Separating the Wheat from the Chaff – A Checklist for Selecting an AI Partner in Insurance

Choosing poorly isn’t just inconvenient—it can cost your company valuable time, drain resources, and potentially damage your career. To help you in this critical decision, we’ve outlined a practical checklist for evaluating AI partners. Whether you’re a CEO, CTO, claims director, or an insurance professional looking to stay ahead of the curve, this guide is designed for you.

Why Selecting the Right AI Vendor Matters

Adopting AI is no longer a choice; it's a necessity for insurance companies aiming to remain competitive. From automating claims processing to improving customer support, the benefits of deploying AI are immense—but only if you’re partnered with a vendor that delivers value and reliability. The reality is, with the rapid evolution of generative AI (GenAI) and large language models (LLMs), many vendors are unproven, promising more than they can deliver. This makes separating genuine innovators from opportunistic “cowboys” critical.

At Simplifai, we’ve worked with insurance companies for over seven years, building solutions for automating claims intake and processing. We’ve seen firsthand what separates a trustworthy AI partner from one that falters when the rubber meets the road. Here’s what to look for in your next AI partner.

1. Longevity and Experience Count

AI might feel like the latest buzzword, but the tech landscape moves quickly, and not all vendors can keep pace. Startups often thrive on bold promises but lack the operational experience necessary to scale or adapt. Look for an AI partner with years of experience under their belt—especially one that’s evolved alongside the tech. Has this vendor successfully transitioned from rule-based AI to NLP and now to generative AI systems? Do they have case studies and proven results with insurance clients? A history of successful adaptation indicates resilience and reliability, qualities essential in this dynamic field.

Key Questions:

• How long has the vendor worked with insurance companies?

• Can they provide specific case studies demonstrating success in claims automation, customer support, or underwriting?

2. Compliance, Security, and Reliability

The insurance industry operates under stringent regulations. From GDPR to ISO27001 to Soc 2, compliance is non-negotiable when handling sensitive data. Vendors cutting corners on these essentials should be instantly ruled out. AI solutions must also be robust, fast, and dependable. They should integrate seamlessly, perform under pressure, and offer business continuity even during high-load scenarios.

What to Ask:

• Does the vendor meet regulatory standards like GDPR, SOC 2, and ISO27001?

• How do they ensure data security and privacy in AI processing?

• Is vendor focusing on industry and region you are into to support upcoming regulation changes?

• What’s their track record for uptime and reliability?

3. Put Their Capabilities to the Test

A common pitfall when selecting AI partners is falling for pitches that sound great on paper but crumble with real-world application. Insurance workflows are complex, requiring an AI solution that performs well under challenging scenarios.

These tests reflect some of the complexity typical in insurance workflows:

• Large PDF Parsing: Can the vendor’s system extract key data from oversized, mixed-content PDFs? This capability is essential for claims processing.

• Structured, Semi structured and Unstructured Data: Insurance workflows often involve both structured (e.g., forms) and unstructured (e.g., free text) data. Ensure the vendor’s AI handles both effectively.

• The Travel Insurance Test: Can the AI process scanned invoices from multiple regions and extract data accurately? This is a litmus test for strong preprocessing capabilities.

Recommendation:

Ask vendors to demonstrate their AI using challenges that mimic your workflows. If they can’t meet your expectations, they aren’t the right partner.

4. Evaluate Orchestration and Integrations

A key element of any AI solution is its ability to integrate seamlessly into your existing systems. Your team shouldn’t have to jump through hoops—or rely entirely on the vendor—to make operational adjustments.

Key Questions:

• Does the platform offer native tools for workflow orchestration without requiring third-party software?

• Does the vendor provide autonomy in system adjustments, or will you rely on them for every tweak?

The right AI partner empowers your team by enhancing flexibility and reducing bottlenecks.

5. The Edge of Human-in-the-Loop and Zero-Shot Learning

For insurance, human-in-the-loop (HITL) functionality is a must-have. While automation is crucial, human oversight ensures accuracy in complex or ambiguous cases. What separates good HITL implementation from great HITL implementation is whether the system incorporates user feedback to improve over time. Pairing this functionality with zero-shot learning—an AI’s ability to perform tasks without additional training data—allows for faster adaptation to new scenarios, a critical edge in the rapidly changing insurance landscape.

What to Evaluate:

• Does the system create feedback loops that improve over time?

• Can the AI make accurate decisions without requiring extensive task-specific training?

6. Bring Your Own Model (BYOM) and Multi-LLM Capabilities

No single large language model (LLM) can tackle every task in insurance. A forward-thinking AI solution should enable running multiple LLMs simultaneously, allowing specialized models for specific tasks. Even better, the system should integrate with your proprietary models. By adopting a modular approach, you’ll avoid vendor lock-in, leverage task-specific optimizations, and future-proof your investment as AI technology evolves.

Consider This:

• Does the platform support task-specific LLM selection?

• Can proprietary models be integrated without overhauling the system?

• How easily can new LLMs be incorporated as they emerge?

Why This Checklist Matters

Choosing the right AI partner feels daunting because it is critical. Missteps can lead to inefficiencies, compliance issues, and even reputational harm. By following this checklist, you’re well-equipped to choose a vendor that’s as innovative as it is reliable.

At Simplifai, we take pride in delivering solutions that meet the highest standards of compliance, scalability, and real-world applicability. We understand the unique challenges of the insurance industry and design AI systems that outperform expectations.

What criteria do you consider essential when choosing an AI partner? Drop your thoughts in the comments—we’d love to hear your perspective! Together, we can build a smarter, more efficient future for the insurance industry, one thoughtful partnership at a time.