Automating Table of Benefits and Provider Network Inquiries with Voice AI: Our #1 AI in Insurance Use Cases for Service Providers

Insurance Member Services at a Breaking Point

According to McKinsey’s latest research, 70% of insurance executives identify customer service automation as their top digital priority, yet only 23% have successfully implemented comprehensive AI solutions. The numbers tell a stark story: the average health insurance provider handles 12-15 member inquiries per policyholder annually, with 65% focusing on basic coverage and provider network questions. For a mid-sized insurer with 500,000 members, this translates to 6-7.5 million annual interactions requiring substantial human resources to maintain baseline service levels.

This operational bottleneck represents more than just an efficiency problem—it’s a competitive disadvantage in an era where consumers expect instant, Amazon-like service experiences. Forward-thinking insurance providers are discovering that automating table of benefits and provider network inquiries isn’t just a cost-saving measure—it’s their gateway to transformational AI in insurance use cases that drive competitive advantage.

Why Traditional Approaches Are Failing

Insurance member services are collapsing under unprecedented inquiry volumes that traditional staffing cannot cost-effectively handle. With each inquiry requiring 8 minutes of agent time, mid-sized providers consume 800,000-1,000,000 agent hours annually at $35 per hour, representing $28-35 million in operational expenses that grow as member bases expand. Beyond volume, accuracy has become critical due to regulatory ramifications, as a 2023 Accenture report reveals that 20% of insurance interactions involve errors that trigger disputes, compliance violations, and erosion of trust, ultimately impacting member retention.

Consumer expectations have fundamentally shifted, with J.D. Power research showing that customers now expect resolution times of 2-3 minutes, compared to 8-12 minutes five years ago. This expectation gap, combined with fragmented multi-channel experiences where members must repeat information across phone, mobile apps, websites, and WhatsApp, creates frustration that drives plan switching during enrollment periods. For providers operating on thin margins, this combination of volume pressure, accuracy requirements, speed expectations, and channel inconsistency makes traditional service approaches unsustainable.

AI Use Cases in Insurance: Intelligent Query Resolution

The most successful AI in insurance use cases start with a simple principle: automation should support—not replace—human expertise. At NextLevel.AI, we apply this principle through intelligent voice AI agents that handle routine insurance member inquiries with unmatched speed and accuracy.

These agents identify the user, retrieve their policy and provider network details, and clearly explain what’s covered and where the member can receive care. After understanding the member’s intent, the agent instantly answers questions about benefits, hospital access, or eligibility. If the member’s issue remains unresolved, the agent triggers a hot transfer to a human representative, passing along full context to avoid repetition or delays. This automation significantly frees up time for live agents, while enhancing the service experience and consistency.

Our solutions of AI in Insurance Use Cases are deployed across five active Table of Benefits implementations with insurance providers and third-party administrators in the UAE, KSA, and Qatar. All systems are designed to meet stringent PDPL and local compliance standards, particularly in regulated sectors such as BFSI (Banking, Financial Services, and Insurance).

But implementing AI in insurance use cases is not without real challenges, and they must be acknowledged to ensure responsible, scalable deployment.

Key Challenges of AI in Insurance Use Cases

• User data privacy concerns: Members may be uncomfortable with their personal or health-related information being stored on external servers, while also expecting real-time conversations in their preferred language with answers that are strictly aligned with their policy terms—no approximations or generic replies. 
• Speech-to-text limitations and errors: No model can yet ideally recognize every language or dialect, especially in multilingual regions like the Gulf. This leads to frustration, miscommunication, and a decline in trust.
• LLM unpredictability: Large language models are non-deterministic, meaning you can’t fully control or predict their outputs, which introduces risk in compliance-sensitive contexts.
• Cybersecurity and local compliance regulations: Organizations must navigate complex cybersecurity requirements and region-specific compliance standards, which can vary significantly across jurisdictions and may conflict with standard AI deployment practices. 

These issues are not hypothetical. They’re the primary reasons many insurers hesitate to implement automation despite clear business value.

Results of Our AI in Insurance Use Cases

At NextLevel.AI, we directly address each of these concerns. Our solutions are built on regionally hosted infrastructure to ensure data sovereignty and compliance with privacy regulations. We apply advanced multilingual tuning and guardrails to prevent hallucinated answers and enforce strict logic flows aligned with approved policy data. This ensures that automation improves accuracy—not just efficiency—and supports predictable, audit-ready outputs.

The results speak for themselves:

• 80% automation of the routine table of benefits and provider network questions
• 70% faster average response time
• 65% reduction in repeat inquiries
• 45% improvement in first-call resolution
• 35–50% reduction in operational support costs

Members benefit from 24/7 multilingual availability, culturally aware voice and text interaction, and instant clarity on what their plan includes—all without waiting on hold or navigating fragmented channels.

We will be happy to share results and onboard you as a company that refuses to fall behind – one that’s ready to embrace the power of AI for the benefit of your insured members, while increasing operational efficiency and scalability.

If you’re ready to deliver better experiences at scale while reducing costs and operational load, we’re here to help. Book a call to explore how NextLevel.AI can support your transformation.

Frequently Asked Questions