Is there a winning AI strategy for insurers? IBM says yes

Insurers that use generative artificial intelligence have an advantage over their competitors, according to Mark McLaughlin, IBM global insurance director. However, he said the way they leverage it matters, as he provided some insights into a winning strategy.

McLaughlin spoke with InsuranceNewsNet on the heels of IBM’s Institute for Business Value having released a study on how gen AI is being used in the industry.

“Lots of insurers are making AI investments. They talk to us all the time. But how do you build it in a way where you’re actually generating business results?” he said.

IBM’s recommendations include:

• Use AI to build customized solutions for clients
• Distribute AI throughout the organization
• Plan on using a range of AI models

“Use AI to connect the customer to the risk and to the right product. Distribute AI throughout your organization, empower your business users to use it, and use AI to solve the underlying IT problems to make all that faster. The companies that are doing well in insurance with generative AI are all taking advantage of those principles,” McLaughlin said.

Gen AI investments on the rise

IBM’s study found insurance CEOs were divided on whether they see gen AI as a risk or an opportunity. However, 77% of insurance executives who responded believe it is necessary to keep up with competitors. Accordingly, IBM expects AI investments in insurance to increase by as much as 300% over the next two years alone.

That intense competition — and not direct customer demand — is what McLaughlin believes is driving such strong pressure for insurers to invest in AI.

“Something like more than three quarters of those executives are getting pressure from their board, from their employees and from the press. They’re reacting to shareholder concerns and competitive concerns and they absolutely know that if they don’t get AI right and their competitor does, that it’s going to be a problem,” he said.

Disconnect with client expectations

However, IBM pointed to a disconnect between what insurers are focused on when it comes to utilizing AI and what their clients expect out of it.

While insurers were found to look at factors like overall experience, brand consistency and ethics policies, clients were more concerned about practical applications to meet specific needs.

“I think customers are looking for something beyond, well, just have the chatbot use my name [or] have the chatbot speak in a language that’s familiar to me. They’re getting down to the brass tacks of the problem, which is [whether] the product you’re selling is the right product to solve my risk issue and to address my emotional concern about why I’m buying insurance in the first place,” McLaughlin said.

Strategy 1: Build trust and customization

Bridging the disconnect between client expectation and how insurers use AI will come down to building trust and providing customized solutions, McLaughlin suggested.

“I think the insurers need to build in products that link to the data that they’ve got on the customer and on the customer’s risk. They need to build those more tailored products. They need to match those products intelligently to customers, and they need to do so in a way that’s trustworthy,” he said.

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. That says it’s really important to get generative AI right in the context of trust,” McLaughlin added.

Strategy 2: Take AI beyond IT

McLaughlin also recommended insurers distribute gen AI capabilities across their entire organization instead of leaving it “locked up” in a single IT department.

“IT can support and help with the technical implementation, but you’ve got to empower your business users with generative AI. You have to help them to apply generative AI in ways that do a better job of serving the customer’s risk,” he said.

At the same time, IT teams can use AI to deal with legacy technical debt — which McLaughlin said over 70% of insurers struggle with.

Strategy 3: Use multiple models

McLaughlin pointed out that many insurers plan to build a single AI model using one of the large language models. However, he advised against this as he said just one tool may not necessarily be the best to meet every need.

“There are specific AI tools you’re going to end up using. Plan ahead. Have tools that will work across a range of AI models; connect to all of your data stores across your organization and across your ecosystem of partners; and govern AI effectively across that range,” he said.

For instance, McLaughlin noted that IBM’s Watson AI has different platforms such as watsonx.ai, watsonx.data and watsonx.governance to meet different specific needs.

IBM is one of the world’s largest, most well-known technology research organizations. Its report, “Generative AI in the Insurance Industry: You Can’t Win If You Don’t Play” included findings from a survey of 1,000 insurance C-suite executives in 23 countries and 4,700 insurance customers in nine countries. The full report can be viewed on their website.

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