Attending this year’s LIMRA Life Conference gave me an upfront view into what is top of mind for carriers.
I expected to learn, but was surprised by how consistent the themes were across sessions and discussions. Those conversations were shaped by broader pressures around growth, economic uncertainty, and reaching new customers.
Overall, awareness isn’t the industry’s biggest issue; agility is. The industry knows its hurdles, and needs to prove how fast it can solve them. Here are three takeaways that stood out most:
1. The buying experience is complex and widely acknowledged as such
Across sessions like Making Life Insurance Accessible: Strategies That Work, we heard that the process is slow, confusing, and easy to abandon. There’s strong alignment on what needs to change:
- Reduce friction in application and underwriting
- Make faster decisions (ideally instant)
- Enable smarter use of data earlier in the process
- Simplify experiences for both buyers and advisors
Meeting rising end-user expectations is no longer a nice-to-have, speed and simplicity are expected, and carriers who deliver on both will be best positioned for future growth.
2. Speed and simplicity only matter if trust keeps pace
One nuance that came up repeatedly: faster doesn’t automatically mean better. There’s a lot of exploration when it comes to:
- Enabling AI in practice and what that means for the end user experience
- Automated underwriting at scale
- Reduced (but not eliminated) human involvement
The focus isn’t just on possibility, but on understanding how to move from vision to practical, trusted implementation.
3. AI is everywhere, but few have moved beyond exploration
AI was part of nearly every conversation. There’s momentum, but little consistency. The industry has moved past the ‘if’ of AI and arrived at the ‘how.’ The answer? None of it works without the bedrock of a strong data infrastructure and integrated workflows.
That’s where I saw a direct connection to the work we’re doing at Sureify. With CoreCONNECT, the focus on unifying data and orchestrating workflows across systems aligns closely with what many are trying to solve. Without that foundation, AI stays experimental.
I look forward to the progress our industry will make by the time I return for my next LIMRA conference.





