The same thing is true, for example, with testing, which is incredibly automated, using different technology, including AI. We are continuing to use AI in the way we run our business, for example, in how we look at our accounts payable and receivables and finding ways where we can optimate to have better efficiencies there. We are using it today in the way we are delivering our consulting services as well and definitely very much so in how we look at sales and being able to predict based on lots of factors. Should we be running after the sale or not, or can we show the data that these €“ this is not the right kind of sale, we are not the right fit. So, we have increasingly been using AI, both in how we deliver services as well as in how we run ourselves.
Of course, our SynOps platform for operations is also AI-enabled. It’s one of the reasons why clients turn to us because it’s helping them digitize faster. They are not having to build these things. So, long-term, we see these technology changes, things like generative AI is playing to our strengths because to use these technologies, it requires deep understanding of the industry, the use cases, the process changes. When people talk about the new kinds of generative AI, which we are super excited about, being like a co-pilot to human beings, the entire process has to be changed in order to make that work. You have got to up-skill the people and you have to be able to do all of that in a very responsible way. So, we are already working with.
There has been a lot of demand to understand this. And in understanding it, understanding actually how hard it is to be able to implement at scale in an enterprise versus, I am assuming you are €“ we are all having fun playing with it, but how you build that into an enterprise is very different and a great opportunity, and we are partnering with all the major players to help them take the technology go from technology to implementation to impact.
Lisa Ellis: Thank you.
Julie Sweet: Thanks Lisa.
Operator: And our next question comes from the line of David Togut with Evercore ISI. Please go ahead.
David Togut: Thank you. Good morning. Could you delve into demand trends in the financial services vertical in a little greater depth, especially given the evolving banking crisis we have seen in the last month or so, particularly with some of the regional banks struggling? And maybe as part of that, if you could just remind us of your profile within bank-related IT services, smaller banks versus regionals and money centers.
Julie Sweet: Sure. As a client base, we skew towards the larger banks across all of the markets. So, we don’t comment on individual clients, but we don’t have any big exposure to kind of the smaller regional banks and in general. So, as you sort of think about the stepping brake, obviously, the developments on the banks for the €“ are still early in the last couple of weeks. So, as I talk about demand trends for our clients, which are generally the bigger banks, a couple of things really stand out. So, first of all, there is a lot of focus on their technical debt, because the banks, a lot of them are still in the mainframe. Our mainframe practice really across industry has growing like gangbusters right now as clients across the industry are really having to take on some of that harder technical debt, which they need to do because the more and more they digitize their services, which is a continuing trend in financial services, if the systems behind it aren’t agile, then it can take a lot of time to introduce new services.
