The rapid acceleration of artificial intelligence in the insurance sector is creating a dangerous disconnect: carriers are automating decisions faster than they can verify the information underlying those decisions. New research from Clearspeed, a voice-based risk assessment provider, reveals that insurers are deploying AI to streamline claims, underwriting, and customer interactions while simultaneously failing to build the verification infrastructure necessary to ensure the integrity of the data flowing through these automated systems. The report, titled “The Speed of Trust: Building the Trust Intelligence Layer for Insurance in the Age of Agentic AI,” exposes a widening verification gap that threatens to undermine the efficiency gains that AI promises, leaving genuine customers caught in a system that cannot distinguish between legitimate claims and sophisticated fraud.
The Verification Gap: Automation Outpacing Infrastructure
The research identifies a central paradox at the heart of the insurance industry’s digital transformation. Insurers are automating decisions, handoffs, evidence review, and customer interactions at an unprecedented pace, but they are not keeping up with the infrastructure required to clear those interactions confidently. At the same time, AI is making it faster and easier to create convincing false or manipulated photos, documents, voices, and identities that can seamlessly enter insurance workflows. This dual movement, accelerating automation alongside advancing fraud capability, creates a gap that the industry is only beginning to recognize.
The report was independently authored by insurance innovation strategist Sabine VanderLinden, chief executive officer of Alchemy Crew Ventures, and commissioned by Clearspeed. It draws on a review of 76 public filings from 49 insurers and reinsurers, 31 industry studies, and 16 interviews with claims and underwriting leaders across the United States and United Kingdom. The findings paint a stark picture of an industry racing forward without a clear view of the risks accumulating behind it.
Reserving Against a Risk Not Yet Named
One of the most striking findings is that the formal risk disclosure mechanisms of the insurance industry have not yet acknowledged AI-generated evidence as a material threat. Researchers searched 76 annual reports, 10-K filings, proxy statements, and statutory returns for a dozen terms related to AI-generated and manipulated evidence, media, and imagery. The analysis found zero mentions of synthetic media, synthetic identity, or voice cloning across all 76 filings. Only six of the 49 companies mentioned deepfakes, and even then exclusively as a cybersecurity concern, never in connection with evidence used in claims or underwriting decisions. Of the five of the world’s top 10 reinsurers analyzed, none mentioned deepfakes, synthetic media, or AI-generated evidence in their most recent annual reporting.
This silence is particularly alarming given the scale of the threat. Industry research published in March 2026, based on a survey of 300 US insurance claims professionals, found that 98% agree AI editing tools are driving a rise in digital media fraud, while only 32% say they are very confident they could identify a deepfake. “There is a striking gap between where this risk is discussed and where capital is committed,” said VanderLinden. “In the filings that set reserves, uncertainty, litigation pressure, and adverse development are all named. The trust problem beneath them is not.”
That is the verification gap: the distance between what the industry can see coming and what it can currently detect. Insurance is automating decisions faster than it can verify the information behind them.
Genuine Customers Paying the Price for the Trust Deficit
The consequences of this gap are not abstract. According to the Coalition Against Insurance Fraud, fraud accounts for roughly 10% of property and casualty losses, with the trust deficit draining at least $308.6 billion annually from the US insurance system. However, the deeper issue is not simply the cost of fraud. Until insurers have a consistent way to determine which interactions need speed, scrutiny, or human judgment, the industry pays for trust twice: once through leakage from the few bad actors, and again through friction imposed on the genuine majority.
Ian Thompson, former group chief claims officer at Zurich Insurance, captured the dilemma succinctly in his interview with researchers. “90%+ of customers who make a claim are honest, good people for whom we should be just sorting out their service needs as quickly as possible,” he said. “But how many of those genuine customers get the feeling that they’re not being trusted, because we’re trying to catch the other 10%?” This friction erodes customer satisfaction and loyalty, creating a hidden cost that compounds the direct losses from fraud.
Building a Trust Intelligence Layer for the Insurance Industry
VanderLinden argues that the solution lies not in deploying more AI to catch more fraud, but in making trust a measurable infrastructure layer across the policyholder journey. The report proposes establishing a Trust Intelligence Layer: a continuous, regulator-ready risk indicator that runs across the policyholder journey, designed to help insurers clear the genuine majority quickly while directing human judgment to the exceptions. This signal informs a decision rather than making one, produces an audit trail rather than an automated denial, and does not require demographic or historical knowledge of the individual being assessed.
“In the age of agentic AI, deepfake evidence, embedded distribution, and automated workflows, insurers can no longer treat trust as a soft value or a late-stage consideration,” said VanderLinden. “The opportunity for carriers is to establish trust earlier and make it a measurable operating layer across the policyholder journey.” This approach shifts the paradigm from reactive fraud detection to proactive trust verification, embedded within the workflow rather than bolted on as an afterthought.
Alex Martin, co-founder and chief executive officer of Clearspeed, emphasized the strategic importance of trust in the age of AI. “Trust is our most vital currency: it is the hardest thing to gain and the easiest thing to lose,” he said. “Today’s promise of AI should yield a faster, richer experience for genuine customers, but that must begin with verifying where to extend trust.”
The Future of Trust in Agent-to-Agent Insurance Interactions
The report looks ahead to 2030, when a material share of insurance interactions will be agent-to-agent: a customer’s AI agent transacting with an insurer’s AI agent, at machine speed, with no human in the loop for routine business. In that world, the verification question does not disappear; it migrates and intensifies. When the action is always executed correctly, the question left is whether the interaction behind it can be trusted. The report describes this as a shift in what gets verified, not whether verification is still needed.
As more insurance interactions become AI-to-AI, the human input behind each transaction still has to be trusted before automated systems act on it. Insurers will need an auditable way to establish that trust at the moment of interaction, and the organizations that build that capability now, while interactions are still human-led, will define the standard when those interactions become machine-to-machine. The report concludes with a stark warning: the arms race is symmetrical, and the only durable advantage is to establish trust earlier and faster than the adversary can manufacture doubt.
The research from Clearspeed and Alchemy Crew Ventures makes clear that the insurance industry is at a critical juncture. The rapid adoption of AI has opened the door to unprecedented efficiency, but it has also created a verification gap that, if left unaddressed, will erode the very foundation of trust upon which insurance depends. Insurers that act now to build a measurable trust infrastructure will not only protect their bottom lines but will also deliver the faster, richer experience that genuine customers deserve. Those that delay will find themselves caught in a cycle of increasing fraud, mounting friction, and eroding customer confidence, paying for trust twice and gaining neither speed nor security in return.
