Amin Venjara, Chief Data Officer at ADP, speaks with Brian Boxman, VP of Sales at Incorta, in a video interview about AI as a tool, focusing on outcome-driven implementation, real-world application, and responsible innovation.

AI as the next tool in the toolbox

Venjara shares perspectives on how artificial intelligence is being understood, implemented, and leveraged to deliver meaningful outcomes across both product development and internal operations. “AI has been heavily discussed internally and externally. We’re always thinking about what that means with the new capability,” he says.

For Venjara, AI is not a sudden disruption but rather part of a continuous evolution of transformative technologies. “This is like the latest tool in the toolbox,” he says, noting that organizations are bullish on AI possibilities. He emphasizes that, like previous tech waves, AI is another inflection point of how work gets done.

Outcome-driven implementation

“One of the things that we’d like to just focus on and drive is the outcome we are trying to achieve,” notes Venjara.

Instead of chasing AI for its sake, he advocates for aligning technology use with specific business goals. He stresses the importance of data — particularly how organizations manage and prioritize it.

“Are you going to get 100% coverage across all of your data? No. But what you’re going to be able to do is focus on the outcomes you want to achieve, and then the data that’s needed to make that happen gets really good.”

Real-world applications

Venjara outlines two major areas of focus when it comes to real-world applications of AI

• Reimagining customer-facing products
• Enhancing internal operations

To illustrate the product innovation front, he points to ADP Assist, an AI-powered capability launched over 15 months ago. “ADP Assist is like an umbrella of how we bring these AI capabilities, and think about it as this assistant that sits with you and throughout your workflow… It can be proactive, it can nudge you, and it can be cross-domain.”

ADP Assist is designed to be contextual and intelligent, helping users across domains like payroll, HR, talent, and benefits, says Venjara. He then shares a use case of payroll anomalies:

“We looked at the data of where errors were occurring for our clients… Like the tax ID example. I’m paying somebody, but they’re working in a new location, and I didn’t set up the tax location.”

By proactively identifying and alerting users to potential issues, EDP Assist mitigates downstream consequences, which are particularly critical for smaller clients, says Venjara. This drives value for customers.

Responsible innovation at scale

Moving forward, Venjara acknowledges that AI implementation requires thoughtful governance.

“Everybody’s out there trying to build and assist. How do you drive and leverage the data but do something that you can marshal the organization around and have a way to make that safe and responsible while still providing value?”

On the operational side, the organization is seeing measurable gains in contact centers, where it implemented AI for note-taking after calls. “We’re already shaving nearly a minute off of calls,” Venjara adds. That seemingly small gain, when multiplied across millions of interactions, translates to real efficiency and better client experiences.

Speaking of development processes and software development in particular, Venjara states, “There are actually really good capabilities now that allow for thinking about testing and developing unit test cases to make it more effective.” AI helps ensure code changes are appropriately tested, avoiding unnecessary tests and improving software quality, he concludes.

CDO Magazine appreciates Amin Venjara for sharing his insights with our global community.