Effective AI Governance for Insurance Claims Solutions

February 18, 2025 / 5 min read

AI is transforming claims processing at a rapid pace, and insurers are taking notice. A recent survey of over 100 industry professionals—ranging from insurance carriers to agencies and tech firms—revealed that 78% plan to increase their tech budgets in 2025. Among them, 36% have made AI their top investment priority.¹

The Growing Role of AI in Claims

As AI adoption accelerates, insurers are actively exploring its potential in claims processing. About 30% of firms have already implemented AI-driven tools, and many more are considering how generative AI can fit into their workflows. However, budget constraints and regulatory uncertainties may slow the pace of expansion.²

The biggest opportunities lie in customer-facing services, such as claims management and customer experience.²But with AI’s rapid evolution comes a growing responsibility to manage risks—ensuring reliable outputs, preventing bias, and keeping up with evolving compliance requirements.³ A recent survey by the SAS Institute found that 59% of insurance professionals are concerned about the ethical implications of AI, underscoring the need for strong governance.⁴

Addressing these matters is essential to keeping customers’ trust, encouraging staff to adopt AI solutions, and protecting an organization’s reputation. When implemented responsibly—with transparency, fairness, and regulatory alignment—AI has the power to create significant value for insurers and their policyholders alike.

Building a trusted platform

As rapid advancements in GenAI spark new ideas in innovators across industries, it’s critical to ensure a strong foundation of research and development in responsible AI and AI governance policies. These capabilities, joined with the ability to train models using decades of data management expertise, can/will enable a leap forward in efficiency and accuracy in document review.

Workforce challenges are also accelerating the push for AI-powered automation. Reports suggest that the U.S. insurance industry could lose up to 400,000 workers by the end of next year.⁵ In response, insurers are turning to AI to ease administrative burdens and allow adjusters to focus on complex decision-making.

As insurers navigate evolving market dynamics, the rapid advancements in GenAI are reshaping claims management, driving efficiency in medical record analysis and decision-making. By automating complex data extraction and summarization, AI reduces the burden of manual review, allowing adjusters to focus on higher-value tasks. Solutions like Verisk’s Discovery Navigator™ help streamline workflows and improve accuracy in severity assessment and settlement evaluation. Yet, as AI adoption accelerates, so do the challenges—raising important considerations around responsible implementation, data integrity, and evolving regulatory landscapes.

Recognize the hurdles

Even with AI’s benefits, insurers recognize the challenges that come with it. 95% of polled industry professionals expect to face at least one AI-related risk in the coming year.⁶

The top concerns include:

AI hallucinations and bias – Generative AI that is trained solely without human expert input can sometimes produce false information or reinforce biases in training data. However, with expert-guided model development, insurers can mitigate these risks and improve reliability.
Lack of transparency – AI models can function like "black boxes," making it difficult for insurers to explain or justify AI-driven decisions.
Unclear purchasing considerations – Many insurers struggle to determine the right questions to ask when evaluating AI solutions.
Resource constraints – Developing, managing, and regulating AI tools requires dedicated time and expertise.
Gaps in vendor risk assessment – Traditional vendor evaluation processes may not fully account for AI-specific risks.

Without clear governance, these challenges can slow down AI adoption—or worse, lead to unintended consequences that undermine trust.

The successful outcomes of AI systems and projects

At Verisk, we’ve embedded governance controls throughout the AI development lifecycle—from initial ideation to continuous production oversight. Our approach brings together medical experts, model developers, business stakeholders, and risk teams to ensure that AI applications remain transparent, fair, and compliant. Our governance framework focuses on:

Data quality assurance – Ensuring AI models are trained on reliable, representative data.
Bias detection and mitigation – Identifying and reducing potential biases in AI outputs.
Performance monitoring – Continuously assessing AI models for accuracy and reliability.
Ongoing documentation and oversight – Keeping detailed records of AI decisions and adjustments.

With a strong governance framework in place, insurers can build confidence in AI-powered claims solutions while ensuring ethical and responsible use.

Partnering with the experts in AI Governance

Beyond internal governance standards, it can be beneficial to align with emerging AI regulations and standards. According to Gartner, by 2027, 75% of AI platforms will integrate AI governance as a key competitive advantage.⁷

Governance isn’t just about having policies in place—it’s about ensuring accountability, risk management, and regulatory compliance. Industry frameworks like the National Association of Insurance Commissioners’ (NAIC) Model Bulletin and the National Institute of Standards and Technology’s (NIST) AI Risk Management Framework provide essential guidelines for insurers. At the time of this writing, 21 states have fully adopted the NAIC’s Model Bulletin, requiring insurers to implement written policies for the responsible use of AI.

To reinforce our AI governance approach, Verisk has partnered with Monitaur, a leading AI governance provider for the insurance industry. Since 2019, Monitaur has demonstrated a clear commitment to helping regulators, vendors, and the broader insurance industry move forward on the topic of AI governance. Their solutions help companies define, manage, and responsibly automate governance that businesses, consumers, and regulators can trust.

“Leveraging robust validation and documentation practices, such as those provided by Monitaur, help build transparency into AI and GenAI development, making it easier to address customer concerns with confidence. This supports broader conversations about responsible AI governance—conversations that are essential as we explore the evolving landscape of AI” said Carrie Barr, President of Casualty Solutions at Verisk.

Through Monitaur’s proprietary control library, Verisk has aligned Discovery Navigator’s AI governance with NAIC, NIST, and other industry standards. This collaboration assures customers of the integrity and reliability of AI-driven claims processing.

“We view AI governance not just as a regulatory checkbox. When a strategic framework is in place, it also guides best practices, and yields better outcomes,” said Anthony Habayeb, CEO of Monitaur. “With this framework, companies can act on top AI priorities and ethical innovation, while ultimately fostering trust in new technologies.”

Taking the long view

As AI regulations continue to evolve, insurers must stay proactive. Governance isn’t a one-time initiative—it’s an ongoing process that will define the future of AI in insurance.

At Verisk, we’re committed to not just keeping pace with these changes but helping shape the industry’s approach to responsible AI. By maintaining strong governance controls, we ensure that secure, transparent, and trustworthy AI solutions are available for insurers.

Learn more about Discovery Navigator here.

Learn more

Frank Gargano, "2025 Insurance Tech Trends: AI, Big Data and Cautious Adoption," Digital Insurance, January 28, 2025, https://www.dig-in.com/news/2025-insurance-tech-trends-ai-big-data-and-wary-adoption.
Patricia L. Harman, "Predicting the Future for Insurance: Areas to Watch in 2025," Digital Insurance, January 21, 2025, https://www.dig-in.com/research-report/predicting-the-future-for-insurance-areas-to-watch-in-2025.
Frank Gargano, "2025 Insurance Tech Trends: AI, Big Data and Cautious Adoption," Digital Insurance, January 28, 2025, https://www.dig-in.com/news/2025-insurance-tech-trends-ai-big-data-and-wary-adoption.
"Your Journey to a GenAI Future: An Insurer’s Strategic Path to Success," SAS Institute Inc., published 2024, https://www.sas.com/en/whitepapers/your-journey-to-a-genai-future-an-insurers-strategic-path-to-success-114043.html.
Kenneth Araullo, "US Insurance Sector to Lose Around 400,000 Workers by 2026," Insurance Business America, November 14, 2023, https://www.insurancebusinessmag.com/us/news/breaking-news/us-insurance-sector-to-lose-around-400000-workers-by-2026-466593.aspx.
Patricia L. Harman, "Predicting the Future for Insurance: Areas to Watch in 2025," Digital Insurance, January 21, 2025, https://www.dig-in.com/research-report/predicting-the-future-for-insurance-areas-to-watch-in-2025.
Gartner, "Top 5 Tech Trends Propelling Digital Transformation in the Insurance Industry by 2026," https://www.espire.com/blog/posts/gartners-5-top-tech-trends-propelling-digital-transformation-in-the-insurance-industry-by-2026.