How to Evaluate AI Vendors: Key Considerations for Insurance and Legal Industries

As artificial intelligence (AI) continues to reshape industries like insurance and legal, selecting the right AI vendor becomes a critical decision for organizations looking to optimize processes like medical record analysis. With a multitude of vendors offering AI solutions, it’s essential to evaluate them carefully to ensure they align with your business needs and regulatory requirements.

This blog will provide some of the key considerations for evaluating AI vendors, helping you navigate this rapidly evolving landscape while ensuring compliance, accuracy, and trust.

1. Accuracy and Reliability: Are the Insights Actionable?

When evaluating AI vendors, one of the first criteria to consider is the accuracy and reliability of the AI’s outputs. In the context of medical record analysis, accuracy means the ability to surface relevant data while excluding unnecessary or irrelevant information. You want an AI tool that delivers relevant data and actionable insights rather than flooding users with overwhelming amounts of data.

Ask the vendor to provide:

• Real-world success stories: How has AI improved efficiency for similar organizations?

For example, Legal & General America used DigitalOwl's AI-powered platform to reduce medical record review times by 60% to 70%, allowing underwriters to understand the contents of a 370-page APS in just 5 minutes. In one-third of the cases, no further review was required, and the platform provided click-to-evidence functionality for easy fact verification, streamlining their workflow and enhancing decision-making accuracy.

2. Transparency and Explainability: How Transparent Is the AI?

Transparency in AI is essential to building trust. When looking for an AI vendor, it's important that they provide full transparency into how the AI operates and the logic behind its decision-making process. Look for tools with features like click-to-evidence functionality, which allows users to trace insights back to their original data sources. This feature ensures compliance and builds trust with users by making the AI’s reasoning process visible.

Ask about:

• Explainability: Does the AI allow users to understand how it reached its conclusions?
• Traceability: Can each insight be linked back to its original data source?

As highlighted in our recent white paper on evaluating AI for medical record analysis, trust starts with transparency. AI systems must be designed with clear governance to ensure they operate within evolving regulatory frameworks, particularly in sensitive industries like insurance and legal.

3. Customization and Fine-Tuning: Can the AI Adapt to Your Needs?

A one-size-fits-all approach rarely works in the insurance or legal industries. Your AI vendor should offer a solution that is customizable and adaptable to your specific workflows. AI that can be fine-tuned by industry experts ensures that the system not only surfaces the most relevant insights but also aligns with the business logic required for each unique case.

Key questions to ask:

• Is the AI customizable to meet the specific needs of your organization?
• How often is the AI updated or fine-tuned by experts?
• Can the system integrate into existing workflows and platforms?

The ability to tailor AI responses based on underwriting, claims, or legal logic is critical to ensuring that the tool provides the most valuable and impactful insights.

4. Bias and Fairness: How Does the AI Address Bias?

AI systems can unintentionally reflect the biases in the data they are trained on. For industries like insurance and legal, this can have serious consequences, such as discriminatory risk assessments. It is crucial that your AI vendor addresses bias proactively and uses diverse datasets to train its models.

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When evaluating vendors, consider:

• Bias mitigation strategies: How does the vendor ensure that their AI minimizes bias?
• Diversity in datasets: Are the AI models trained on a diverse and representative dataset?
• Regular audits: Does the vendor conduct regular audits of the AI system to detect and correct biases?

Ensuring that the AI system is fair and unbiased helps maintain compliance and avoid reputational damage, particularly in regulated industries like insurance.

5. Security and Compliance: Is the AI Vendor Compliant with Industry Standards?

Given the sensitive nature of medical data, it’s crucial that the AI vendor adheres to industry-specific security and compliance standards. In the healthcare and insurance sectors, meeting standards such as HIPAA or SOC 2 Type II is essential. The vendor must ensure the highest levels of data protection and risk mitigation through robust AI governance practices.

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Make sure to ask:

• What security certifications does the vendor hold?
• How does the vendor handle data privacy and protection?
• Does the vendor adhere to key regulatory standards, such as SOC 2 Type II, HIPAA, or GDPR?

As mentioned in our AI Governance Toolkit understanding an AI vendor’s security protocols and governance structures is key to ensuring long-term compliance and data security.

6. Scalability and Flexibility: Can the AI Grow with Your Business?

Finally, your AI solution should be scalable to meet the growing needs of your business. As your company expands or adopts new processes, the AI must be able to adapt and scale accordingly.

Ask the vendor:

• Can the AI solution scale to handle more data as your business grows?
• Does the system offer flexibility to adapt to new processes or use cases?
• How will the vendor support you as your needs evolve?

Ensuring scalability means you won’t outgrow the system, and the AI can continue to provide value as your business matures.

Evaluating AI Vendors with Confidence

Evaluating AI vendors is about finding a partner that not only provides cutting-edge technology but also ensures that their solution is accurate, transparent, customizable, and compliant. By focusing on key factors such as accuracy, transparency, fine-tuning, bias mitigation, compliance, and scalability, you can ensure that the AI vendor you choose will enhance your workflows and drive long-term success.

Progress starts with trust, and selecting the right AI vendor is the first step toward unlocking the potential of AI in your organization.

Want to learn more? Download our recent white paper Evaluating AI’s Reliability in Medical Record Analysis or check out our AI Governance Toolkit.

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