How Expert.ai is using hybrid AI to transform the insurance market
October 7, 2025
AI is no longer a side project. It's part of the core product stack across financial services. Property and casualty carriers feel this pressure every day-submission volumes up, margins tight, and talent stretched.
Expert.ai is leaning into that reality with a practical, hybrid AI approach that helps carriers, MGAs, brokers, and TPAs make faster, more consistent decisions. The focus: higher accuracy, lower operational cost, and clear auditability.
The EidenAI Suite: built for the full insurance lifecycle
Expert.ai's EidenAI Suite targets the work that drives P&L: underwriting, claims, policy servicing, and premium audit. The system reads, classifies, and extracts data from unstructured documents, then routes it into your existing workflows-quickly and consistently.
Tackling underwriting where it slows down most
Commercial lines still run through broker email submissions loaded with binders, SOVs, ACORDs, loss runs, and bespoke questionnaires. That's where quotes stall and costs creep in.
- Reads full broker submissions and related documents
- Understands intent and extracts the critical data points for rating and risk selection
- Delivers normalized, structured data to underwriters and core systems
- Cuts reliance on offshore data entry as wage pressure rises
Underwriters stop hunting through unfamiliar forms and start making decisions. Every workflow includes a human-in-the-loop step so teams can review, correct, and trust outputs. That feedback improves models and preserves explainability.
Claims reimagined
Indexing backlogs and misrouted documents drive leakage. Expert.ai classifies and associates thousands of document types to the right claim, then exposes them in the claims system your teams already use.
- Near real-time processing with on-demand scale during CAT events
- 24/7/365 throughput on high-volume inflows
- Accurate routing of sensitive items-like time-limited demands-to the right adjuster
Misclassification isn't trivial. A significant share-estimated at over 20%-of legal demands get mislabeled as general correspondence by manual indexing teams. Getting these right avoids delays that can trigger bad faith exposure and higher loss costs.
Faster policy servicing that keeps accounts
Endorsement requests are a loyalty test. Slow turnarounds send insureds shopping. Expert.ai processes inbound requests quickly and consistently, helping carriers, agents, and insureds stay aligned.
Why hybrid AI wins in insurance
One-size-fits-all AI creates cost and compliance risk. Expert.ai mixes LLMs, generative and agentic models, and neuro-symbolic techniques based on the use case and customer constraints.
- Higher accuracy by matching the method to the task
- Lower cost by reserving heavy models for the few steps that need them
- Traceability and control for regulated workflows
Every call to a large model carries a cost. A hybrid approach keeps total spend down while improving performance where it matters.
What's next: real-time multimodal AI
Expert.ai is investing in R&D to stay aligned with regulatory and compliance requirements while pushing capability forward. A major focus is real-time multimodal AI-combining text, voice, and images-to interpret submissions, photos, and audio notes together and deliver a single, consistent output stream to underwriting and claims.
That means faster intake, fewer handoffs, and clearer decisions at scale.
How carriers can move now
- Pick one bottleneck with measurable leakage (e.g., broker submissions or legal document routing)
- Define "source of truth" fields and quality thresholds
- Pilot with human-in-the-loop and clear SLAs
- Instrument the workflow: touch time, cycle time, accuracy, and rework
- Scale to adjacent lines and document types once KPIs hold
The market rewards speed and consistency. Expert.ai's stance is simple: ship solutions that show immediate P&L impact. As one leader put it, "We work in partnership with our customers… Everything we work on has to have immediate P&L impact for our customers… so they can better serve their stakeholders."
If you're strengthening AI skills across underwriting and claims teams, explore practical upskilling paths here: AI courses by job function.
For broader policy context on AI in UK financial services, see the Bank of England's overview: AI and machine learning.
