November 25, 2025

In Insurance, AI’s True Value Is Accuracy—Not Just Speed

Justin Fink

VP of Marketing

A dartboard with alternating purple and black sections is centered against a digital-themed background with abstract blue and white geometric shapes.

Recently, TechCrunch published an article, “AI is too risky to insure, say people whose job is insuring risk.”  Needless to say, we have some thoughts about it. 

While the TechCrunch article highlights the insurance industry’s concerns about AI’s unpredictability and systemic risk, it’s crucial to recognize that in sensitive, highly regulated sectors like insurance, the primary value of AI is not speed—but accuracy, reliability, and explainability.

AI Is More Than Just Latency

The recent TechCrunch article, “AI is too risky to insure, say people whose job is insuring risk,” raises valid concerns about the challenges of underwriting AI-related risks. Insurers are right to be cautious about black-box models and the potential for systemic failures. However, the discussion often overlooks a fundamental truth: in industries like insurance, AI’s greatest impact comes not from how fast it operates, but from how accurately and transparently it can support critical decisions.

We believe that accuracy is the baseline for any AI system deployed in regulated environments. In insurance, where decisions affect livelihoods, compliance, and financial stability, the cost of an inaccurate or opaque AI output far outweighs any benefit gained from faster processing alone.

Why Accuracy Matters Most in Insurance

1. Risk Assessment and Underwriting

AI models are transforming insurance underwriting by analyzing vast, complex datasets to deliver more precise risk profiles. For example, insurers using explainable AI platforms have improved both the accuracy and transparency of their pricing and risk models, directly addressing regulatory and audit requirements.

In practice, deep learning models for vehicle damage assessment have achieved up to 99.4% accuracy, reducing human error and ensuring fairer outcomes for policyholders.

2. Claims Processing

Leading insurers have piloted AI systems that process claims with 98% accuracy, matching or exceeding human performance. This not only streamlines operations but also ensures that claims are handled consistently and justly.

3. Fraud Detection

AI-driven fraud detection systems have enabled insurers to identify up to three times more fraudulent activity than traditional methods, minimizing false positives and protecting both the company and its customers.

4. Regulatory Compliance

Regulatory bodies now require that AI systems be explainable, auditable, and fair. Insurers must demonstrate that their models do not introduce bias or make unexplainable decisions—making accuracy and transparency non-negotiable.

AI Accuracy Table
Use Case AI Accuracy Achieved Impact/Outcome
Claims Processing 98% Reduced errors, improved consistency
Vehicle Damage Estimation 99.4% Fairer, more reliable assessments
Fraud Detection 3x more fraud found Fewer false positives, better risk management

Addressing the “Black Box” Concern

The TechCrunch article rightly points out that insurers are wary of AI’s “black box” nature. At You.com, we tackle this head-on by prioritizing explainability and transparency in every AI deployment. Our enterprise AI agents are designed to provide citation-backed, auditable answers—empowering insurers to understand, trust, and validate every decision.

Beyond Insurance: A Broader Industry Standard

This focus on accuracy isn’t unique to insurance. In healthcare, finance, and legal sectors, regulatory frameworks demand that AI systems be accurate, explainable, and reliable. For example:

  • Finance: AI-driven credit and fraud models are subject to rigorous validation and must be explainable to regulators.
  • Legal: AI document analysis tools must ensure compliance and avoid introducing legal risk through errors.
  • Healthcare: AI diagnostic tools must match or exceed clinician accuracy and provide clear audit trails.

You.com’s Commitment: Accuracy, Reliability, and Trust

At You.com, we’ve built our platform to meet the highest standards of accuracy, security, and compliance. Our enterprise AI agents are:

  • Benchmark-leading in accuracy for complex, real-world business queries.
  • SOC 2 certified and designed for zero data retention, ensuring data privacy.
  • Customizable and transparent, allowing insurers to tailor AI to their unique workflows and regulatory needs.

Make AI Work for Your Org

The insurance industry’s caution around fast AI is understandable, but the solution is not to avoid AI altogether—it’s to demand and deploy AI that is accurate, transparent, and reliable. In regulated industries, speed is only valuable when paired with uncompromising accuracy and explainability. The future of AI in insurance—and beyond—depends on building systems that are not just fast, but fundamentally trustworthy.

We’re committed to delivering AI that meets these standards, empowering insurers to manage risk confidently and compliantly in a rapidly evolving landscape. To learn more, book a demo. 

Featured resources.

All resources.

Browse our complete collection of tools, guides, and expert insights — helping your team turn AI into ROI.

A person standing before a projected screen with code, holding a tablet and speaking, illuminated by blue and purple light.
AI Agents & Custom Indexes

Why Agent Skills Matter for Your Organization

Edward Irby, Senior Software Engineer

February 26, 2026

Blog

Illustration with the text “What Is P99 Latency?” beside simple line-art icons, including a circular refresh symbol and layered geometric shapes.
Accuracy, Latency, & Cost

P99 Latency Explained: Why It Matters & How to Improve It

Zairah Mustahsan, Staff Data Scientist

February 25, 2026

Blog

Modular AI & ML Workflows

How to Add AI Web Search to n8n

Tyler Eastman, Lead Android Developer

February 24, 2026

Blog

Abstract circular target design with alternating purple and white segments and a small star-shaped center, set against a soft purple-to-white gradient background.
Modular AI & ML Workflows

Give Your Discord Bot Real-Time Web Intelligence with OpenClaw and You.com

Manish Tyagi, Community Growth and Programs Manager

February 20, 2026

Blog

Blue graphic background with geometric lines and small squares, featuring centered white text that reads ‘Semantic Chunking: A Developer’s Guide to Smarter Data.’
Rag & Grounding AI

Semantic Chunking: A Developer's Guide to Smarter RAG Data

Megna Anand, AI Engineer, Enterprise Solutions

February 19, 2026

Blog

Clothing rack seen through a shop window, displaying neatly hung shirts and tops in neutral and dark tones inside a softly lit retail space.
AI Agents & Custom Indexes

4 AI Use Cases in Retail That Demonstrate Transformation

Chris Mann, Product Lead, Enterprise AI Products

February 18, 2026

Blog

Graphic with the text “What Is a Forward-Deployed Engineer?” beside abstract maroon geometric shapes, including concentric circles and angular line designs.
AI Agents & Custom Indexes

The Forward-Deployed Engineer: What Does That Mean at You.com?

Megna Anand, AI Engineer, Enterprise Solutions

February 17, 2026

Blog

Abstract glowing network of interconnected nodes and lines forming a curved structure against a dark blue gradient background with small outlined squares floating around.
Modular AI & ML Workflows

What is n8n? A Beginner's Guide to Workflow Automation

Tyler Eastman, Lead Android Developer

February 13, 2026

Blog