IBM Courts Insurance Companies: Interesting Move from the Watson Folks
December 20, 2024
This blog post flowed from the sluggish and infertile mind of a real live dinobaby. If there is art, smart software of some type was probably involved.
This smart software and insurance appears to be one of the more active plays for 2025. One insurance outfit has found itself in a bit of a management challenge: Executive succession, PR, social media vibes, and big time coverage in Drudge.
IBM has charted a course for insurance, according to “Is There a Winning AI Strategy for Insurers? IBM Says Yes.” The write up reports:
Insurers that use generative artificial intelligence have an advantage over their competitors, according to Mark McLaughlin, IBM global insurance director.
So what’s the “leverage”? These are three checkpoints. These are building customized solutions. I assume this means training and tuning the AI methods to allow the insurance company to hit its goals on a more consistent basis. The “goal” for some insurers is to keep their clients cash. Payout, particular in uncertain times, can put stress on cash flow and executive bonuses.
A modern insurance company worker. The machine looks very smart but not exactly thrilled. Thanks, MagicStudio. Good enough and you actually produced an image unlike Microsoft Copilot.
Another point to pursue is the idea of doing AI everywhere in the insurance organization. Presumably the approach is a layer of smart software on top of the Microsoft smart software. The idea, I assume, is that multiple layers of AI will deliver a tiramisu type sugar high for the smart organization. I wonder if multiple AIs increase costs, but that fiscal issue is not addressed in the write up.
The final point is that multiple models have to be used. The idea is that each business function may require a different AI model. Does the use of multiple models add to support and optimization costs? The write up is silent on this issue.
The guts of the write up are quite interesting. Here’s one example:
That intense competition — and not direct customer demand — is what McLaughlin believes is driving such strong pressure for insurers to invest in AI.
I think this means that the insurance industry is behaving like sheep. These creatures follow and shove without much thought about where the wolf den of costs and customer rebellion lurk.
The fix is articulated in the write as have three components, almost like the script for a YouTube “short” how-to video. These “strategies” are:
- Build trust. Here’s an interesting factoid from the write up: “IBM’s study found only 29% of insurance clients are comfortable with virtual AI agents providing service. An even lower 26% trust the reliability and accuracy of advice provided by an AI agent. “The trust scores in the insurance industry are down 25% since pre-COVID.”
- Dump IT. Those folks have to deal with technical debt. But who will implement AI? My guess is IBM.
- Use multiple models. This is a theme of the write up. More is better at least for some of those involved in an AI project. Are the customers cheering? Nope, I don’t think so. Here’s what the write up says about multiple models: “IBM’s Watson AI has different platforms such as watsonx.ai, watsonx.data and watsonx.governance to meet different specific needs.” Do you know what each allegedly does? I don’t either.
Net net: Watson is back with close cousins in gang.
Stephen E Arnold, December 20, 2024
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