Insurance has always been a data-driven business, but today, the stakes are higher than ever. With generative AI (GenAI) accelerating into the enterprise mainstream, insurance chief information officers (CIOs) face a new and urgent mission: to harness this powerful technology for smarter, faster decision-making without triggering compliance nightmares or operational chaos.
The pressure is on. Regulators are watching. Budgets are tightening. And the board wants results. So, the question isn't just can you adopt GenAI, but how will you extract measurable business value from it, responsibly, and at scale? Here, I'll cover several ways to do that.
Reimagining the Broker-Underwriter Partnership
The broker-underwriter relationship has long been hindered by fragmented data and sluggish manual workflows. But GenAI is now stepping in as a powerful enabler, transforming the way these two roles collaborate. By streamlining data sharing and automating tasks, GenAI unlocks faster, smarter decision-making and a more seamless flow of information across the value chain. Here's what that looks like in action.
Instant policy summarization. AI tools can scan lengthy broker submissions and extract key risk indicators, saving underwriters hours of manual review.
Automated broker queries. Instead of trading emails, GenAI-powered assistants can clarify missing information in real time.
Real-time risk analysis. Brokers can use natural language prompts to query underwriting data and instantly uncover price trends and exclusions.
Tailored policy recommendations. GenAI analyzes client data to help brokers suggest more personalized coverage options.
GenAI doesn't just streamline processes; it sharpens broker insight. By using natural language queries, brokers can ask plain-language questions about client cases and instantly tap into underwriting data for fast, authoritative answers. Behind the scenes, GenAI can parse these questions and pull the most relevant data from trusted sources to answer the question with authority.
It also powers hyperpersonalized policy recommendations. By scanning prior claims, shifting marketing conditions, and real-time risk profiles, GenAI can suggest the best-fit coverage for each client, helping brokers drive customer satisfaction and boost revenue in one move.
Moving from GenAI Experimentation to GenAI Differentiation
Insurance companies are starting to move from GenAI experimentation to GenAI differentiation. However, many companies are also learning the hard truth that GenAI applications are only as reliable as the data that feeds them. As insurance companies deploy GenAI applications, they need to be able to provide these applications with immediate access to trusted, governed, and properly formatted data from across the organization.
To move from GenAI experimentation to GenAI differentiation, insurance companies need data platforms that can deliver the following.
Real-time access to disparate data sources, including not only data lakehouses but also other supporting data sources
A universal semantic layer, that can automatically transform data into clear language that can be readily understood by large language models
Rich metadata, providing GenAI applications with critical context about all data
Enterprise-wide data governance, as well as data security for protection, risk mitigation, and compliance
Balancing Innovation with Governance
"Enterprise-wide data governance" requires a bit more focus, as insurance companies must proceed with GenAI adoption with a full view of the risk, compliance, and execution challenges that may lie ahead. Innovation must always be tempered with governance.
In particular, insurance companies will need to pay close attention to the National Association of Insurance Commissioners guidelines, EU AI Act, and state-specific AI regulations, all of which require insurance companies to maintain transparency in their GenAI applications. All such applications must be explainable, free of bias, and compliant with recent data privacy laws.
A Powerful Strategy for GenAI
Insurance CIOs are no longer simply data stewards; they are now the architects of AI transformation. Standing at the intersection of innovation and accountability, they must unlock the full potential of GenAI without compromising on trust, ethics, or compliance.
The opportunity is vast. GenAI can turn complex, fragmented insurance data into insights, tailored recommendations, and operational breakthroughs. But the magic only happens when the foundation is solid. With the right data platform—one that delivers real-time access, semantic clarity, rich context, and enterprise-grade governance—CIOs will have that foundation. In short, CIOs can move from experimentation to enterprise-wide differentiation.
This is the moment to go beyond pilots and proofs-of-concept. The insurers who can do that will be those who can embed GenAI deeply into their workflows and measure its impact with confidence. Not just to enable faster underwriting or better broker interactions, but also to create measurable shifts in risk accuracy, customer satisfaction, and revenue growth.
The mission is clear, and the tools are ready. Now it's up to the CIOs to lead with vision and deliver the results that the boardroom expects and the industry will remember.
Opinions expressed in Expert Commentary articles are those of the author and are not necessarily held by the author's employer or IRMI. Expert Commentary articles and other IRMI Online content do not purport to provide legal, accounting, or other professional advice or opinion. If such advice is needed, consult with your attorney, accountant, or other qualified adviser.
Insurance has always been a data-driven business, but today, the stakes are higher than ever. With generative AI (GenAI) accelerating into the enterprise mainstream, insurance chief information officers (CIOs) face a new and urgent mission: to harness this powerful technology for smarter, faster decision-making without triggering compliance nightmares or operational chaos.
The pressure is on. Regulators are watching. Budgets are tightening. And the board wants results. So, the question isn't just can you adopt GenAI, but how will you extract measurable business value from it, responsibly, and at scale? Here, I'll cover several ways to do that.
Reimagining the Broker-Underwriter Partnership
The broker-underwriter relationship has long been hindered by fragmented data and sluggish manual workflows. But GenAI is now stepping in as a powerful enabler, transforming the way these two roles collaborate. By streamlining data sharing and automating tasks, GenAI unlocks faster, smarter decision-making and a more seamless flow of information across the value chain. Here's what that looks like in action.
GenAI doesn't just streamline processes; it sharpens broker insight. By using natural language queries, brokers can ask plain-language questions about client cases and instantly tap into underwriting data for fast, authoritative answers. Behind the scenes, GenAI can parse these questions and pull the most relevant data from trusted sources to answer the question with authority.
It also powers hyperpersonalized policy recommendations. By scanning prior claims, shifting marketing conditions, and real-time risk profiles, GenAI can suggest the best-fit coverage for each client, helping brokers drive customer satisfaction and boost revenue in one move.
Moving from GenAI Experimentation to GenAI Differentiation
Insurance companies are starting to move from GenAI experimentation to GenAI differentiation. However, many companies are also learning the hard truth that GenAI applications are only as reliable as the data that feeds them. As insurance companies deploy GenAI applications, they need to be able to provide these applications with immediate access to trusted, governed, and properly formatted data from across the organization.
To move from GenAI experimentation to GenAI differentiation, insurance companies need data platforms that can deliver the following.
Balancing Innovation with Governance
"Enterprise-wide data governance" requires a bit more focus, as insurance companies must proceed with GenAI adoption with a full view of the risk, compliance, and execution challenges that may lie ahead. Innovation must always be tempered with governance.
In particular, insurance companies will need to pay close attention to the National Association of Insurance Commissioners guidelines, EU AI Act, and state-specific AI regulations, all of which require insurance companies to maintain transparency in their GenAI applications. All such applications must be explainable, free of bias, and compliant with recent data privacy laws.
A Powerful Strategy for GenAI
Insurance CIOs are no longer simply data stewards; they are now the architects of AI transformation. Standing at the intersection of innovation and accountability, they must unlock the full potential of GenAI without compromising on trust, ethics, or compliance.
The opportunity is vast. GenAI can turn complex, fragmented insurance data into insights, tailored recommendations, and operational breakthroughs. But the magic only happens when the foundation is solid. With the right data platform—one that delivers real-time access, semantic clarity, rich context, and enterprise-grade governance—CIOs will have that foundation. In short, CIOs can move from experimentation to enterprise-wide differentiation.
This is the moment to go beyond pilots and proofs-of-concept. The insurers who can do that will be those who can embed GenAI deeply into their workflows and measure its impact with confidence. Not just to enable faster underwriting or better broker interactions, but also to create measurable shifts in risk accuracy, customer satisfaction, and revenue growth.
The mission is clear, and the tools are ready. Now it's up to the CIOs to lead with vision and deliver the results that the boardroom expects and the industry will remember.
Opinions expressed in Expert Commentary articles are those of the author and are not necessarily held by the author's employer or IRMI. Expert Commentary articles and other IRMI Online content do not purport to provide legal, accounting, or other professional advice or opinion. If such advice is needed, consult with your attorney, accountant, or other qualified adviser.