Driving AI Adoption in Insurance – with Ryann Foelker of American Family Insurance Group

Sharon Moran

Sharon is a former Senior Functional Analyst at a major global consulting firm. She now focuses on the data pre-processing stage of the machine learning pipeline for LLMs. She also has prior experience as a machine learning engineer customizing OCR models for a learning platform in the EdTech space.

Driving AI Adoption
in Insurance-1-min

As a rule, AI adoption tends to take more time for legacy industries compared to digitally-native sectors. As a profile from June 2021 in Harvard Business Review explains, insurance companies are data-rich but have long relied on actuarial approaches to data and analytics.  The insurance industry has several concerns regarding the integration of AI. Insurance companies obviously have regulatory compliance as a top priority, so any AI solution implemented needs to comply with existing regulations regarding consumer protection and data security, among others. 

The same emphasis is reiterated at regular intervals through various means, including a recent bulletin published by the National Association of Insurance Commissioner’s Center for Insurance Policy and Research last year. 

Founded in 1927, the American Family Insurance Group is a private mutual company that focuses on property, casualty, and auto insurance along with life, health, and homeowners coverage. Additionally, they provide commercial insurance as well as investment and retirement-planning products. Emerj CEO and Head of Research Daniel Faggella recently sat down with Ryann Foelker, Strategy Director of the American Family Insurance Group, on the ‘AI in Business’ podcast to talk about AI adoption in the insurance industry.

The following article examines two critical insights from their conversation: 

  • Minimizing the risk of AI solutions that fail to account for the human side of loss: Designing AI use cases to augment rather than replace human workflows that provide empathy and logistical expertise to customer experiences. 
  • Understanding the importance of cross-functional teams: Strategically deploying AI use cases with IT, leadership, and especially design considerations in mind that incorporate both human and business value.

Listen to the full episode below:

Guest: Ryann Foelker, Strategy Director, the American Family Insurance Group

Expertise: Industrial Design, Strategy, Innovation

Brief Recognition: Ryann graduated from Milwaukee Institute of Art & Design in 2006 with a BFA in Industrial and Product Design. Previously, she was Art Director at Sonic Foundry Inc. and also founded a boutique strategic design agency.

Minimizing the Risk of AI Solutions that Fail to Account for the Human Side of Loss

Foelker begins by acknowledging that AI is currently transforming the entire insurance industry. In the process, she believes there is a risk right now of AI failing to account for the human side of loss.

Foelker’s team designs use cases that help ensure her company uses AI to augment rather than replace the human element of insurance workflows where they can best support company goals. Foelker thinks the insurance industry is presently very young in its AI adoption. “We need to make sure that we don’t get so excited about what this new tool brings to the table that we lose sight of our primary value proposition,” she tells the executive podcast audience. “Instead, what we want to do, obviously, is augment that value proposition and enhance it for the future.”

Foelker acknowledges that her company and the industry as a whole are risk-averse. As a result, her company’s initial conversations regarding Chat GPT were centered around some of the following questions:

  • What’s the liability of using it?
  • What are the ethical considerations?
  • What are the privacy considerations?
  • What are the security considerations?

The American Family Insurance Group’s approach to the process was excitement tempered with risk, which according to Foelker, is representative of the entire insurance industry. However, the evolution has not been without significant headwinds for the sector. “AI really is the tool for big problems, the ones that haven’t seen successful solutions yet, and it’s not necessarily the tool for reliable results,” she says. 

When designing the best use cases for AI, Foelker said her company is looking at:

  • The capabilities of AI
  • The problems that haven’t found a successful solution yet
  • Deep industry expertise to find the nuanced actions that are needed to drive solutions for those challenges

Understanding the Importance of Cross-Functional Teams

Foelker explains that when her team is building the best AI use cases, they want a cross-functional team that can take into account the above elements and champion both human and business value to ensure that they’re using tools to their full potential. She emphasizes how, in order to maximize value, they need technological, design, and business expertise to work in unison: 

“I’ve seen a lot of things come out of business and IT that are excellent, but it lacks the sort of nuance that it needs when it comes to having design at the table. Similarly, I’ve seen things done with business and design that certainly lack a big perspective from the IT folks. So, I think it’s really about that balance to make sure that you’re using the tool to solve all the problems.”

– Ryann Foelker, Strategy Director at The American Family Insurance Group 

Foelker mentions that the multiple perspectives needed must include:

  • A distinct technology-based perspective to know how things are working and what needs to happen
  • A business leadership perspective to ensure solutions align with existing processes
  • A design perspective to ensure that they’re creating value that lasts beyond a year

When asked about the shift in leadership that comes from viewing AI as a capability that helps organizations compete in the future, Foelker responds, “As a design leader in a legacy insurance company, I could tell you a lot of stories, but I do think it is shifting may be slower than it has in some other industries.”

As a designer and futurist, Foelker’s focus is on initiatives that will be more important in the future than they are today despite recognizing all the merits of use cases in underwriting and claims. 

She then proceeds to cite startling statistics, including that a quarter of all of the homes in the US are at risk of becoming uninsurable because of increasing climate risk, which is driving rates and deductibles to unaffordable levels. She also mentions that two-thirds of US homes are underinsured, and 12% are uninsured due to cost and access issues. “So, I think this is a really prime opportunity for AI because this is a huge problem that has yet to see a large-scale solution,” she summarizes.

Foelker mentions the need for large-scale translation so that various sectors, including the regulatory industry, can communicate more effectively with each other. She is confident that AI will become a powerful tool to help enhance and facilitate those conversations.

When asked about insights or perspectives that could be useful for enterprise leaders just beginning their AI journey, Foelker offers the following guidance: 

  • Leaders should first think about the big problems in their organization or industry that haven’t seen a solution yet or are viewed as being unsolvable. 
  • Next, they should consider whether or not AI provides the capabilities that are needed but didn’t exist in the past. 
  •  Finally, they should look at new technologies through a big lens. 

In exemplifying her final point, Foelker then asks a series of proverbial questions business leaders should ask themselves in the same position: “How can I add my unique industry, organizational, or market perspective to make a use case that I didn’t just read about in someone else’s organization? Or how can I take that use case and tweak it so that it really is exclusive to my perspective or my point of view?” 

She ends with a pointed lesson from her experience in these areas: “Targeted is the way that design succeeds.” When asked what she meant by the word ‘targeted,’ she continues: “If you’re trying to be everything to everyone, you’re nothing to no one. You need to know what you’re trying to solve.” 

On a final note, Foelker emphasizes that, for the same reasons, it is so essential for industry leaders to think big but then rely on their industry expertise to understand the nuanced changes that need to happen.

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