What Insurance Carriers Should Ask Their AI Vendors

A client recently described the current state of AI vendor scrutiny as akin to "doing due diligence in a funhouse mirror." The sentiment resonates deeply, especially within the insurance sector, where the integration of artificial intelligence is no longer a strategic aspiration but an operational imperative. This isn't just about vetting a new software package; it is about embedding capabilities that can fundamentally alter risk posture, impact customer trust, and, if mishandled, invite significant regulatory attention. The questions insurance carriers must pose to their AI vendors are not merely technical; they are foundational to the enterprise's long-term resilience.

Why Your AI Vendor Questions Matter Now

We have entered an era where the lines between technological advancement and core business risk are increasingly blurred. For insurance carriers, this fusion is particularly acute. The rapid proliferation of AI, especially large language models, has compressed the threat landscape. Attackers now possess tools that democratize sophisticated social engineering, making credible impersonation accessible and scalable. This shift changes the economics of fraud and manipulation, transforming what once required extensive human effort into a near-instantaneous, high-volume operation. The organizations that perceived IT risk as solely an 'IT problem' are finding themselves a year or more behind competitors who embedded security thinking into their digital transformation from the outset.

It is easy to get caught up in the headlines recounting breaches or large-scale data exfiltrations. Those are lagging indicators. The more telling signal, for those attuned to it, is the burgeoning internal search traffic on corporate intranets: queries like "insurance claims workflow AI policy" or "LLM data handling protocol." These are the quiet skirmishes on the front lines, revealing where executives and mid-level managers are grappling with the practical implications of integrating AI into their mission-critical processes. They are trying to build the foundational protections for a technology that fundamentally alters access and authority, often without a clear blueprint.

The Threat Pattern in Practice

The notion of a 'single bullet' solution in security is a persistent, if ultimately false, hope. Here, too, no isolated control offers complete protection against a determined adversary. Instead, effective defense is a carefully constructed latticework of controls, each designed to incrementally increase the cost and complexity for an attacker. The objective is to elevate the "price" of a successful attack to a point where the return on investment for the attacker diminishes significantly, prompting them to seek easier prey. This principle is not new; it underpins almost every other facet of information security. What is distinctive is *where* these defenses must now be applied.

In the field, this vulnerability often manifests along paths optimized for legitimate convenience. Think of the IVR less as a phone tree and more as an unauthenticated API. Consider the manager override for an expedited claim, the self-service portal for policy changes, or even the after-hours support channel designed to keep operations flowing. Adversaries are not merely looking for weak links; they are methodically surveying these designed-for-flexibility workflows, much like an auditor would, but with malevolent intent. They arrive at these points of least resistance first, because they represent the soft underbelly of efficiency. The most powerful predictor of a successful attack isn't the sophistication of the attacker's tools but rather the absence of friction once they initiate an interaction within a trusted workflow. We often find that the very mechanisms intended to streamline customer experience become the most attractive attack vectors.

What Effective Defense Looks Like

The unique challenge in communications security, particularly in an AI-augmented landscape, is its intimate connection to the customer experience. Implementing traditional cybersecurity controls, like adding an extra factor to a login, is a familiar, if occasionally inconvenient, trade-off. However, introducing friction into a customer's phone call or a digital interaction, particularly one involving AI, often elicits greater business resistance. This is where the strategic balance must be struck: how to secure these interactions without alienating the customer or impeding legitimate business. Achieving this balance requires robust data, which in turn demands continuous measurement and an integrated security program, not a series of one-off projects.

Our guiding maxim, which we impress upon our clients, is simple: "raise the cost." We do not advocate for the impossible goal of absolute prevention. Instead, the aim is to render a successful attack sufficiently expensive-in terms of attacker time, resources, and specific preparation-that the attacker diverts their attention to a less fortified competitor. This strategic calculus is identical to that which informs every other mature security program. When applied systematically and with discipline, rather than as an ad hoc response, it provides a powerful bulwark against evolving threats.

Practical Next Steps for Your Team

For organizations beginning to construct this framework or those looking to validate existing measures, the initial step often involves a holistic Communications Security Assessment. This evaluation establishes a baseline of current vulnerabilities and operational risks, providing the data necessary to inform subsequent program development and resource allocation.

If there is one actionable insight to take from these observations, let it be this: Conduct a focused, constrained review. Document the specific actions a single inbound customer interaction can trigger within your most sensitive operational workflow. Then, critically assess whether each of those actions would withstand a determined impersonation attempt. This exercise invariably uncovers a short, prioritized list of high-impact changes. These are not about deploying new, complex technologies; they are typically about refining existing processes or adding judicious points of verification, modifications that often deliver a significant return on investment within a single fiscal quarter.

What We Are Watching Next

Looking forward, the management of AI-related risk, especially concerning impersonation and deepfake technologies, will increasingly migrate beyond the sole purview of the information security team. We anticipate this responsibility diffusing across operations, legal, and – perhaps most critically – customer experience departments. This decentralization of ownership is a healthy and necessary evolution. It is a trend that progressive organizations are planning for now, integrating it into their organizational design, rather than reacting to it under duress. We will continue to share our observations from the field as this pattern solidifies across industries.