Don't Try to Boil the Ocean: Lessons From the AI Front Lines

Before we get into the meat and potatoes of the conversation, I thought it would be appropriate to really kick off with a bit of a state of the nation in terms of how FIs are experimenting with AI and what the adoption curve looks like, because I think it'll set the conversation up well.

I remember a couple years back at our conference, Connect, where I sat with a group of folks around the table at lunch.

Really, post-ChatGPT had taken the world by storm.

Everyone was experimenting, but everyone was also fearful what this could mean for their respective business and really maybe the world writ large.

And so while there have been certainly folks that have pushed back against the rapid adoption of AI solutions across the workplace and across the world.

I think we're starting to see that early experimentation turn into real life use cases that can drive businesses forward, whether that comes from cost efficiencies that can be gained implementing AI in the back office, new revenue expansion opportunities in terms of helping acquire customers in a far more personalized way.

but also just the productivity gains that folks can get having a helpful assistant by their side working with them to solve real customer problems.

And so I think it's fair to say that that early skepticism from what were once flashy demos has turned into something resembling conviction that AI is going to be here to stay and it is going to be a true force in enterprise business transformation, in particular, financial services transformation.

And so today is a conversation, I believe, with two leaders who really embody that shift from early experimentation to strategic adoption.

And so really excited, Brian and Michael, to have this conversation with you.

So maybe to start, Brian, Michael, would love for you to introduce yourselves, your role and where you're at in your adoption journey.

So, Brian, let's kick off with you.

Yeah, thanks, Corey.

I'm the VP of Digital Strategy for Stanford Federal Credit Unions.

So being in the role for a little bit over five years now and being with the credit in almost 10 years, where we at is really we are at a selective stage at this moment to know selecting the type of AI that we wanna implement.

And we serve over close to 100,000 member and $4.5 billion in assets for Stanford.

Yeah, Corey, Michael Purefoy, Chief Treasury and Digital Banking Officer here at Vera Bank.

Vera Bank is a 96-year-old community bank with $4.5 billion in assets and 42 branches across East, Central and Southeast Texas.

And I would say that we started this journey and really started putting focus on it about 18 months ago or so.

Really since the beginning of the year, what we've been doing is trying to build that foundation and establishing what we feel like are the core elements needed to scale this appropriately and responsibly.

And so we've invested in a dedicated AI leader and we're building a team around that person because we don't wanna treat this like a side project in IT.

We don't feel like that that's not, Not going to be a recipe for positive growth there with this technology.

We spent a lot of time around governance and developing and trying to align our bank with regulatory expectations, even sharing that governance with the OCC and getting their feedback on it.

And we've spent a lot of time with our leadership team because we felt like that if our leaders were not going to engage with the technology, we couldn't expect the others within the bank to engage either.

And so we've looked for opportunities across multiple work streams.