How new AI benchmarking tool helps insurers track ROI

Digital customer service platform Glia recently launched an AI benchmarking tool it hopes will help insurers “cut through the fog” in analyzing their artificial intelligence strategy.

“There is an enormous fog of war at the moment. We are squarely in the middle of the hype cycle. Everybody’s throwing AI onto their products like a sort of bumper sticker. Our customers are like a deer in a headlights; it is very difficult to know what’s working and what’s real and what’s not,” Jake Tyler, AI strategy director, Glia, said.

Cortex AI Benchmarks is a reporting dashboard created by Glia. The AI benchmarking allows companies to assess the actual impact of their AI rollout and compare that performance with leading companies across the sector — either “patting themselves on the back” for their AI rollout or rethinking what’s not working.

“We can share the results of how other customers, how people’s peers, are using our AI products and provide some very relevant benchmarks on that performance for customers who are either evaluating if they should introduce AI tools, or have already introduced these tools and are looking to evaluate how they’re using them,” Tyler said.

He noted that many companies are already using the same or similar AI benchmarking tools, but the differentiating factor comes down to how that technology is being adopted.

“The difference between your results and someone who’s in our top quartile is really about how you’ve deployed it and how you’re using it. That was the point of our AI benchmarks. It’s really meant to cut through the hype and fog of war in AI and let people see the data for themselves,” Tyler said.

AI benchmarking: Key metrics

Glia’s benchmarks look at KPIs that are “easy to understand and easy to measure,” such as automation rates and time saved. For example, the results from an AI feature called “autocomplete” that types ahead to suggest the next word or the rest of the sentence an agent is typing.

“This is a super helpful tool as people are interacting via chat specifically. So, what we can do with autocomplete is tell people how much time they’re saving per every hundred interactions. That’s a very sort of standard benchmark,” Tyler said.

He noted that a lot of financial companies that rank in the top quartile save almost twice as much time as the average benchmark using this autocomplete feature.

“Many customers have deployed the feature, have activated it, but their service reps just aren’t using it very much. So, we do see lots of folks are below that average and looking to come up,” he said.

Similarly, another Glia tool called “interaction wrap up” helps automate post-call work. Tyler said this is another area where results vary significantly between those who use it and those who don’t — and the value realized accordingly.

“We have some key benchmarks for that feature as well. What’s the automation rate? How much of that post-call work are we able to automate? What’s the time saved for every interaction? And then again, we can share the benchmark for average and top quartile,” he said.

Capturing efficiency

Tyler acknowledged that many stakeholders are eager to measure the efficiency of AI. However, as this is a “difficult” metric to measure, he instead suggested companies analyze indicators like whether AI has helped multiply their team’s capacity.

“We talk about efficiency with AI a lot, and I think the efficiency part is a little bit challenging to actually capture in the real world. I think AI and tools like this are more of a force multiplier. So, you can do more with your existing team,” Tyler explained.

To illustrate his point, he said if a given company has a 10-minute handle time but AI automation is able to save one to two minutes, that equates to a 10% to 20% force multiplier from a feature that is very simple to use and integrate.

“Regardless of the insurance company, their size, their line of business — everybody’s feeling that pain of wanting to be more efficient. This tool really helps them solve that, and the beauty of benchmarks is that they can see that data for themselves,” Ryan Baillargeon, insurance industry lead, Glia, noted.

Insight and analysis

Glia believes this tool can benefit anyone evaluating an AI product or solution, and especially for those in financial services, which is their specialty. Additionally, they offer clients support with improving benchmarks by providing suggestions and sharing best practices from top quartile clients.

“The tool is a way for you to see that these features can deliver value and are delivering value for people like you. It can help you to build the business case; we certainly have other ways to help folks do that as well,” Tyler said.

Glia is a digital customer service platform that helps insurance companies improve customer interactions. Founded in 2012 with headquarters in New York City, Glia has partnered with over 500 financial institutions across 47 states and 12 countries.

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