What’s Next for Data Leaders in Specialty Insurance?

The role of our market’s data leaders is changing. As the insurance space continues to digitally mature, data leaders find themselves at the heart of this transition. Balancing short-term BAU demands with achieving long-term goals is an ongoing challenge, but there is also an opportunity to show the value of the data and the data team’s work. But what’s next for data leaders? From our recent discussions across the specialty market, here are four key themes data leaders should consider when setting their priorities for 2026.

View AI as an Opportunity

AI runs on data. Data quality affects whether your AI projects succeed. Your business needs the right data, governance, and architecture to support AI implementation. Thus, AI means that data teams can revisit their foundations, to ensure they have the architecture, skills, and governance properly implemented to support future AI initiatives. It’s also an opportunity to reinforce the importance of data to your business generally and to cement “data ops” as the critical business function it is.

Concentrate on Your Data Foundations

With AI algorithms relying on clean data and companies using historical data for planning, legacy data quality is critical. So now is the time to think strategically about what you need from your data going forward – and how it needs to be captured, checked, and monitored to be useful. Take advantage of the interest and investment in AI to take a hard look at the architecture and processes supporting your data governance and whether this will support your business’s future plans. The chances are that you will need to rebuild some of your data foundations.

Be More Visible!

Data teams are increasingly moving from technology orientated teams to becoming much more part of the business. Data continues to be viewed as a business-critical asset. This means that data leads need to be more visible to business side stakeholders. We think data champions need to shout more loudly about their wins and the value they bring to their business! Raising your profile makes it easier to engage stakeholders across the business and encourage them to work with you to improve data quality and its governance.  The goal is to encourage the rest of the business not only to be “data-minded” but to come to you with their data questions and needs. Now is the time to be proactive, to go out into the business and start by asking.

Understand Data Context

The last gen of insurtech AI focussed on machine learning, but the use of language-based models such as GPT 5 , Claude plus Agentic AI means that more than ever, that data needs to be put into context. Data leaders need to bring together data and subject matter experts within their organisations to provide the context around the data. Capturing not only the data but the context around that data ensures consistent and accurate interpretation. For example, correctly codifying claims consistently can substantially improve reinsurance recoveries.

Final Thought…. what’s next for data leaders?

The role of insurance data leaders continues to evolve, reflecting the increasing importance of data to their organisations. The current noise around AI provides data teams with a great opportunity to revisit key data foundations and to future-proof their processes.

Related content:

These topics were distilled from our recent webinar with The Insurance Network about data leadership in transition. To find out what the expert panel said, watch the webinar here >> https://www.the-insurance-network.co.uk/tinsights/webinar-recording-data-leadership-in-transition

We will be going into this topic at the Insurance Network’s Data Jam on November 25th. We are hosting a panel with market leaders to talk about how building strong data foundations is crucial to success. Find out more about Data Jam and how to attend here >>  https://www.the-insurance-network.co.uk/conferences/data-jam

At DQPro, we are always interested in how the role of data leaders is changing and the challenges and goals they are facing. We’re building an active market community of engaged data practitioners – all focussed on driving better data across specialty markets. To find out more contact us explore the website further.