About this webinar
Too many opportunities. Where do you start?
AI has no shortage of possible applications in insurance operations. Submissions arriving by email, policy servicing, claims documents, bordereaux and other repetitive work moving between people and systems can all present opportunities for automation.
The problem is no longer finding something AI could do. It is deciding where to start.
When there are dozens of potential use cases competing for attention, choosing the perfect one can become a project in itself. Teams can spend months assessing processes, debating priorities and building business cases while practical opportunities to improve a workflow remain untouched.
So what makes a good first move?
This webinar looked at how to make that call with more confidence: finding where automation makes a material difference, understanding what it costs to run today, testing whether AI genuinely suits it and defining success before a build begins. It stayed close to what the London market is actually doing – where AI is delivering value, where attractive use cases have proved difficult and what they would do differently after moving from pilot into production.
Sasha Haco, Chief Executive Officer and Co-Founder of Unitary explored why projects stall, what makes a strong first use case and what changes once AI becomes part of operations – joined by practitioners who have already put AI to work in their businesses.
Attendees left with a practical approach for assessing their own operations: how to identify the opportunity, build the business case, embed the right controls and measure its delivery.
In this webinar, the panel discussed:
- Where is the business case strongest? Finding the workflow – across submissions, policy servicing, claims or bordereaux – where automation makes a material difference
- What makes an insurance process automatable? Volume, variation, exceptions, data quality and where human judgement still has a role
- What does the process cost today? The baseline in handling time, turnaround and cost per transaction needed to prove value
- How do you automate safely in a regulated environment? The controls, oversight, audit trails and governance to put agentic AI into live operations responsibly
- Where do promising use cases break down – and what should success look like? Lessons from pilot to production and the measures that decide whether to scale
