Why AI Governance Is Essential for Organizations

Artificial Intelligence (AI) is changing how insurance works, from processing claims to spotting fraud and handling customer data. For insurance companies and claims stakeholders adopting technology, it has become a daily part of doing business. 76% of US insurers are already using generative AI, but only 45% feel confident the benefits outweigh the risks. As AI use grows, so do concerns about fairness, accuracy, and accountability.

With new laws on the rise and clients expecting more oversight, businesses need to be thoughtful about how AI is used. Clear governance, strong compliance practices, and keeping people involved in high-impact decisions are no longer optional. These are now the basics for building systems that are powerful and trustworthy.

What Is AI Governance and Why Organizations Should Care

AI governance means putting the right rules and processes in place to guide how AI is built, used, and overseen. It covers everything from how systems are trained to how outcomes are reviewed and who takes responsibility. The goal is to make sure AI stays fair, safe, and grounded in real-world needs.

For teams working with AI in insurance, this matters more than ever. In 2024, US federal agencies introduced 59 AI-related regulations, more than double the year before and coming from twice as many institutions. Strong governance helps companies navigate shifting rules, reduce bias, and earn confidence with clients, partners, and regulators.

AI Regulations Are Coming Into Place

AI regulations are advancing quickly, and for organizations working across regions, that brings new challenges. In the US, a 2025 executive order moved away from federal oversight to promote innovation. This change left many firms navigating a growing mix of state-level laws without a clear national standard.

At the same time, the US government is raising expectations. In April, the Office of Management and Budget called on agencies to strengthen AI governance and ensure people stay engaged in decisions that affect public services. Many states followed by proposing laws focused on transparency, accountability, and safety in advanced AI. For insurers and claims teams, this points to a future where responsible AI use is expected, not optional. Strong internal standards are becoming a key way to align with policy and build long-term trust.

The Role of Human-in-the-Loop AI in Insurance Compliance and Accuracy

Despite the hype surrounding the efficiency of AI in automating tasks, many are still hesitant to adopt this approach. In high-stakes industries such as claims and legal, technology should support people, not replace them. A  human-in-the-loop (HITL) approach adds a layer of human expert review that supports validating AI’s decisions, by catching errors, flagging bias, and making sure actions can be explained and adjusted when needed.

This is most important in high-stakes areas like underwriting, claims, and health data. A recent study found that combining AI with human oversight can process 300-page claims in minutes with around 99% accuracy, saving companies over 1.3 million dollars a year by reducing mistakes and rework. Wisedocs’ own survey report in partnership with ALM Property & Casualty 360 surveyed claims professionals on this very matter and found that HITL was a 4x trust multiplier when expert human oversight is added to AI outputs. The insights are clear: HITL gives organizations a practical way to maintain compliance, protect users, and reinforce reliability in how their AI systems work.

The Future of AI Governance in Insurance

Looking ahead, the rules around AI are only going to continue to develop. Keeping up with new laws, having clear processes in place, and making sure people stay part of important actions can help your team avoid problems and strengthen credibility along the way. These choices shape how your AI performs, how it’s understood, and how your organization shows up in this changing landscape.