external sources for client and environmental enrichment.

The challenge is no longer volume but structuring and intelligent exploitation. Non-standard formats, silos, and lack of interoperability limit value.

AI breaks through these barriers:

• Mass ingestion of internal, partner, and open data.
• Weak signal detection to anticipate fraud and emerging risks.
• Dynamic, personalized pricing in real time.

4. IT and core systems

The backbone of insurance is its information systems: policy admin, broker extranets, accounting tools, regulatory databases. Most players still rely on legacy systems, built for stability rather than agility.

Problem: AI requires real-time flows, modern APIs, and data governance. Legacy silos slow innovation and expose systemic weaknesses.

With modern IT platforms, AI can deliver:

• Productivity gains by automating back-office processes.
• Faster deployment of new products and services.
• Scalability to handle new volumes and AI-driven operations.

Conclusion: a sector that must be ready

Because its four critical functions — customer service, contracts, data, IT — are precisely those AI transforms, insurance is one of the sectors most exposed to the AI revolution.

Those who implement the right infrastructures, data foundations, and compatible platforms will take the lead. The rest will remain stuck at the pilot stage.

At Korint, we bring a clear vision: helping the market cross this gap, making AI operational and impactful.