5 ways everyone can benefit from AI today

Record date: 9/26/25
Air date: 11/5/25

Just as learning to read once unlocked access to knowledge, opportunity and participation in society, AI literacy is rapidly becoming a baseline skill for the modern workplace. In this episode of Zurich North America’s Future of Risk podcast, host Justin Hicks explores how understanding and using AI is fast evolving from a niche capability to a core professional competency.

Jay Bell, Head of Innovation for Specialties and Head of Operations for Construction at Zurich, and Mark Breading, Senior Partner at ReSource Pro, share how AI is reshaping their daily work—from turning flip chart photos into meeting summaries in seconds to using AI-powered conversations to brainstorm complex ideas during a commute in the car. They argue that AI is not just a tool—it’s a collaborator, a co-creator and a force multiplier.

Whether you're just starting your AI journey or looking to deepen your expertise, this episode offers practical, real-world examples of how AI literacy can elevate your impact, improve communication, and unlock new levels of productivity.

In this miniseries, other episodes include:

10/22/25: What is AI delivering so far
11/19/25: Dark side of AI
12/3/25: What’s next in AI?

Guests:

Jay Bell
Head of Innovation for Specialties
Head of Operations for Construction
Zurich North America
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Jay Bell serves as the Head of Innovation for Specialties and Head of Operations for Construction at Zurich North America. In this dual leadership role, Jay drives strategic transformation across underwriting frameworks and operational excellence, aligning innovation with execution to deliver measurable impact across the organization.

With over two decades of experience in the insurance industry, Jay has held pivotal roles including Vice President and National Middle Market Construction Consultant for Zurich, Divisional Vice President at Great American Insurance Group and Head of Middle & Large Commercial Programs at The Hartford. His expertise spans underwriting, operations, risk management and strategic business planning—consistently contributing to growth, profitability and innovation.

Jay is also the founder of AI 4 All, a working group dedicated to advancing AI literacy and practical adoption across the insurance sector. He holds multiple certifications from Vanderbilt University in Prompt Engineering, Generative AI Automation, Leadership & Strategy, and AI Assistants—positioning him as a thought leader in integrating AI into underwriting and operational workflows.

Mark Breading
Senior Partner
ReSource Pro
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Mark Breading is well known for his perspectives on the future of the insurance industry and innovative uses of technology in insurance. His specialty areas include distribution strategies, Insurtech and innovation. He leads the research, advisory services and partnership areas for ReSource Pro, serving clients across the P&C ecosystem. Mark has been named one of the “Top 50 Global Influencers in Insurtech” by Insurtech News, is currently serving as a mentor with Insurtech Israel and has recently been named by Consulting Magazine as Mentor of the Year.

Host:

Justin Hicks
Communications Business Partner
Zurich North America
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Justin Hicks is a Communications Business Partner at Zurich North America and supports enterprise communications efforts for the Direct Markets business and the Operations and Technology function. Before joining Zurich, Hicks was the first dedicated internal communications manager at Rivian's electric vehicle manufacturing plant in Normal, Ill. Earlier he served as public affairs communications specialist at State Farm, supporting claims executives and leaders.

(PLEASE NOTE: This is an edited podcast transcript, capturing speakers with natural speech patterns that may include incomplete sentences and/or asides, grammatical errors, verbal shorthand and some statements that may be less clear in print.)

EPISODE TRANSCRIPT:

JAY BELL:

I started, probably about six months ago, turning the radio off and turning my phone on and having a conversation with ChatGPT as I drive to work. So, I start thinking through a topic, I start framing out that idea, and I have a partner helping me think through a complex topic. By the time I get to work, I take that conversation, I email it to myself, I walk in the door, say hi to a few folks, maybe use the restroom, grab a cup of coffee, and within 30 minutes from walking in the door, I have output that, in the old world, would've taken me weeks to produce. I have a thought starter, I have a presentation, even a scoring approach built out in Excel. And again, 30 minutes from walking in the door. And I have multiple weeks’ worth of work product at my hands. So, huge benefit.

JUSTIN HICKS:

Welcome to Future of Risk presented by Zurich North America. We explore the changing risk and resilience landscape and share insights on the challenges that businesses face to help you meet tomorrow prepared.

AI isn't just for help with emails and written content. Today we're going to look at how AI literacy can multiply your impact in any role. I'm your host Justin Hicks and today I'm speaking with Jay Bell, Head of Innovation for Specialties and Head of Operations for Construction at Zurich; and Mark Breading, Senior Partner at ReSource Pro, which offers consulting and technology services to the insurance industry. Jay and Mark, welcome to the podcast. How are you?

MARK BREADING:

Thanks, Justin.

BELL:

Outstanding.

Real-world examples of everyday AI efficiency

HICKS:

Jay, I know that you and Mark are both very avid AI users. Obviously, I think Mark, in our pre-meeting you even said that you've been involved in this space for decades, <laugh> going back quite a while. And as both of you being avid AI users and supporters, we're looking to learn from you today. So, I was hoping you could start by talking a little bit about the first way that you used AI today because it's becoming something that we can all use in our daily lives, every single day, personally or professionally. So, I'm curious, Jay, how did you use it today to get things started?

BELL:

Great question, Justin. So, I was actually at an offsite leadership team meeting for the last week or so, and today was the day where we wrapped everything up. And if you've been to any leadership meetings, you'll find there's many flip charts, lots of things written on the wall, and it's always a challenge to have to then take all of that and then type it out, put it in the computer, and then synthesize that information and make some sense of it. So, today I was able to take a few photos, and in about 30 seconds—if that—I had all of the information that we had written all over the walls and on the flip charts, and was able to synthesize that fairly quickly, put it in an outline format, and disseminate that out to the attendees of the leadership session.

So, saved me a great deal of time and probably put it together in a better fashion than I would have previously. I will tell you another way that I tend to utilize AI fairly regularly, which is maybe a little atypical. I drive to work, you know, two to three times a week—go to the office, about a 45-minute drive. I started, probably about six months ago, turning the radio off and turning my phone on and having a conversation with ChatGPT as I drive to work. So, I start thinking through a topic, I start framing out that idea, and I have a partner helping me think through a complex topic. By the time I get to work, I take that conversation, I email it to myself, I walk in the door, say hi to a few folks, maybe use the restroom, grab a cup of coffee, and within 30 minutes from walking in the door, I have output that, in the old world, would've taken me weeks to produce. I have a thought starter, I have a presentation, even a scoring approach built out in Excel. And again, 30 minutes from walking in the door. And I have multiple weeks’ worth of work product at my hands. So, huge benefit.

HICKS:

That is unbelievable. The first example that you mentioned, as far as taking the pictures on the walls and turning that into an outline and disseminating that, how long did that take you?

BELL:

30 seconds.

HICKS:

<laugh>. I hope everybody else finds that as intriguing and humorous as I do because it's ridiculous how fast that happens. Mark, what about you?

BREADING:

Yeah, so actually the first thing I did this morning was—I’ve been interviewing for a new job, for not me, I'm hiring somebody. So, I had an hour interview yesterday and was reviewing the interview summary, and it's a fairly simple thing, right? Doing summarizations. But if you look at the impact, for me personally, like my style has always been, in the past, to take notes. So, if I'm doing an hour interview, I've probably taken six pages of notes, half of which I can't read because I scribble. Yet, with the AI assistant, I get not just the transcript, but a summary that's organized based on topic area, right? As opposed to the way you normally would kind of bounce around in an interview. So, it makes it much easier for me to remember what happened in that interview and do some evaluation and assessment of it.

So that's the first thing I did. And then, I'm making some visits next week to several insurers throughout Wisconsin. I'm going on a road trip. And so, for each of those, I asked some pretty detailed questions to really get an update—some insights on where those companies are today in terms of their strategy. Now, again, what would I have done 10 years ago? I’d go read annual reports, right? I’d do searches to find out current news about those companies, right? I’d look at their leadership team and see what they might be posting or what they might be doing. Very time-consuming, right? Like one prompt—you know, pretty detailed prompt—but boom, I've got it. And then I can review that as I'm traveling around and getting ready for the next meeting. There's just so many different ways that you can use the AI tools that are available today. That just happened to be what I did first thing this morning.

BELL:

Mark, when you're using it to capture meeting notes, have you also found – like I have – that it allows you to be significantly more present in the conversation than you would be otherwise, when you have to keep looking down and scribbling notes? I know it's been a huge benefit for me.

BREADING:

Absolutely. Yeah, absolutely. And so, you know, my primary domain is research, right? So, we do lots of interviews for research as well as some of these internal things that we have to do, or internal meetings. And for interviews—especially when you're interviewing someone to understand their use cases, the value they've derived, how they did it—it helps to really be focused on that individual. Like, usually if we have important interviews in the past, what we do is we'd actually have a note taker, right? Like, so I could drive the conversation and, you know, think about like, how do we get the value out of this discussion? So, somebody else is taking notes. I don't need that anymore. I have a note taker, right? So, it's tremendously productive.

Beyond search: Redefining daily work routines

HICKS:

It kind of goes back to what people talk about with multitasking. It became fashionable some years ago for people to get into an interview setting, Mark, and even say, “Oh, I'm a great multitasker.” And it's like, well, are you really, or are you just good at doing one thing, stopping, and then starting something else, and then stopping, and then doing something else? And you're not giving your all to either of those things, right? Your attention is automatically divided. And I think, Jay, that was a great call-out that you made about being more present in meetings. Actually, I wanted to point out also that I've used AI myself in one of my team meetings that I helped support for our leaders in our operations and technology space. I took the transcript from the meeting, dumped it into an AI tool, and it spit out a summary with highlights and all that stuff. I packaged that up, sent it off to people as a recap, and they loved it. So, it's clear that there's benefits to be had all over the place, and that it's not really just a search engine, right? I think that's kind of maybe how people think of AI, and maybe we need to reshape some thinking around that. Wouldn't you say, Jay?

BELL:

A hundred percent, Justin. But I think we've been conditioned to think about it in that way, right? So, over the past, you know, couple decades with social media, we have these small text windows. We operate with Google, we put small amounts of information in, and then we end up going and hunting and seeking. I would really encourage people, instead of thinking of it as a search engine, or, candidly, even thinking of it as a tool, I would think of it instead as a force maximizer, if you will, or a partner, or even a co-creator or collaborator. If you frame this differently in terms of what the real use case and benefit for this technology is, I think that empowers you to achieve different outcomes, rather than just going in and trying to find a single answer for whatever you're looking for at the moment.

BREADING:

Yeah. You know, Justin and Jay, the way I think about it is beyond search engines. So, you need to think about a couple of different categories of uses, right? One is one that I call translations, right? So, I have a number of text paragraphs, and I want to translate that into a diagram, right? Or I have a diagram, and I want to translate that into text paragraphs. So, that's one kind of simple usage that's quite valuable. Another is around analysis, right? Because, you know, that's where the real value comes in, where you're not just automating something, or not just summarizing something, but where you're actually asking the AI tool to do some analysis, give you some recommendations, give me the plan, you know. And as you all know, I mean, you can ingest any kind of information that you have.

It's a PowerPoint chart, or it's a spreadsheet or text—whatever it is—and ask for some analysis on that, and summary, and then some recommendations. You have to be thoughtful about how you ask for those, but you certainly can do that. And then the other is actually the content creation, right? Which was really the true essence of generative AI, right? It generates content. And there you have to be—I think it depends on your domain. What your role is, right? So, like in my role, because I write a lot of blogs, I do a lot of webinars, I write research reports, I write byline articles...

HICKS:

Can tell by all the books behind you, you're pretty well versed in reading and writing, right?

BREADING:

Yeah. That's one of about five of these kinds of things I have in my office here, right? <laugh> So, you know, we've done lots of experimentations—saying, you know, write a blog on this topic with these parameters, or ingest this research report we've just written and write a blog, you know, of the key ideas in here. So, it's fine; it can do that. And for some use cases, that's really useful. But in my case, we want to be authentic. And so, we've kind of made a decision a couple years ago—we're not going to do that, right? We produce, publish research for folks, and we want it to be our voice. Can you give it examples and have it write in your voice? Yeah. But I just am personally not as comfortable with that. But there's a lot of places where you're just, you know, writing a long email or correspondence to a customer or something, that it's incredibly helpful to actually generate content.

AI’s role in enhancing client relationships and strategic work

HICKS:

So, I'm curious, when you get that help with the content creation or the analysis or the translations, you're saving a bundle of time. What are you able to then do with that time that's been freed up for you? How does that make you better in your role?

BREADING:

Me? Go talk to customers. <laugh> Honestly, isn't that the objective that a lot of us have is they like --

HICKS:

For sure.

BREADING:

-- Reduce the amount of, you know, internal stuff we have to do and be out in the market, right? I'm a brand ambassador for ReSource Pro, so I do a lot in the market, and I talk to a lot of folks across the ecosystem so I can understand things like how they're using AI, and it gives me more time to do that.

HICKS:

Jay, same question. I'm curious, the AI gives you all this time and then you're using that time to do what?

BELL:

Well, think about it, Justin. I think we all, in our work lives—and candidly, even in our professional lives—are looking for more time, more capacity to get more done, right? And this is a partner, a tool and technology. It gives you the ability to have more time in your day for however you want to direct that time. How valuable is that? I think many of us throughout our lives, before, you know, we had the advent of generative AI, have probably looked, you know, in the mirror and said, "Man, I wish I had more time to get x done." Well, now we have something that helps us accomplish that, and I think we'd be silly to miss out on taking advantage of something that can give us more time to accomplish the things that we want to get done.

Empowering employees with AI literacy and enablement

HICKS:

I know that every individual is on their own individual journey—be it professionally or personally—but it's a wide spectrum, right? And people can be anywhere. You have people who are early adopters, such as yourselves. Jay, you've been a big proponent within Zurich of pushing AI and all the different ways that it can assist our business. And Mark, you obviously have a wealth of experience as well. But how do you think leaders should then manage, you know, as they figure out how to empower and guide employees to use AI? How should they do that?

BELL:

So, Justin, I love the question—particularly the part like, how should leaders think about empowering and guiding employees? And I think that's key, because I think too often, when most leaders think about AI, they want the next shiny tool, right? So, they're going to go out and grab a vendor that has a specific use case; they're going to inject that into a process, and they want that immediate ROI. Don't get me wrong, that can absolutely work. But I think to really successfully utilize AI in any organization, you have to spend a good deal of time engaging in AI literacy and AI enablement. You have to meet people where they are. And you need a robust framework to educate people on what this technology is, what this technology isn't, what you can rely on out of this technology, what you need to validate from this technology, and then give people appropriate use cases—and then just let them start to play and experiment. And then, rather than improving that one process where you're going to get ROI, imagine now you empower a hundred people to utilize this technology more effectively. The number of potential benefits that you can get by empowering a hundred people, I would wager, would far outweigh the benefit you're likely to get from the engagement of one specific tool or vendor.

BREADING:

I would say the biggest challenge that leaders have in this area is finding the right balance between governance and guardrails on the one hand, and innovation on the other hand, right? I happen to have as many conversations about governance as I do about technology and tools with folks, because, as a leader, you want to understand: how do I prioritize investment? Where am I going to get value, right? If I'm thinking of resources and dollars and projects, how do I know I'm going to invest in the right AI solutions and business use cases to get that value, right?

So, that's one part of governance. Another part is: how do I ensure that I'm working within regulatory boundaries, that I'm using AI in a way that is fair and equitable, right? That it’s accurate, right? Because we do need human judgment often to ensure that, hey, actually, what's being created here is authentic and accurate. That's a very important part of how we're going to leverage AI in different industries.

Many companies publish guidelines—you know, which tools you can use and how you can use them and things like this. But you can also take that too far, where you stifle innovation, right? Because, to Jay's point, you want hundreds of people, you want thousands of people out there experimenting, right? Because that innovation is going to happen from the ground up—people that are actually doing the work day-to-day that understand, hey, I got an idea on how I can use AI in my job, or how we can use it in our area.

So, you do need to empower them. You do need to enable them. You do need to give them latitude, right? And the permission to fail when they try things as well. So, it's a little bit of a balance to find the right way to do those things.

HICKS:

What I'm hearing is: you create the framework to allow for exploration, then you empower people to explore. I mean, is that fair? I mean, because it seems like a fairly simple concept, right? But maybe it doesn't always come across that way in organizations.

BREADING:

Yeah, and there's a piece in the middle, I would say, which is: you don't just say, here's the framework, go at it, right? There is the whole education and enablement piece, right? You’ve got to give people some avenues to go get some education or talk amongst their peers to understand who's doing what and how they might use these. So, there are certain heat seekers that are going to just be out there—they're going to find the stuff themselves; they're going to go do it. But if you want broad experimentation across the enterprise, you’ve got to have some programs in place to help people understand what the possibilities even are.

Creating an ‘Aha’ moment: Education is key to AI adoption

HICKS:

When you guys were talking a minute ago, it's funny—this is probably a horrible analogy—but where my mind went is: you have this really cool tool (we'll use "tool" for lack of a better term), and then if you don't put any type of framework or education around it, I'm just reminded of the electric football game from the seventies and the eighties. You guys remember that game? You just plug it in, and it just vibrates, and the guys are spinning around <laugh>—they're not really going anywhere. They're not doing anything. That's crazy. It seems cool. It seems cool, but it's like, you know, what is this? What are you supposed to do with this? <laugh>

So, you need some more direction. And obviously, video game and gaming technology has come a long way as well. So, with that said, how then were you guys able to adapt to it so quickly? And what if somebody is struggling—an individual, a leader has a person or a few people on their team that's struggling? You know, not everybody's going to be necessarily as enthusiastic as the two of you are, and so how do you help that individual come along on their journey?

BELL:

So, I've done a fair amount of this over the last year or so, and I think it takes a good deal of effort from a small number of people that are committed to educating their peers. And each individual that you onboard and show the value of this technology—essentially, it's almost a compound effect, right? So, if I have a conversation with one individual in an office, and then I leave that office, when I go back to that office a month later, it's no longer one individual that's playing with those tools. Now it's multiple individuals that are playing with those tools.

And so, the key from my perspective is: one, you need to demonstrate—almost get the aha factor—demonstrate something that's almost awe-inspiring. Like, really show them something that can save them massive amounts of time or accomplish something that they couldn't have accomplished previously. And then, once you've demonstrated how valuable it can be for them—and that's the key, not just how valuable in your own personal use cases, but you help them demonstrate how it can benefit them today, right? —and then you play with it a little bit, help them tweak their approach. And then it's just a matter of continuing to play around with it, continuing to experiment.

And what I like to tell people is: think about your day, right? And your workday. And I think all of us can say there are aspects of our workday that are a little bit more on the mundane side, right? And imagine, if you will, if you had a tool, technology, or even an assistant that you could offload—let's say—70 to 80% of those mundane tasks. I can promise you, as you become more proficient with utilizing this technology, that's a very real possibility. And the more you understand how to utilize it today, the faster you are going to be able to take advantage of the advancements that this technology continues to make, right? So, I've been playing around with generative AI since it came out, and what it feels like today is dramatically different than what it felt like when it first came out.

HICKS:

Yeah, yeah.

BELL:

To the point—it changes sometimes. And Mark, I'd love to hear your perspective on this. Sometimes it feels like it's changing month by month and getting better and advancing. So, as an example, when I first started trying to educate others on utilizing AI, I spent an inordinate amount of time diving very, very deep into prompt engineering. Today, I rarely talk about prompt engineering unless I'm dealing with a specific use case.

So, when I'm just educating people in terms of what AI is, how it works, how to get benefit out of it, I no longer spend the same amount of time on prompts. When they come to me and say, here's my problem—help me figure this out—well, then that's when we dive into what prompt or what approach in utilizing these tools is most likely to get us the outcome that we're desiring.

BREADING:

Yeah, you know, I find that most people are—I don't want to say stuck—but they have their way of their normal processes, the way they do business, and it's just not natural for them to think about doing things in a different way. So, what I try to do is just make suggestions, right? "Hey, you know what, here's a different way you could do this. You ought to try using Perplexity and ingesting this kind of data into it and asking this question and see if that helps you," right? And after you do that a couple times, then people start doing it on their own. "Oh, oh, I see."

And those are small, like one-on-one examples, but that works. Or you just show them what you've done. Like, "Hey, by the way, I had a problem the other day, and this is how I solved it, and it saved me an hour's worth of work," right? And when you start talking about time and efficiency and new insights, then you start to get people's attention.

I do want to say, Jay, to your question about how fast things are moving—you know, it's kind of my job, myself and our team, to follow all these advancements. And it is really difficult, right? I mean, just tracking what are the tools that are available in the marketplace, and what are their capabilities, and how are they evolving alone—it’s a challenge, because there's stuff coming out every day, right? And then it's the, you know, ChatGPT of September 26th, 2025, versus a month ago, or a year ago, right?

So, it is a challenge, but the only way to solve that is to do it, right? Just get in, get your hands dirty, get your colleagues working on it, trying things.

Choosing the right AI tool for your business needs

HICKS:

So, Jay, Mark, tell us a little bit about some of the different AI tools that are out there. Which ones should certain people use for different circumstances? I feel like there may be an issue where you may want to use one for one purpose but not another, and they maybe have different strengths.

BELL:

I probably defer to Mark. I think he probably knows more than I do to a degree, but to me, ChatGPT is still probably the big gorilla, right? But depending on use case—if I'm doing coding, I'm probably doing Claude; if I'm doing communication to other humans, also probably Claude, right? Gemini, I think, has got better image generation models, I think, although Sora is pretty good. Mark, what are your thoughts?

BREADING:

Yeah, it definitely depends on use case, on your role. In the research domain, I use mostly Perplexity Pro because I like the sourcing that it provides and easy access into, you know, where do they find that information.

BELL:

Agreed.

Adapting to continuous AI innovation in the workplace

HICKS:

I was going to say that I feel like the pace issue could be something that prevents people from diving in at all, because—or maybe just makes it more challenging for you guys to educate others—because things are changing so quickly. And because it requires so much time and effort and energy to learn something, and then it's like, "Oh, okay, that's obsolete now," or "That's outdated now." Have you found that you've been able to build on your knowledge efficiently, or has the technology been moving so quickly that sometimes you find yourself going back to the drawing board?

BREADING:

I wouldn't say I've gone back to the drawing board. You just try to track things every day and try things. And again, work with your colleagues on that.

BELL:

Most of my experience, Mark, when I think about the advancements—I'm obviously, part of my job is not necessarily to have to do the research and keep tabs on it in the same level of detail that you are, although I do make my best attempt. But, as I think about playing around with these, I tend to find out about the advancement sometimes just based on better outcomes, where I'm using it in a way that I've used it before, and all of a sudden I'm like, "Wait, it's better this time. The answer's better, it's faster, it's doing something different." And then I've had to go back and be like, "Oh, well, there's been a new update to the model that I wasn't initially aware of." That's been an interesting way to find out that something's been advanced—just based on the fact that it works better for you.

BREADING:

The other thing that I do is—since we track, at least in the insurance industry, how are people using AI in different forms of AI—then it gives you the ideas, right? As you're every day seeing new examples of company A is doing this, company B is doing that, and here's the business results they're achieving from that. Then it gives you that sense of what's possible and how you might apply that to your particular domain.

Lessons learned from early AI adoption

HICKS:

So, you guys, again, as I've pointed out many times, early adopters, knowing what you know now, is there anything that you would've done differently when you first began on your AI journey that maybe people could benefit from?

BELL:

1000%, Justin, 1000%. I think I maybe gave a little bit of insight to this in one of my earlier answers. So again, when I first started in this journey of trying to educate, you know, my peers and others across Zurich, I spent a ton of time focusing on prompts. Now, really what I'm trying to get people to focus on is: one, I want—I tell people to take a step back—like, think about intention, right? So, what is it that we're trying to accomplish?

The reality is that the vast majority of people that go to utilize these tools, their first use case is almost always speed, efficiency. They want to do something faster. And don't get me wrong, AI is a phenomenal, phenomenal technology to allow you to accomplish things more quickly. But I really encourage people to kind of focus on two themes.

So, the first theme is: I want people to focus on outcomes versus speed. So, I truly believe that if your intention in utilizing this technology is to achieve better outcomes versus just be faster, the speed will come naturally. And what it forces you to do is—it forces you to continue to iterate. So, if you're really focused on achieving outcomes better than you could have achieved without this technology, the only way that's going to happen is you continue to iterate. So, you get something back, like, "That’s not quite it. I need a little bit more of this." You get another version, "That's not quite it. I need a little bit more of this." And you keep going until you reach an outcome that is better than you could have achieved otherwise. So, for me, that's number one.

Number two—this goes along with the iterating—is, you know; context is king. So, the more context that I can provide as a prompt, right, the better off I'm going to be. And the easiest way, in my view, to achieve that is to use the microphone capability to either dictate your prompt to it or to actually have a conversation with these tools. And I know that sounds weird—I put it off for an incredibly long time because it felt very inauthentic, very artificial. But once I got over the hump and actually started to see the value in having discussions with this technology, again, as I mentioned before, I think of it now as a partner, as a co-creator, as a collaborator that allows me to digest significantly more information and then review more potential scenarios so I can almost pick the version that I want, right? So, I think of it in that way. I also think it allows you to move the starting line significantly from where it was before the advent of this technology.

HICKS:

Awesome. What about you, Mark?

BREADING:

Yeah, for me, I would just be more aggressive in my ramp-up in my experimentation. So, you know, ChatGPT officially released to the public November 2022—you know, I started using it right away, but not as aggressively. As I look back, I should have been using it more aggressively. And as other tools started to come out, I should have been using them more aggressively. You know, and just ramping up and collaborating with other people who were really trying to understand the space. I probably didn't go as fast as I could have or should have. I guess that would be my number one advice.

Five ways AI can boost your professional productivity

HICKS:

Well, again, everybody's moving at their own pace, and so you're still ahead of the curve. I feel like that's why we brought you here today on the Future of Risk podcast. So, I think you're doing okay. Don't be so hard on yourself, Mark. Don't beat yourself up. <laugh>

Okay, we've covered a lot of ground—we've covered a lot of ground. I'm curious, getting back to the theme of today's episode, which is five ways that anyone could benefit from AI today, right now, where they're sitting listening to this. And you guys have offered numerous examples already, so this may be slightly redundant, but I'm curious from your perspective: what are five ways anyone could benefit from AI today in their professional life?

BELL:

So, number one: clarity. Utilize AI to help you untangle difficult or complex problems and see them from new angles or different ways than you would have before.

Creativity—so you can jumpstart brainstorming sessions, generate fresh ideas, flesh things out a little bit.

The more obvious one that most people think of first would be efficiency. So, it would be number three: to summarize long documents, emails, redraft information, you know, summarize notes, as we mentioned before—allow you to focus on what matters most.

One that I think people don't necessarily think of this technology for, but I think it's incredibly valuable, is learning. You can utilize this technology essentially as a tutor, and it can help explain really difficult concepts. You can actually role-play various scenarios. It can guide you through learning new skills.

And obviously, communication, which kind of goes along with efficiency to a degree—draft, refine, or even role-test various messages to help make sure that the content that you're providing is landing in the way that you would want it to. I mean, so for me, it's really shifted from being, you know, a tool that I was using occasionally in the beginning to—it's now a partner that I use virtually every day. In fact, I even try to be AI-first, and I try and utilize AI almost at the outset when I'm digging into a new issue. Now, granted, it's not always going to help me get through everything, but even in those situations where it doesn't directly benefit me for that particular use case, I'm still upskilling myself to a degree.

And then I'll throw in one bonus one, because I think that was already five—but the bonus one is: I think at the outset of the podcast, you mentioned my dual role. One of those roles—I’m fairly certain that the only reason that I got it is based on my early adoption and consistent advocacy of AI, particularly AI literacy and AI enablement.

BREADING:

I do think there is a benefit to enhanced search, right? For information retrieval, organization, summarization—and you might call it super search. There are benefits just at that level.

Certainly, content creation—anything that you have to write, to present, to speak—you know, you can get aids for creating that content, for yourself or for others.

Content translation I've already mentioned earlier—from one format to another, or making it look better and enhance that.

Insights and patterns—I think when we look at the broader AI, that's where there's a lot of value that's going to be coming from it, as well.

And then just efficiencies—you know, task automation, workflow automation—just improving productivity is certainly another one as well. I'm not sure if that was five, but I was just kind of rattling off what I see as some of the benefits.

HICKS:

I think you guys pretty much covered it, and I very much appreciate your time today, because this was a powerful conversation. And I feel like anybody who is maybe new to AI, or wanting to stick their toe in the water, or is maybe a little bit further on that journey but still looking for some more either confirmation or some new ideas on how to use it, they will have benefited from hearing the two of you speak on it today. So, thank you very much for being the longstanding advocates that you are, and we appreciate you joining the podcast today.

BELL:

Thank you very much, Justin.

BREADING:

Thanks for inviting me.

HICKS:

And thank you all for listening. Stay tuned to our next episode in the series where we look at the darker side of AI with Barry Perkins, Chief Operations Officer at Zurich North America, and Adam Page, Chief Information Security Officer at Zurich North America. If you like the show, you can leave a comment or review wherever you get your favorite podcast, or you can drop us a note at media@zurichna.com. This has been Future of Risk presented by Zurich North America.