We hear it all the time from our customers
‘We want to embrace AI BUT…’
That’s when the blockers to AI adoption start to surface.
We've helped insurance companies overcome their AI adoption challenges and want to share 3 common barriers we frequently encounter:
Let's explore these challenges and discuss approaches to addressing them.
Many teams don't know where to start—and that's perfectly normal. The recurring theme is that they want to do it right and responsibly. The key question is are you implementing a single model or tool, or is this a broader enterprise digital transformation initiative to govern all AI models?
Many successful teams begin with one high-impact model or a few critical ones that directly affect the bottom line. Then, focus on scaling the groundwork for a robust governance program.
Focus early on establishing a clear, structured approach to AI governance and give yourself time. At Monitaur, we refer to this as the Define stage of governance. Many organizations face challenges in this phase, including inconsistent AI definitions, an overemphasis on GenAI, and decentralized teams working without proper risk oversight.
To address these challenges, Monitaur provides comprehensive solutions through our Corporate AI Governance Policy Template, Risk Assessment Methodology, and Control Library. This structured approach ensures organizations can move forward confidently while maintaining proper oversight.
AI Governance Tip #1: Start with a project that is connected to key company-level objectives
As regulatory scrutiny of AI systems intensifies, insurance carriers need proven frameworks for responsible AI implementation. Bonus if those frameworks understand the finer points of regulation within the industry. With AI models growing more complex and central to critical business processes, structured governance isn't just beneficial—it's essential.
For example, ISO 42001 has emerged as a particularly valuable framework for insurance organizations. Developed by the International Organization for Standardization (ISO) and the International Electrotechnical Commission (IEC), ISO 42001 provides insurance carriers with a comprehensive blueprint for responsible and ethical AI governance. This international standard is particularly important as states like Colorado already recognize it as an acceptable risk management framework in their legislation.
It's crucial for insurance companies because:
While ISO 42001 helps carriers demonstrate compliance, implementation requires more than checking boxes. Success demands two crucial steps: identifying gaps in your current AI management system (whether using Open Pages, Excel, or another solution) and establishing comprehensive controls. Both steps require deep governance and industry expertise.
That's why our customers rely on our pre-built Common Controls Library, which maps directly to ISO 42001. For complete regulatory alignment, Monitaur's controls also pre-map to NIST AI RMF, the NAIC Model Bulletin, and various state legislation.
AI Governance Tip 2: Look for pre-mapped out-of-the-box controls to accelerate compliance and to reduce overhead.
Trust is the foundation of successful AI adoption in claims processing, building upon clear starting points and regulatory compliance.
In the claims environment, trust must extend across multiple stakeholder groups. Adjusters need confidence that AI tools will enhance—not replace—their expertise. Customers need assurance of fair and transparent claims handling, with AI improving rather than diminishing service quality. For leadership and shareholders, trust comes through demonstrated ROI and compliance—showing that AI governance isn't merely a regulatory requirement but a strategic advantage that improves accuracy while reducing processing times and costs.
Building trust requires a methodical approach that aligns operational goals with regulatory requirements. Through robust governance frameworks, insurers can monitor AI performance, prevent bias, and maintain high accuracy standards. This proactive approach to governance both protects against risks and accelerates the benefits of AI in claims processing.
At Monitaur, we combine robust governance software with deep insurance expertise to help carriers build trust at every level. Our platform provides the visibility and control needed to confidently deploy AI solutions, while our team's industry knowledge ensures you're making informed decisions that align with both business objectives and regulatory requirements.
AI Governance Tip 3: Build trust through transparency by documenting AI decisions and maintaining open communication among technical teams, claims adjusters, and leadership.
Implementing AI in claims processing doesn't need to be overwhelming. Success comes from three key elements: identifying the right starting point, ensuring regulatory compliance, and building trust across your organization. Our software and expertise with enabling AI projects through governance has been recognized as one of the only end-to-end governance solutions by Markets and Markets, complementing our deep insurance expertise.
Whether you're starting with a single model or planning an enterprise-wide transformation, the right governance framework is crucial for successful adoption:
Ready to unblock AI adoption? Schedule a demo with our team today to learn how you can accelerate your AI journey while maintaining compliance and building trust.
