SMAR Daily Industry News

Insurers Face Data Trust Hurdles in AI Adoption

As insurance carriers move toward the next phase of artificial intelligence adoption, including agentic AI and automation, the industry faces a critical challenge: data trustworthiness. Speaking at the InsurTech Connect conference in Las Vegas, Chris Newman, CEO of ACORD Solutions Group, emphasized that while AI is capable of making effective business decisions, its success depends on the reliability of the underlying data.

The core issue for insurers involves verifying the origin of information and maintaining accountability for AI-driven decisions. Newman noted that without verified data, companies risk operating within a "black box," where they cannot justify or explain the rationale behind automated outcomes. This lack of transparency poses a significant regulatory risk, as insurers must be prepared to provide evidence for their processes even if regulators do not mandate specific methodologies.

To address these concerns, Newman advocates for a balanced approach that integrates AI with human oversight and established guardrails. He cautioned against automating entire workflows without these necessary controls. However, insurers are also constrained by significant investments in existing legacy systems. Rather than forcing companies to abandon these platforms for new ones, Newman suggested that the industry needs a "bridge" between current infrastructure and future digital capabilities. ACORD Solutions Group aims to facilitate this by helping disparate systems communicate and converting data into trusted, usable formats.

This strategy allows insurers to establish a digital foundation while preserving their existing technology investments. By operationalizing standards and creating a layer of trust, carriers can reduce current industry inefficiencies. Looking ahead, Newman suggests that the most significant opportunity lies in re-engineering end-to-end operating models. Forward-thinking carriers are beginning to move beyond automating isolated tasks, instead using trusted data to rethink how business flows from distribution channels and agents, ultimately creating new digital operating frameworks.

For insurance professionals, this shift signals that the transition from AI hype to practical implementation requires a foundational focus on data integrity. As regulatory scrutiny regarding AI decision-making likely increases, carriers that prioritize transparent, verified data pipelines today will be better positioned to redesign their workflows and gain a competitive advantage in the future.

Why it matters

The ability to verify data sources and explain AI-driven decisions is becoming a regulatory necessity, forcing insurers to bridge the gap between legacy systems and modern digital frameworks.

FAQ

What is the primary challenge for insurers adopting AI, according to Chris Newman?
The main challenge is ensuring the reliability and trustworthiness of the data that supports AI decision-making.

Why does Newman advise against fully automating insurance processes?
He warns that without human oversight and guardrails, insurers risk operating within a 'black box' where they cannot justify or explain decisions to regulators.

How does ACORD Solutions Group propose insurers handle their existing legacy systems?
Instead of requiring a complete platform migration, the firm aims to build a 'bridge' between old and new systems, allowing companies to digitize while preserving their current technology investments.

Source: Insurance Journal. See the original source for full details.