Jul 235 min read

InsurTech Ohio Spotlight with Jason Wrather

Jason Wrather is the AVP of Innovation at Grange Insurance, providing peace of mind and protection during life's unexpected events. Jason was interviewed by Daniel Kessler, Client Partner at Capgemini.

Jason, how do you believe the conversation around implementing Artificial Intelligence (AI) technologies should be framed?

“At Grange at least, we've established three areas of focus that guide our work. We call those governance, education and adoption. Governance is the activities we engage in, to define the controls around our data privacy activities, in addition to understanding the emerging legislative requirements. Education is about ensuring that the organization has a firm understanding of all the new and emerging technologies. You want to begin by exposing people to the technologies and providing explanations of what these new technologies are.

Many times people see AI technologies in their everyday lives, and they don't even realize it. Getting people comfortable with AI is the first step to helping them become comfortable with adopting it, which leads to conversations about adoption. A culture that embraces change helps us look for ways to implement new AI capabilities as we look to drive value in the organization.”

What are some key considerations around AI governance?

“It's important to recognize that AI is constantly evolving, so it's difficult to know all the questions we should be asking at this point, much less have all the answers to some of those questions. With that sort of caveat, when I think about AI governance, it's important to bring in a cross-functional team to help evaluate all the different risks.

That's what we've done at Grange. We have folks from our risk management, legal, IT, product, data management and customer experience teams there. So, we have a lot of voices represented at the table, and that helps us think about governance in a broad way.

With that said, we have a couple of guidelines that we use to help navigate this space. I can give you a few examples that are top of my mind today. From an external view, you could say, how do you set up the controls and procedures to manage data privacy? That should be first in any discussion around AI. It's important to protect the customer and company data.

One of the things we've done right out of the gate with our governance committee is review all of our existing contracts with vendors and outside parties to understand if they use AI in their current product set and/or if they are getting ready to adopt new AI technologies in their current product set. We want to know the details and how that AI is being utilized. We're updating our contract with those companies to provide guidance and language around governing, so our data is protected at all times.

From an internal view, we have what we call a ‘phase-gate lifecycle’ approach. Anytime we create a new product or project, we begin by looking at some of those phases and start to add additional criteria that help us ask the right questions and force a discussion around AI-related needs. In order for a project to continue to move forward, it has to pass our approach of project management.”

Is AI an existential threat to insurance professionals or is its potential deserving of our optimism?

“Since I'm on the innovation side of the house, my answer will always be cautious optimism. There’s a quote I share often with people that applies to this question. When folks ask me how we should think about AI, I acknowledge the question that's on everybody's mind. Is this going to take my job? My response to that question is this quote, ‘Employees should not be worried about AI technology itself taking their job away. They should be worried about someone else that's using AI technology in the work that they do.’

This translates to employees who understand AI will be the ones who can advance and compete in the marketplace. The important part of that whole message is to embrace AI, learn how it works and learn how you can leverage it to your advantage.

It’s important to recognize that if you're managing a team, you're going to have different cohorts of your employees who are going to be at different points in that journey of adopting and leveraging new technology. AI is the technology of the day, but you can look back through time to see that technology has come into the insurance industry many times over the years. I remember when I first started in the industry, computers were just coming into the office. I was on the actuarial side back then. Some of my fellow co-workers still calculated rates by hand.

Then you had another group there that embraced the use of the computer. It was no surprise that the computer was faster and more accurate. I'm sharing my age here, but I look at that and say technology has come into the industry many times. This is not the first time that we're faced with this opportunity. Part of it is to look backward to see how things have happened and apply those learnings going forward. Acknowledge that people are in different places and start to cater that education to where they are and help them get to where you need them to be.”

When and where in this evolution to adopt this technology do we begin executing work with the support of AI?

“It's going to take a while to become part of our standard work processes. I like the term ‘human in the loop’. I'll never use AI on its own, but always have checks and balances in there. When I think about how you envision AI making its way into that standard work process, I know it's going to start small. Start with the back office and then move to the front office, and by that, I mean that the back office is more employee-facing work.

Start in areas of low risk that are easy to implement and provide training. Your employees are more open to training and receiving guidance, and they'll change their behavior if you provide them with the right training. It also allows you a safe space if you are implementing in this back-office, employee environment. If you make a mistake, employees are usually more forgiving. You could go in and fix the mistakes before you're out in the market, and it's customer-facing or agent-facing.

Begin in the back office, try to optimize it and start to learn how to leverage the AI technologies there. Help the organization fine-tune those skills along the way, and then start to think about how you can scale it. As you begin scaling, you can look outward to that front-office view, looking at ways to really enhance the agent and customer-facing processes.

The final area I’d like to mention is what I call a tech sandbox. Always have a space off to the side where you can test risk-free things that are not connected to the business in any way. A place where you're always given the freedom to explore those new, cutting-edge technologies. Get it off to the side, learn about it, find ways to test it and then look for applications to bring that back into the business environment.”