Equisoft Q&A: How Life Insurers are Navigating AI Adoption

AI is beginning to reshape how life insurance carriers approach operations and decision-making.

The sector has historically relied on legacy technology and fragmented data systems that limit operational flexibility.

According to Equisoft, the industry now faces questions about overcoming infrastructure constraints and building capabilities needed for AI-driven workflows.

Brian Carey, Vice President of Insurance Solutions Engineering at Equisoft, says adoption patterns vary widely and that caution remains a defining characteristic of how insurers engage with the technology.

How would you describe the current state of AI adoption in the life insurance industry?

AI adoption in life insurance is moving in the right direction, but the adoption rate is still uneven because carriers are cautious about implementation. Life insurance has never been quick to adopt new technology, particularly when it affects underwriting, compliance, or customer-facing processes. Most insurers don’t want to be the first to try something in the AI space – they want proof, guardrails, and reassurance before committing.

We see that caution reflected in our client base. Recently, Equisoft brought on two new clients at opposite ends of the spectrum: one is fully committed to AI and actively looking for ways to embed it across their organisation, while the other is more cautious. That second client understands AI is important, but they’re unsure where to start and are even cautious about letting AI be used internally. So, while appetite is growing, the pace of adoption isn’t as fast as many expected, especially given how quickly the technology itself is advancing.

How much does leadership and company culture influence whether AI adoption succeeds?

Culture is one of the biggest determining factors. Having a CIO or CTO who is enthusiastic about AI helps, but leadership support alone isn’t enough. If the people doing the day-to-day work aren’t comfortable with the technology or -don’t see its relevance, adoption stalls very quickly.

Successful AI adoption requires companies to treat the technology as a strategic priority and actively encourage teams to explore how it can add value across the organisation. If it’s simply viewed as a side experiment or a leadership talking point, it’ll never scale. 

Where is AI delivering the most value today, and where are life insurers focusing their efforts?

The area we’re seeing the strongest traction right now is in operational and workflow--driven use cases, where AI can clearly save time, reduce errors, and lower costs. For example, at Equisoft we’ve built agentic AI capabilities into our Equisoft/amplify policy administration system enhancement platform, and now processes that once took 40 minutes only take a few minutes. When life insurers see that kind of impact, it immediately resonates because the business value is evident.

A lot of what’s currently marketed as AI in the industry is still surface -level, and that doesn’t really move the needle. The real opportunity is embedding AI directly into existing systems, so it enhances workflows without users needing to think about it. Whether it’s suitability checks, good order processing, underwriting support, claims handling, or internal reviews, AI works best when it’s applied to repetitive tasks that are prone to error and slow down organisations. In many ways this mirrors where cloud adoption was- several years ago. Once companies understood the operational benefits, adoption accelerated.

What should life insurance carriers be asking vendors when evaluating AI solutions?

Right now, life insurance carriers are still learning what questions to ask. The most common questions we hear are about governance: Is the AI auditable? Is it traceable? Can automation levels be controlled? In a regulated industry, those concerns are entirely appropriate and extremely important.

Beyond that, insurers should dig deeper into how a solution actually works. Is the vendor building agentic AI that can take actions, break complex tasks into smaller steps, and repeat processes autonomously? Or is it simply a chatbot layered on top of existing tools? Insurers should look at what models are being used, how data privacy is handled, which technology partners are involved, and how those partnerships are leveraged in practice.

It’s also critical to distinguish between generic AI providers and vendors who truly understand the life insurance domain. Without deep life insurance industry expertise, solutions tend to miss key regulatory, operational, and business nuances, which can be more expensive with less real value.

What advice would you give life insurance carriers that are just beginning, or are hesitant, to adopt AI?

Don’t wait. The gap between companies that are investing in AI and those that aren’t is widening quickly. Enterprise AI adoption is still in its infancy, but the technology is evolving faster than organisations can keep up. Waiting for a “perfect” solution only guarantees falling further behind.

Internally, life insurance carriers should put AI tools directly into the hands of their employees in a secure, controlled way and let use cases emerge naturally. AI adoption works differently than traditional enterprise software. It’s more bottom up-. When people experience firsthand how AI can save time and reduce friction, the value becomes obvious.

Life insurance carriers should work with partners who understand their industry and are willing to evolve alongside them. The companies that start now, invest in resources, and build institutional knowledge will be the ones best positioned to innovate, serve their customers better, and operate more efficiently long term.