Explore what it really means to embrace AI in the workplace with Sri Shivananda, Chief Information Officer, and Tony Wimmer, Head of Data and Analytics at J.P. Morgan Payments, in conversation with host Bria Bell, Vice President, Communications. Recorded at the March 2026 Global Town Hall, Sri and Tony reflect on navigating AI uncertainty, reframing anxiety as a signal to act, and building the habits and skills that turn disruption into transformation. Tony shares a simple but powerful analogy — learning AI is like learning to drive — and walks through the practical steps anyone can take to get started, regardless of technical background.
Explore what it really means to embrace AI in the workplace with Sri Shivananda, Chief Information Officer, and Tony Wimmer, Head of Data and Analytics at J.P. Morgan Payments, in conversation with host Bria Bell, Vice President, Communications. Recorded at the March 2026 Global Town Hall, Sri and Tony reflect on navigating AI uncertainty, reframing anxiety as a signal to act, and building the habits and skills that turn disruption into transformation. Tony shares a simple but powerful analogy — learning AI is like learning to drive — and walks through the practical steps anyone can take to get started, regardless of technical background.
Narrator (00:02):
Welcome to Pay It Forward, a podcast by J.P. Morgan Payments for J.P. Morgan Payments. Get to know our business and gain a better understanding of where we sit at the intersection of technology and finance. Did you know we move nearly $12 trillion dollars globally each day through over 170 countries and 120 currencies at more than 5,000 transactions per second? Join us as we take you inside the stories, technology, and people that make it all happen.1
Bria Bell (00:38):
Hi, I'm your host, Bria Bell, Vice President on the payments communication team, and this is part one of our AI miniseries. Today you're tuning into an excerpt from a recent global town hall conversation with Sri Shivananda, Chief Information Officer, and Tony Wimmer, who leads data and analytics and has spent nearly a decade in payments. This discussion was designed to help our teams better understand and embrace AI, where to start, how to think about it, and what it means for the way we work. You'll hear practical insights and real world perspectives, including a simple but powerful analogy from Tony on how anyone, regardless of technical background, can begin using AI. With that, I'll let Tony and Sri take it away.
Tony Wimmer (01:18):
Hey, I'm Tony Wimmer. I work in data analytics for payments for a little bit over nine years. And to be honest, it is the craziest time I've been here and it feels a little bit overwhelming at times. I think what's important is that we will remember, while this is a tech transformation, it's never just about tech alone, but it's always about also a people transformation. How do you make the tech work for our people? And that's ultimately what we're currently experiencing. We're learning together. We are going to figure this out by leaning in by learning the tools as everybody said right and figure out how to ask the right questions to the right tools.
Sri Shivananda (01:51):
I share the feeling with you. In fact, there's a lot of transformation happening in the area of software engineering and the pace is actually compounding and code is becoming cheap as in it's going from being artisanal to being manufacturable at this point in time. And we as a technology organization are adopting it and moving in that direction. But during this moment, what's important to do is to take that anxiety, a little bit of fear, a little bit of uncertainty and put it to work. It's not a weakness, it's actually a signal, it's a strength. You have to lean in. And this is a moment if you're tinkering, you're testing, you're experimenting, you're exploring, that's how you build courage and those will give you the strong instincts on converting this disruption into a transformation. So the right thing to do is, yes, it's a moment of change, but it's not the first time we've seen change. We are people who are intellectually curious. We have to have intellectual humility. We are to learn. We are to just take that next step so we can get going.
Tony Wimmer (02:47):
One thing I've learned in my career is whenever there's a time of great uncertainty, best action is to take action. You learn by doing, you learn by getting into the game. And I wanted to share this analogy with you of how leveraging AI is actually like driving a car. I don't need to know every little detail of how the engine is manufactured or the powertrain. I can still be one of the best and fastest German drivers on the road, right?. So what does it mean in the terms of AI? Number one, learn how to drive, like learn the basics, learn the tools. I actually recommend to everyone in payments to become AWS certified.
(03:22):
Take the AWS certified AI practitioner certification. Not technical, but you learn a ton. Number two, know your road conditions, right. Figure out what's a good use case and what should you better not let AI handle right now. And number three, when that engine light flashes, it's time for an oil change, you got to know how to maintain your car. It means you got to know how do you keep your knowledge current. That's exactly what we've been doing over the last two years.
Sri Shivananda (03:49):
Your analogy actually reminded me of something. I don't know how many of you taken a self-driving car. It is the most sophisticated use case of AI built over the last 20 years. And now in cities like San Francisco, in a terrain that's actually hard to drive in, what AI has been able to do is to make the most complicated thing humans do, which we do instinctively, something that you can do in a driverless way. That's the potential of this technology. I've been tinkering around with this technology since the ChatGPT moment in December 2020, I guess. And I spent about three to six hours on a weekend on this tech, primarily because I run a technology organization and if I need to have a good conversation with my engineers, I need to know what the tech is. And I've been able to do a lot of things with it.
(04:33):
One, brainstorming with it to actually understand concepts very deeply. Number two, throwing data at it and getting visualizations that are stunning and you can understand a lot more from it. Third, to be able to use apps where I can design certain interfaces and send it to my team instead of saying it in two words, you know what leaders do, we write one line to our team and they have to figure everything out. Now I'm able to create a mock-up and send it to them more properly describing it. Of that matter, tinkering and building apps and things of that nature. Code has become easy to do, but I want to just highlight the fact this is not just about coding. You may be in different functions where you don't need coding on a day-to-day basis. These tools are still helpful. And the first step to take is just pick one, start to use it, play with it, get comfortable with it and ask a friend.
Tony Wimmer (05:19):
To make it more concrete, I want to shift to a capability that the team and I have become focused on: chat as data. Ultimately, you can type a question like, have there been any transactions processed in my merchant services transaction division? Give me five sample transactions, include a transaction identifier. On the right-hand side, "Hey, what's the current
active fee schedule for this company ideas client?" And I didn't even have to type it in. I could just track to my LLM suite, proving the point these technologies move so quickly. Why do I obsess about this type of work use case? Number one is I think there's a lot of opportunity for team productivity and the general purpose version is kind of cute, but it doesn't really unlock value as general purpose. But what we've seen is the teams that start to really use this heavily and that need to retrieve so much point-to-point information.
(06:09):
This is a great, great tool. So we are using this, these early versions to figure out what are the workflows that would benefit the most from these type of capabilities? Number two though, is why I'm obsessed about this. This in my mind is the unlock for everything else because in order to get this use case to work, you actually got to teach the AI about your business. You got to teach the AI all the context about how our data fits together. It's called the ontology or the systematic layer. It is incredibly hard. The entire industry is trying to figure this out. How do you make your data ready for AI? And coming back to your point is you got to get in the game. You cannot build this on day one, but I think you're learning together and this is probably going to unlock a lot of the AI, the agent to agent future going forward.
Bria Bell (06:58):
That was Sri and Tony on what it really means to embrace AI, not just as a technology shift, but as a fundamental shift in how we work. What really stood out to me is the emphasis on action, not waiting until everything feels fully understood or perfect, but leaning in, trying things, experimenting, and building confidence through doing. That idea of learning by engaging really resonates in a moment where the pace of change is only accelerating. So how have you started using AI in your own work? Is there a moment where it shifted from concept to practical tool? One piece of advice I have for someone just starting to experiment with it, don't wait until you feel ready to start. Just start. Think of it less like a tool you need to master and more like a thought partner you're having a conversation with. The more you interact with it, the better you'll get at asking the right questions and unlocking its full potential.
(07:48):
Every prompt you write is a small experiment and even the ones that don't land, teach you something. Give yourself permission to be a beginner. And honestly, that's what excites me most about this moment. AI isn't just changing the tools we use, it's changing how we approach problems, how we collaborate, and how we grow in our roles. Thank you again to Tony and Sri for sharing such thoughtful perspectives and for setting the tone as leaders, encouraging the teams at J.P. Morgan Payments. And stay tuned for part two of our AI miniseries where we'll continue exploring how this transformation is showing up across our business from operations to product and beyond.
Narrator (08:26):
Thank you for tuning in to Pay It Forward, a podcast by J.P. Morgan Payments for J.P. Morgan Payments. If you're interested in exploring career opportunities at J.P. Morgan Payments, please visit jpmorgan.com/careers and enter the word payments for relevant opportunities. Stay up to date on the latest stories, technology, and people powering payments by subscribing on Spotify, Apple Podcasts, or your favorite podcast platform. Keep pushing boundaries and we'll keep moving the payments world forward one transaction at a time.
Sources:
1: https://www.jpmorganchase.com/ir/annual-report/2025/ar-ceo-letters