The question for insurance executives is not how quickly to adopt AI. It is whether the organization has the foundation to turn AI into measurable business value.
Since 2012, Agile Insurance Analytics has consistently called for insurers to establish the foundational data management building blocks — governance, quality, integration, and accountability — required to support advanced analytics and predictive modeling. Without these essentials in place, investments in AI and predictive tools rarely deliver sustainable business value.
A 2026 study from Precisely and Drexel University’s LeBow College of Business surveyed 505 data and analytics leaders around the world. Its message is straightforward: organizations are moving rapidly toward AI while many still struggle with the basic conditions needed to make those investments work — reliable information, clear accountability, effective governance, the right skills, and a clear connection to business results.
For a CEO, this is less a technology issue than a management issue. An organization can invest in new AI capabilities and still make poor decisions if leaders cannot trust the information those capabilities depend on.
AI does not replace the need for good management. It makes the need for trusted information even more important.
Insurance decisions depend on information every day — from underwriting and claims to pricing, financial management, customer relationships, and regulatory obligations. When leaders receive different answers to the same question, confidence falls and time is lost reconciling the numbers.
Executives can act with greater confidence when the organization agrees on the information that matters.
Clear ownership and consistent information reduce the recurring effort spent finding, checking, and correcting problems.
AI initiatives have a stronger chance of producing meaningful results when they are connected to reliable information and real business priorities.
The most useful executive conversation is not about algorithms or technology. It is about whether the organization can make better decisions, improve operations, reduce risk, and create measurable value.
Data decisions should have visible business ownership and executive accountability.
Fix recurring information problems before they become larger business problems.
Define the result the organization expects before selecting an AI initiative.
AI should fit within the organization's broader approach to accountability and risk.
Technology creates value only when the organization is prepared to use it effectively.
Modernization should strengthen the organization's ability to use trusted information to improve performance.
At Agile Insurance Analytics, we believe sustainable AI value begins with alignment: business priorities, operating processes, accountability, trusted information, and measurable outcomes. The technology matters, but it is not the strategy. The strategy is improving how the business performs.
It is who builds the strongest foundation for turning AI into better decisions, better operations, and measurable business results.