Innovations in artificial intelligence (AI) will impact people across the workforce differently depending on their roles.
ADP Ventures’ Usman "Oz" Khan shares ways leaders can think about how AI technology can be tailored to address the unique needs of different teams.
For more information, visit ADP.com/SPARK
Transcript:
I think there's there's multiple trends hitting the workforce landscape, if you will. And I would compartmentalize them in a couple of different categories. One is where the work is getting done. If you have a white collar environment, there's this push for productivity. And how do we actually enable or white collar employees to be more effective, more efficient, and really leverage this new toolkit that's come out?
If you're looking at blue collar industries, where would you want the frontline to be doing? How do you take the traditional efficiency that you had on the frontline and supercharger with AI, i.e., you reduce process, you essentially make people a lot more effective at their day jobs and so on, so forth. And so that's what you're seeing on the front end.
And then there's the supporting layers of the organization. So a company like ADP we support HR teams, but we also support the middle layer of operating teams that help you run your company and run your organization. And and that's where you're seeing a lot of thoughts around anything that's manual.
Anything that has more human intervention than you would like. People are investing to try and make that much more efficient, because this reasoning ability that generative AI is brought, that actually enables you to do things much more differently than you would five years ago, for instance. And so you're seeing a lot of capital flow into that application layer.
But there's also this need to just modernize what you had. It's really about picking and choosing where you want to start and then expanding from that particular use case. And this whole, hey, let's just apply AI across the board. Boiling the ocean is a very real thing right now, especially when it comes to enterprise systems that have existed for a number of years and that are pre-AI. It's easy to get lost in this realm of why you're trying to integrate some of this tech.
And you may not have, the semantic layer work to that extent where you can identify where things are and you may not be that effective. You might be taking on more than you can chew with a particular integration, which is why it's always good to start off with one use case. And connect a workflow or a tool to or a new, more modern solution and, and go from there.
