AI has this amazing potential to streamline processes, make data analysis fast, and reduce manual effort.
→ Sounds like a dream, right?
But there are some key challenges that insurers need to overcome to make this dream a reality.
First, insurance companies are often dealing with very old technology. Many insurers are reluctant to let go of legacy systems because, well, that's what they use on a daily basis for their operations. The thing is that these systems weren’t designed with AI in mind, and that creates a massive problem for integration. You can’t just plug in AI and expect it to work perfectly fine with a system built on COBOL... And let’s not forget that upgrading or replacing legacy systems is a huge, expensive task that many companies aren’t quite ready for.
The second big challenge? Data. Insurance is a data heavy industry and AI works on data, but not just any data - clean, structured, and high-quality data. Unfortunately, the data in insurance is often spread across multiple systems, stored in different formats, and sometimes incomplete or inaccurate.
You need a solid foundation for AI to function effectively. Without that, you’re going to run into issues like biased models, inaccurate predictions, and even non-compliance with regulations.
Next, the insurance industry is very much regulated given the sensitive nature of the data involved. But that also means AI has to operate within strict legal frameworks. AI doesn’t just need to be transparent; it needs to be explainable. This is a huge challenge because AI models, especially the more complex ones like deep learning, can be a bit of a black box. How do you explain to a regulator why an AI decided to deny a claim or raise a premium? If you can’t explain it, you’re not only going to face regulatory issues but also a trust problem with your clients.
Finally, AI in insurance workflows can trigger fears among employees. There’s a lot of talk about AI ‘replacing’ jobs, and while AI can automate repetitive tasks, it doesn’t mean we’re eliminating the human workforce. Employees may resist AI integration because they see it as a threat rather than a tool to make their jobs easier. Overcoming this challenge is as much about change management as it is about technology.
To make AI integration successful, insurers need to work closely with their teams, provide training, and emphasise how AI can augment human expertise rather than replace it.
AI is here to support, not take over.
So, what’s the solution? The key is patience and a phased approach. Integrating AI into insurance workflows isn't a one-size-fits-all process. Insurers need to start small, test their AI systems, and iterate based on the results. Legacy systems may need to be updated gradually, data governance strategies must be put in place, and regulatory frameworks must be understood.
Curious about how this could work for your business? Send me a message, and let’s chat about how Simpli can help make it happen!
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